University Of Pennsylvania

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY Opioid addiction is a chronic, progressive disorder that fuels the current US epidemic of opioid overdose deaths. Over the years, a tremendous amount of research effort has been devoted to understanding the biological roles of opioid receptors and developing newer generations of synthetic opioids to treat pain and combat opioid addiction. However, given the advancement of contemporary and novel neuroscience technologies, we have the tools to think beyond mu-opioid receptors (MORs) to develop improved OUD therapeutics. This proposal aims to investigate the architecture and function of endogenous MOR-expressing neural circuits in the brain and to determine how these circuits maintain cellular dependence and drive brain-wide maladaptive plasticity across different stages of the OUD cycle. In four complementary aims, we will first map the shifting structural and functional connectivity of opioidergic networks using viral-genetic and tissue clearing methods to identify monosynaptic inputs to withdrawal-active MOR-expressing cells and axonal output projections, as a function of opioid exposure and abstinence. We will then integrate these input/output maps with cell-type information and gene expression changes within dependence networks using hyper-multiplexed 3D in situ hybridizations to generate the anatomic localization of hundreds of dependence-related genes, targeted to cell types and retro- labeled connections. Finally, to reveal how MOR-expressing cells within core regions are modulated during opioid exposure in real-time, we will use miniature head-mounted microscopes to image the population activity— at cellular resolution—across weeks of opioid exposure and withdrawal. Our models will provide formal summaries of activity, connectivity, and gene expression as they evolve with repetitive opioid exposure and withdrawal, and our datasets will be made publicly available as they are generated. To bridge these experimental measurements and provide a common framework for our analyses, we will adopt Network Control Theory to identify brain nodes that drive the transition between opioid dependence states to identify potential candidates that disproportionately drive each state.

NIH Research Projects · FY 2025 · 2021-09

Project Summary/Abstract Urgency urinary incontinence (UUI) is a biomarker of falls risk and disproportionately affects older minority women living in urban communities. Over 50% of an estimated 10 million women age 70 and older with UUI will experience a fall. A fall compounds the functional dependency already present in older women with UUI making their quality of life worse than that following a stroke. This proposal addresses a key research gap: existing fall prevention interventions cannot be applied to women with UUI and effective interventions that reduce falls in older community-dwelling women with UUI are lacking. Our objective is to establish the effectiveness of a novel multidimensional intervention to reduce falls in older women with UUI. This intervention is based on the hypothesis that falls in older adult women with urinary incontinence are the result of urinary urgency related anxiety in the setting of reduced lower limb muscle strength, poor balance, and environmental hazards. Our trial will show that a tailored intervention that addresses each of these interdependent factors through integrated behavioral bladder training and urge suppression, strength and balance exercises, and home hazard assessment will reduce falls and improve urinary incontinence in older community-dwelling women with UUI. The investigators of this proposal have already developed and validated the intervention in pilot studies and now propose a randomized controlled trial of 314 women to rigorously establish its effectiveness. Our specific aims are: 1) To determine the effect of a tailored integrated exercise and bladder training intervention on falls in older women and 2) To determine the effect of a tailored integrated exercise and bladder training intervention on urgency urinary incontinence in older women. The trial will use a community-engagement approach to recruit women living in an urban core community with high proportion of minorities. This trial will be the first adequately powered study to test an intervention for reducing falls in older community-dwelling women with urgency urinary incontinence and also the first adequately powered study to test the efficacy of a physical exercise intervention for the treatment of urinary incontinence. This study will have significant public health impact because it will establish the clinical effectiveness of a scalable intervention that targets two common highly morbid conditions: falls and incontinence in older women.

NIH Research Projects · FY 2025 · 2021-09

Project Summary An ongoing outbreak of a novel coronavirus infection (COVID-19) has claimed millions of lives and disrupted social infrastructures around the world. Fortunately, the new mRNA vaccines from Moderna or Pfizer/BioNTech are highly effective against SARS-CoV-2. However, much remains unknown about the longevity of memory responses generated by the new mRNA-based vaccine platform in humans. With the emergence of new viral variants, there is also the need to have a flexible type of immunologic memory that is not only long-lasting but can also respond to mutated viruses. My lab studies human T cell memory. We have shown that the human pre-immune T cell repertoire for a novel pathogen is shaped by past antigen experiences and contains cross- reactive memory T cells that could compete with naïve T cells. Using a highly effective live attenuated yellow fever virus (YFV) vaccine as a model for novel infectious challenge, we tested how pre-immune repertoire impacts post-vaccine response. Multiple YFV-specific populations were identified longitudinally within the same individual using peptide-MHC (pMHC) tetramers. Extensive single-cell T cell receptor (TCR) sequencing on tetramer+ cells was used to follow progenies of the same parent cells over time. We found that vaccine selectively recruits initially rare but more responsive T cells, leading to better repertoire fitness and higher TCR diversity after vaccination. Having a diverse TCR repertoire has been directly linked to protective T cell responses and host survival in mice. For fast evolving pathogens, the diversity in T cell composition may additionally limit escape variants as mutations emerge. Here, we will use the mRNA vaccines for COVID-19 (COVID vaccines) as a model to study the durability and the breadth of T cell responses elicited by mRNA- based vaccine strategies. We hypothesize that effective peripheral T cell selection is critical for maintaining durable immunity against actively mutating viruses. Here we will build on established biological insights, resources, and donor recruitment infrastructures to determine: (1) if COVID vaccine drives effective repertoire selection and diversification, (2) how boosting enhances CD4+ T cell diversity and variant recognition, and (3) how post-vaccine memory cells are maintained and change with time. The proposed experiments will map the entire trajectory of vaccine-induced response using precise molecular and cellular tools. Data from this study will provide vital knowledge on the quality, the breadth, and the longevity of CD4+ T cell response to the mRNA vaccines in humans. Beyond COVID, insights revealed by the proposed research will be relevant for understanding how immunological memory is generated and preserved. The proposed research will therefore have broad impact and could aid future development of improved vaccine strategies for other pathogens.

NIH Research Projects · FY 2025 · 2021-09

Grant #U01ES036367 Americans living in low-income neighborhoods in the US fare worse across nearly every health indicator compared to Americans living in higher-income neighborhoods. In Philadelphia, the location of this study, these differences culminate in a stark longevity gap, with average life expectancies in low-income neighborhoods being 20 years lower than in nearby affluent neighborhoods. The fundamental cause of poor health in low-income neighborhoods is a constellation of reduced economic opportunities, financial insecurity, and adverse environmental conditions, which act in mutually reinforcing ways to harm health across generations. To date, most interventions targeting low-income neighborhoods have focused on changing behaviors for individuals living within them or single neighborhood-wide factors that impact health. However, by failing to address the multiple, reinforcing mechanisms that generate persistent health disadvantages for Americans living in low-income neighborhoods, existing interventions have had limited impact. We propose to develop and test a radically different approach in which we intervene on multiple upstream drivers of health in unison to more substantially and durably improve health among Americans in low-income neighborhoods. This new approach is motivated by the insight that overcoming multiple, reinforcing threats to health will require significant concentrated investment in the structures that have left these neighborhoods in peril. Specifically, we will conduct a cluster randomized controlled trial (RCT) of a suite of place-based and financial-wellbeing interventions at the community and individual/household levels that address health. At the community level, we address underinvestment in low-income neighborhoods by implementing vacant lot greening, tree planting, and trash cleanup. At the individual/household levels, we increase access to public benefits, financial counseling and tax preparation services, and emergency cash assistance. We will test this “big push” intervention in 60 neighborhoods low-income neighborhoods, with up to a total of 720 adults. We hypothesize that this “big push” intervention will have significant impact on overall health and wellbeing, psychosocial distress, food insecurity, social connectedness, and crime. This proposal is innovative because when implemented simultaneously in targeted geographic areas, the suite of interventions will address the multiple mechanisms by which living in low-income neighborhoods harms health. The positive health impacts will be multiplied and longer-lasting what would be achieved by implementing any individual component. The results of the proposed research are expected to have significant public health impact as it will provide timely and scalable evidence of new strategies to more effectively promote health in low-income neighborhoods.

NIH Research Projects · FY 2024 · 2021-09

PROJECT SUMMARY As a prominent leader in the nationwide shift towards value-based payment, Medicare has implemented large fee-for-service population- and episode-based alternative payment models (APMs) that hold organizations financially accountable for the quality and costs of care. However, these APMs are not designed to protect access or outcomes for Black and Hispanic patients and those patients with low socioeconomic status (SES). These patient groups already face significant surgical disparities compared to other individuals. These disparities could worsen further under both APM types if participating providers engage in patient selection that reduces these patients’ access to surgical procedures or changes their care after participating. Because policymakers must make critical decisions about how to use different APMs to catalyze nationwide reform, insight about how population- and episode-based APMs affect surgical disparities for Black, Hispanic and low-SES patients can help policymakers determine how to best design, refine, implement policy adjustments, and scale up different models to safeguard the care of these patients. This study examines how prominent Medicare fee-for-service population- and episode-based APMs that are highly relevant to surgical care affect disparities in surgical access and outcomes for Black, Hispanic, and low-SES patients across insurance coverage type, and whether effects vary by providers’ financial attributes related to APM incentives. We hypothesize that APM participation will be associated with widened disparities in surgical access and outcomes (quality, utilization, and cost) for Black, Hispanic, and low SES patients vs. other patients, after providers begin participating in APMs. We also hypothesize that the impact on surgical disparities will vary by providers’ financial attributes – experience with financial risk and payer mix – related to APM incentives.

NIH Research Projects · FY 2024 · 2021-09

Abstract. The proposed project concentrates on technology developments to enable high sensitivity, bias-tolerant spectral CT for accurate quantitation of iodine concentration. Spectral CT has the potential of providing true quantitative information of tissue composition and provides an avenue for combined functional and structural imaging. High- sensitivity spectral CT accommodates anatomical sites that are traditionally hard to image, and reliable meas- urements of iodine perfusion allow additional quantitative measures such as tissue texture to aid diagnosis and clinical decision making. In the case of pancreatic cancer, the complex tumor microenvironment and the conse- quential poor perfusion characteristics lead to difficulty in diagnosis, staging, and treatment assessment. The need for visualizing low-enhancing lesions and the benefit of extracting quantitative information directly from image data strongly motivate a high-sensitivity imaging modality for reproducible iodine measurements. The need for visualizing low-enhancing lesions and the benefit of extracting quantitative information directly from image data strongly motivate a high-sensitivity imaging modality for reproducible iodine measurements. How- ever, state-of-the-art spectral CT presents large quantitation bias, i.e., inaccuracies in measured iodine concen- tration compared to the truth. We identify three major sources that contribute to quantitation bias: imaging system (e.g., spectrum mismatch), post-processing (e.g., biased estimator), and patient (scatter, beam hardening). The bias effect in current spectral CT cannot be fully eliminated by increasing radiation exposure, and has complex dependencies on the imaging system, imaging techniques, patient habitus, and processing algorithms. This in- accuracy is a major impediment to pancreatic cancer management and quantitative applications in general. The overall goal of this proposal is to develop robust, high-sensitivity spectral CT solutions that will enhance sensi- tivity and reduce variability in iodine quantitation, which in turn enables accurate, high-performance spectral biomarkers for disease management. The following specific aims will be pursued: (1) to develop an end-to-end, modular theoretical model for robust spectral CT design and optimization, (2) to develop bias-tolerant processing pipeline, and (3) to implement and evaluate high performance, hybrid spectral CT solutions on an experimental CT bench. Completion of the proposed efforts enables robust, high sensitivity spectral CT for improved tumor detection and characterization through accurate, high performance spectral biomarkers. Vendor- and spectral technology-independent outcomes of the proposal include: optimized, patient-specific protocols; post-processing pipelines that are robust against quantitative bias and variability; and the next generation spectral CT system designs for enhanced iodine quantitation. Achievements from the proposed project will improve sensitivity and quantitation accuracy of iodinated contrast media in spectral CT which enables quantitative diagnostics and treatment assessment using robust iodine biomarkers across a broad range of clinical applications.

NIH Research Projects · FY 2024 · 2021-09

Abstract. Decisions concerning anesthetic dosing typically rely on population-based measures of drug potency. However, similar anesthetic doses have markedly different effects on distinct individuals. While some patients recover from anesthesia uneventfully, in others, recovery is complicated by postoperative delirium and cognitive dysfunction. Such complications are disproportionally prevalent in the elderly. It is presently unclear why some elderly patients exhibit these debilitating and costly complications. To answer this question, individual-based rather than population-based measures of drug effects must be developed. We create such measures for anesthetics in mice. Preliminary data indicate that standard population-based measures of anesthetic potency, such as half-maximal effective concentration (EC50), are insufficient to explain anesthetic responses in each individual. This is because at a fixed anesthetic concentration, the level of consciousness in each individual fluctuates. While fluctuations in the state of arousal occur spontaneously, there is an inertial tendency in each animal to resist state transitions. Hence, the response in each individual depends not just upon the anesthetic concentration, but also upon the individual’s previous state of arousal. Standard drug potency measures fail to account for this history-dependence. Thus, to adequately quantify individual-based responses to anesthetics, we develop two independent measures: personalized drug sensitivity and resistance to state transitions. We hypothesize that resistance to state transitions contributes to delayed restoration of cognitive function after anesthesia. We investigate age-dependence of resistance to state transitions in a first of a kind longitudinal study (Aim 1). To investigate a neurobiological basis of resistance to state transitions, we selectively decrease resistance to state transitions using chemogenetic activation of orexinergic neurons that are critically involved in stabilization of sleep and wakefulness (Aim 2). To determine whether resistance to state transitions is causally linked to restoration of cognition, we use a behavioral test of sustained attention (SA) performed immediately upon recovery after anesthesia. Our published results indicate that SA is dramatically disrupted after recovery from anesthesia in human volunteers. We determine if increased resistance to state transitions is associated with greater impairment on SA performance after emergence in mice. We attempt to restore normal SA performance by modulating resistance to state transitions using chemogenetic activation of orexinergic neurons (Aim 3). In summary, we develop a qualitatively novel measure of personalized, rather than population-based anesthetic responses: resistance to state transitions. We determine the neurobiological underpinnings of resistance to state transitions, and investigate its relationship to subsequent cognitive recovery. Thus, we offer a critical first step towards developing truly personalized anesthesia and delineate factors underlying delayed restoration of consciousness.

NIH Research Projects · FY 2025 · 2021-09

ABSTRACT Acute Respiratory Distress Syndrome (ARDS) is a heterogeneous syndrome of lung inflammation, alveolar capillary barrier dysfunction, and micro-thrombosis that is common in sepsis. Mortality is above 30% and no pharmacotherapies exist for ARDS. We previously identified a reproducible association between ABO blood type A and an approximately 14% higher absolute risk of ARDS compared to blood type O in sepsis. ABO blood type is genetically determined by the ABO gene, which encodes a family of glycosyltransferases responsible for catalyzing specific carbohydrate modifications on glycans and glycoproteins on erythrocytes, endothelial cells, and platelets. The genetic variation that determines blood type is associated with risk to multiple coagulopathic diseases, including myocardial infarction and venous thromboembolism, as well as plasma levels of multiple endothelial-derived glycoproteins. Our published preliminary data, demonstrate an association between the genetically determined A1 subtype of blood type A, distinguished by 30-50 fold higher “A” transferase activity relative to the A2 subtype, and highest ARDS risk. Additionally, we identified an association of blood type with plasma levels of two proteins measured early in sepsis and important in endothelial activation and coagulation, von Willebrand factor (vWF) and soluble thrombomodulin (sTM), as well as with risk of disseminated intravascular coagulation (DIC). These same proteins have been implicated in ARDS. On vWF, A antigens reduce degradation by ADAMTS13, resulting in a pro-coagulant effect, suggesting septic blood type A patients may require higher ADAMTS13 levels. Therefore, we hypothesize that there is an endotype of ARDS influenced by ABO blood type that can be identified and targeted clinically. The goals of the research proposed in this application is to obtain critical information necessary to identify a population most likely to benefit from therapies targeting ABO-influenced vascular biology and to understand the effect of ABO glycans on injured lungs. We will accomplish this through the following Aims; Aim 1 will determine the association of genetically determined ABO blood type A1 and mortality in sepsis and sepsis-associated ARDS, in two large cohorts of critically ill sepsis patients. Aim 2 will derive and validate a predictive tool that includes ABO genotype, plasma levels of vWF and sTM, and components of the DIC score to identify a population at high risk for an ABO-defined coagulopathic endotype of ARDS in sepsis. Aim 3 will determine the longitudinal physiologic effects of ABO blood type on lung injury recovery in an ex vivo lung perfusion (EVLP) model and test if these effects are modified by the administration of recombinant ADAMTS13. The multidisciplinary team of investigators includes a translational scientist and genetics expert (Meyer), two molecular epidemiologist with expertise in ARDS and predictive modeling (Christie, Ware), an EVLP expert (Cantu), a bio-statistician with a history of collaboration in critical care research (Feng), and the PI (Reilly), a translational epidemiologist who first identified an association between ABO blood type and ARDS risk.

NIH Research Projects · FY 2025 · 2021-09

ABSTRACT The “Center for Advanced Metabolic Imaging in Precision Medicine (CAMIPM)” is a National Center for Biomedical Imaging and Bioengineering (NCBIB) that will develop and translate cutting edge noninvasive metabolic imaging biomarkers for use in biomedical research. Technology development is focused in four major application areas: Oncology, Cardiovascular, Neuropsychiatric, and Musculoskeletal. Driven by collaborators across the country and in partnership with Penn’s clinical research institutes in these areas, a range of novel technologies will be developed, optimized, and implemented with the goal of providing mechanistic understanding of disease states based on fundamental biological properties that can also serve as treatment targets and biomarkers for monitoring therapeutic interventions. The proposed technological development will span from bench to bedside and will include a significant clinical research component. Four synergistic technological research and development (TR&D) projects will focus on 1) Chemical Exchange Weighted Molecular MRI for metabolic mapping in brain, heart, skeletal muscle, and tumors, 2) MRI Mapping of Oxygen Consumption in brain, muscle, and placenta 3) Down Field Spectroscopy of brain, heart, skeletal muscle, and tumors, and 4) Diffuse Optical imaging in tumors, brain, and muscle. Each of these TR&D projects will innovate and validate novel strategies for measuring tissue metabolism and translate these technologies to clinical populations through its collaborative projects, and dissemination through sharing of instrument design, MRI pulse sequences, data processing pipelines, and sample data as well as serving a multitude of funded service projects. The CAMIPM also proposes an extensive training and dissemination program in biomedical imaging through seminars, workshops, peer reviewed publications, targeted courses, hands-on training and a dedicated website and will train collaborators, service project investigators, students, postdoctoral fellows, and visiting scholars in the resource developed technologies. Core investigators have an outstanding track record of imaging technology research, technology dissemination, and of training the next generation of scientists in biomedical imaging technologies. An administrative component consisting of both internal and external advisory committees will oversee the fiscal matters, day-to-day activities as well as coordinate the TR&Ds, collaborations and service components. This project leverages an outstanding biomedical research environment with extensive resources for biomedical imaging research, strong institutional support, a compact campus housing nationally leading research and health care enterprises in very close proximity to basic science and engineering departments, closely integrated clinical-research institutes, and outstanding faculty and trainees. With its stellar faculty and unique biomedical focus, the CAMIPM is committed to interdisciplinary pursuit of basic and clinical research through technology development driven by its collaborators and through service to users geographically distributed across the country and thus has all the attributes required for a national NCBIB.

NIH Research Projects · FY 2026 · 2021-09

Bronchopulmonary dysplasia (BPD) is the most common complication of prematurity and is the leading respiratory cause of childhood morbidity. BPD results in a significant burden to families and increased health care utilization. In the United States alone BPD accounts for over $2.4 billion in healthcare costs annually. Ventilator induced lung injury (VILI) an accepted and important contributor to BPD. Exposure to oxygen and positive pressure ventilation leads to developmental arrest and parenchymal injury in the immature preterm lung. Because even brief exposure to positive pressure ventilation is injurious, avoiding invasive intubated mechanical ventilation is the most widely acknowledged strategy to prevent VILI and the long-term sequela of BPD. Therefore, time on ventilators and rates of successful extubation are important endpoints of therapy. Lung protective strategies prioritize non-invasive respiratory support for preterm infants with respiratory failure, but failure rates of continuous positive airway pressure (CPAP) therapy are high. In meta-analysis of available trials, both synchronized and non-synchronized non-invasive positive pressure ventilation (NIPPV) are superior to CPAP for preventing extubation failure in preterm infants. A stronger effect size was observed for synchronized NIPPV vs. CPAP than for non-synchronized NIPPV vs. CPAP. However, until recently no FDA-approved reliable methods to provide synchronized NIPPV for preterm infants were available in the US Neurally Adjusted Ventilatory Assist (NAVA), an FDA approved technology, is a novel method to synchronize ventilatory support with infant respiratory drive. This effective non-invasive synchronization matches electrical diaphragmatic activity to deliver synchronized and accurate tidal volumes in proportion to the neural signal. To date, the clinical impact of non-invasive NAVA (NIV-NAVA) on clinical outcomes in preterm infants has not been established. In these clustered UG3/UH3 and U24 applications, we propose a pragmatic, unblinded, phase III clinical trial in 478 extremely preterm infants of 24 0/7- 27 6/7 weeks gestational age to determine if NIV-NAVA, compared with non-synchronized NIPPV, prevents extubation failure within 5 days of extubation from mechanical ventilation.

NIH Research Projects · FY 2025 · 2021-09

Project Summary: Metastatic cancer is a major clinical challenge that accounts for numerous deaths annually in the United States, particularly in women with triple-negative breast cancer (TNBC). Many tumors develop within a microenvironment (TME) characterized by altered/stiffened extracellular matrix (ECM) and compromised immunity. These alterations play a causal role in malignancy and metastasis. Recently tumor-derived exosomes have drawn tremendous interest as they are implicated in modulating the TME, suppressing anti-tumor immunity, and preparing the metastatic site for progression. A hallmark of cancer cells is their ability to evade the immune system. Exosomes play a pivotal role in the suppression of anti-tumor immunity. In this project, focusing on TNBC, we explore how ECM stiffness and cytoskeletal tension (collectively referred to as tissue tension) regulate exosome production and cargo composition, and how these exosomes contribute to the suppression of anti- tumor immunity and promote metastasis. We pursue a unique set of hypotheses linking tissue tension to exosome production and defining the role of tumor-derived exosomes in immune surveillance and metastatic progression. To test our hypotheses, we have assembled a strong team from UPENN and UCSF, integrating expertise in bioengineering, cancer mechanobiology, and cancer immunology. In Aim 1, we address whether and how the tissue tension affects exosome production and alters exosome cargo in vitro in TNBC cells. We will also delineate a molecular pathway linking ECM stiffness to intracellular signaling and exosome trafficking, using experimental and subcellular biophysical modeling methods. In Aim 2, we address how tissue tension promotes metastatic progression via exosomes in vivo. In this aim we test the hypothesis that the tension of the primary tumor tissue enhances exosome production and alters exosome cargo to promote the dissemination of primary tumor cells and foster their survival and outgrowth at the metastatic site. We will use unique genetically engineered mouse models (GEMMs) and syngeneic TNBC models, and TNBC patient PDXs, combined with multiscale pharmacokinetic modeling. In Aim 3, we address how tissue tension contributes to the suppression of anti-tumor immunity. In this aim, we will investigate the role of exosomes derived from tumors with high tension in stiff ECM TMEs in suppressing anti-tumor immunity through (1) reprogramming macrophages against T cells; and (2) the engagement of PD-1/PD-L1 checkpoint axis in T cells. We will use a combination of in vitro cell culture experiments, in vivo genetically engineered mouse models and syngeneic transplant manipulations and tissue-scale agent-based modeling. The expected results will shed light on the roles of exosomes in immune regulation and metastatic tumor progression; these are important and timely questions in cancer research. The results will lay the foundation for future therapeutic intervention of metastatic disease through the identification of actionable biomarkers, development of new immune checkpoint inhibitor (ICB)-based therapies, and ultimately reduce patient mortality.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY/ABSTRACT Candidate: Paula Chatterjee, MD MPH is an early stage health services researcher and general internist interested in improving access to care for rural older adults and narrowing rural-urban health disparities. She aims to develop content expertise in aging; expand her mixed method research skills; and transition into an independent investigator dedicated to improving the health of older adults and narrowing health disparities. Research Context: Older adults make up a growing portion of rural communities in the United States (US), but have more chronic conditions and limited access to care compared to their urban counterparts. Rural hospitals, which increasingly provide essential inpatient and outpatient care for older adults, struggle financially and are at accelerating risk of closure. Global budgets for rural hospitals have been proposed as a strategy to financially bolster rural hospitals to stave off risks of closure, while transforming rural care delivery to optimally manage chronic conditions and narrow rural-urban health disparities. Understanding how global budgets might achieve these outcomes is critically important to understanding how to strengthen rural health care systems. Specific Aims: (1) Describe trends in access to care, chronic condition management, and corresponding rural- urban disparities among older adults in the US; (2) estimate changes in access to care, chronic condition management, and rural-urban disparities among older adults after the introduction of global budgets for rural hospitals; and (3) qualitatively chronic identify hospital-based facilitators and barriers to preserving access, improving condition management, and narrowing disparities for rural older adults. Research Plan: Using the Health and Retirement Study and Medicare claims, Dr. Chatterjee will first describe trends in access to care and chronic condition management, and then use a synthetic control approach to evaluate the association between the introduction of global budgets in rural Pennsylvania hospitals and these outcomes. Dr. Chatterjee will then collect primary data from rural Pennsylvania hospital executives to better understand their efforts to preserve access, improve chronic condition management, and narrow disparities. Career Development Plan: Dr. Chatterjee will (1) develop content expertise in aging and health care delivery for older adults, particularly those in rural communities; (2) broaden and solidify research skills in causal inference, qualitative methods and implementation science; and (3) execute a research agenda focused on improving the health of older adults with chronic conditions. She will achieve these goals under a team of leading experts in aging, rural health, health disparities, econometrics, and qualitative methods. Environment: The University of Pennsylvania is an ideal environment to achieve these training aims under the guidance of an experienced and multidisciplinary team of Mentors and Advisors with a strong track record in developing independent health services researchers in aging and health services research.

NIH Research Projects · FY 2025 · 2021-09

This proposal is to develop the University of Pennsylvania’s Innovation in Suicide Prevention Implementation Research (INSPIRE) Center. Suicide is a leading cause of death in the US. Guided by a conceptual model based on the Integrated Behavior Model, which posits that organizational culture, policies, and resources (or lack thereof) impact the provider’s attributes and behaviors, INSPIRE brings together psychology, implementation science, health economics, machine learning, health information technology, psychiatry and participatory research experts to apply innovative interdisciplinary approaches to suicide prevention. INSPIRE’s overarching goals are to develop and adapt practice-based and other suicide prevention interventions and to design and test implementation strategies to optimize how evidence-based practices can be brought to scale efficiently and with high fidelity, for optimal effectiveness. INSPIRE will prioritize strategies that can be rapidly deployed in a range of practice settings, including those with limited resources, thereby increasing their reach and public health impact. Penn INSPIRE will use state-of-the-science methods from participatory research to actively engage stakeholders from many sectors – including patients, providers, and payers – at every level of its work to accomplish its Specific Aims. INSPIRE will apply innovative, interdisciplinary behavior change and implementation science methods to develop, adapt, and evaluate cost effective interventions. A Signature Project will use a stepped wedge study design to test an innovative organizational strategy that leverages telehealth to deliver high quality Safety Planning Intervention and follow-up services in Emergency Departments. Three Exploratory Projects will test novel strategies for suicide prevention across individual, clinician, and organizational levels that will lay the foundation for more definitive studies. INSPIRE will also support 10 pilot projects and an innovative Methods Core that will develop and test new methods to advance research at the intersection of suicide prevention and implementation science. The Suicide Prevention Scholars Program will expand the cadre of suicide prevention researchers by engaging both emerging investigators and established scientists who do not currently work on suicide prevention through content, design. and methodological mentoring and capacity-building. By catalyzing interdisciplinary, cross-sector collaborations and advancing suicide prevention research, care, and policy both locally and nationally, we will develop cost-effective, practical, and efficient ways to implement evidence-based suicide prevention interventions. INSPIRE is poised to be transformational for suicide prevention.

NIH Research Projects · FY 2025 · 2021-09

Project Summary Large observational data such as electronic health records (EHRs) and medical claims have become an enabling source for facilitating clinical and translational research including Alzheimer's Disease and Alzheimer's Disease Related Dementia (AD/ADRD). One major challenge for conducting observational AD/ADRD studies is about phenotyping – there is a lack of a centralized repository for hosting and standardizing phenotype definitions in AD/ADRD research and few methods have been developed to address bias associated with phenotyping errors in observation data. Therefore, the overarching goal of this proposal is to fully develop a joint effort between medical informaticians, statisticians, clinicians, and epidemiologists with a focus on building a rigorous set of methods and tools for managing phenotype definitions and for correcting bias in observational data analysis, through modern knowledge engineering and data-driven statistical modeling. To achieve that goal, we propose three specific aims in this study: (1) Aim 1 - Collect, normalize, and share definitions of common phenotypes used in AD/ADRD observational research; (2) Aim 2 - Develop novel algorithms to correct bias associated with phenotyping errors when users apply existing phenotype definitions to local data; and (3) Aim 3 - Validate, refine, and disseminate proposed methods and tools by demonstration studies and community engagement. We believe informatics methods and tools proposed here will improve current practice on phenotypic data management and analysis, thus enhancing the reproducibility and quality of observational studies on AD/ADRD.

NIH Research Projects · FY 2025 · 2021-09

Synthetic mammalian artificial chromosomes (MACs) represent a new frontier in genome technology, with the potential to transform chromosome and synthetic biology and stimulate the development of numerous radical advances in medicine. Human Genome Project-Write aims to generate an entire set of synthetic human chromosomes. Short of this ambitious goal, MACs have enormous potential for breakthroughs in biotechnology and medicine, such as creating humanized animal models for drug development or for harvesting patient- personalized organs for transplantation. Furthermore, building MACs from minimal components will advance our fundamental understanding of what comprises a mammalian chromosome. As vehicles for genetic inheritance, fully functional chromosomes are faithfully transmitted through mitosis and the specialized meiotic divisions underlying eukaryotic sexual reproduction and Mendelian inheritance. Our goal is to construct the first MACs that achieve faithful inheritance through the germline, using mouse as a model system. One obstacle is the centromere, the locus on each chromosome that directs transmission through both mitosis and meiosis. Because mammalian centromeres are not encoded in the DNA sequence, it is unclear how to build synthetic chromosomes containing this crucial element. There are additional challenges to create MACs that pair and recombine as homologous chromosomes in meiosis. To solve these problems, we will hijack the existing cellular machinery for assembling centromere chromatin and incorporate additional genetic elements to ensure meiotic pairing and recombination. This effort requires innovation at multiple levels: designing MAC vectors encoding key functional elements, assembling large synthetic DNA constructs, and ultimately creating animals to test MACs in vivo. The proposed work builds on recent advances from the co-investigators’ teams in all of these areas, and we have key tools and expertise in place to build the necessary DNA templates, introduce them into embryos, analyze the outcomes, and develop alternative strategies as necessary. The most meaningful preliminary data would be to show a synthetic artificial chromosome that is successfully transmitted through mitosis and meiosis in vivo, but achieving this step is a major goal of our proposal and will require substantial investment of time and effort. Thus, we are requesting support for this project without the preliminary data that would demonstrate high likelihood of success, justifying consideration of our proposal as part of the T-R01 mechanism. We use mouse as a relatively rapid and tractable mammalian model system with outstanding opportunities for testing and debugging MACs, and our advances should readily transfer to other species for applications in biotechnology and medicine. Success in this project will represent a quantum leap in the development of synthetic artificial chromosome that are fully functional in vivo, providing unprecedented genome engineering capabilities in animal models and enabling diverse synthetic biology applications.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY Heart failure (HF) is a critical public health issue that affects over 5 million US adults and imposes an enormous clinical, social, and economic burden. Over half of individuals with HF have HF with preserved ejection fraction (HFpEF). Furthermore, HFpEF is highly heterogeneous, and different pathologic mechanisms contribute to symptoms and poor outcomes in several different subgroups of the disease. Although several largescale randomized trials have been performed, no pharmacological therapies have been identified that improve symptoms or clinical outcomes in patients with HFpEF. Our group and others have identified that novel approaches to deeply phenotyping patients with HFpEF can identify subgroups of patients with HFpEF that are likely to benefit from targeted therapy. The overarching goal of the current proposal is to establish a large cohort of deeply phenotyped patients with HF with a focus on patients with HFpEF. We propose establishing a cohort of 1000 patients across all 4 Penn clinical centers: 700 patients with HFpEF, 200 patients with HFrEF (including 100 patients with mid-range LV EF, 40-50%) and 100 non-HF patients with hypertension (a suitable control population, given that most patients with HFpEF have a history of hypertension). We will incorporate comprehensive clinical data, socioeconomic data (particularly as they relate to social determinants of health), patient-centered data (such as quality of life and functional status), structural and mechanistic cardiac and extracardiac phenotypes (including in-lab characterization and innovative ambulatory approaches to data collection) and multi-omics approaches. The phenotypic data will be complemented by contemporary bioinformatic approaches to enhance our understanding of human HFpEF. Our phenotyping protocol will provide the opportunity for cross-sectional comparisons against other groups above, application of within-group clustering approaches, as well as establishing a comprehensively characterized large prospective cohort of patients with strictly adjudicated HFpEF for prospective follow-up of hard outcomes. In these patients, we will assess detailed cardiac and extracardiac phenotypes, electronic health record data, patient-reported outcomes, aerobic adaptations to exercise, and plasma and urinary proteomics and metabolomics and micro RNAs. We will also assess key ambulatory phenotypes including innovative approaches to home blood pressure monitoring, physical activity, sleep duration and quality, and important social determinants of health. Heart failure outcomes will be prospectively adjudicated, including heart-failure related hospitalization, death, myocardial infarction and stroke. Our analytic approach will include hypothesis-based research as well as unbiased discovery approaches that will leverage contemporary bioinformatics tools but will be subject to expert interpretation by members of the Steering Committee, investigator teams at the other Clinical Centers, and scientific community at large.

NIH Research Projects · FY 2024 · 2021-09

Project Summary: Cardiac allograft rejection (CAR) is a serious concern in transplant medicine, representing the leading threat to short- and long-term allograft survival. As a result, CAR surveillance and prevention is a primary focus of post-transplant care, with recipients undergoing frequent, scheduled, surveillance endomyocar- dial biopsy (EMB) for histologic CAR grading along with frequent, scheduled de-escalation of immunosuppres- sion (IS). The uniformity of this standardized approach to CAR mitigation is the result of an inability to employ reliable, proactive, and tailored strategies based on individual CAR risk. Consequently, patients at low CAR risk are exposed to unnecessary EMB procedures and excess IS therapy, while patients at high risk experience inadequate CAR surveillance and early/inappropriate weaning of IS. This exposes patients to potential harm, and highlights the clear, unmet need for precision CAR risk-assessment tools. The overarching premise for this proposal is that contained within the clinical data and EMB tissues already collected as part of usual care at transplant centers exists the means to provide actionable CAR risk assessments. Extensive immunologic, diag- nostic, and pharmacologic data are captured in electronic health records (EHR) at transplant centers, while large collections of EMB histology samples are stored (and often digitized) in pathology archives. This proposal seeks to utilize advanced machine-learning algorithms and in-situ diagnostic methods to deeply mine these archival resources for the purpose of validating novel CAR risk-prediction models. In Aim 1, we will leverage our experi- ence with automated histologic analysis pipelines to develop a ‘morphologic model’ for predicting future CAR using archived H&E slides. Hematoxylin-and-Eosin (H&E) histology slides are generated from all EMB events as part of standard-of-care. In published and patented prior efforts, we have extracted quantitative morphologic features from digitized H&E slides which, when modeled, demonstrate excellent performance for diagnosing myocardial injury and CAR grades. In Aim 2, we will move beyond standard H&E, leveraging our experience with quantitative, in-situ immune-profiling of transplant EMBs to develop a ‘morpho-molecular’ model for predicting future CAR. This aim will expand upon exciting pilot work which showed the CAR risk-stratification potential of combining quantitative image-analysis with multiplex immunofluorescence. Finally, in Aim 3, we will develop a ‘histo-informatics’ model for predicting CAR by integrating data from Aims 1 & 2 with comprehensive clinical informatics data extracted from the EHR. Ultimately, as a result of this work, we expect to validate a novel pre- cision prediction model for use in prospective investigations exploring personalized CAR surveillance and pre- vention strategies. Beyond the potential translational impact, this research plan will build on the Applicant’s knowledge of complex cohort design, integrated data modeling, and transplant immunodiagnostics. Along with planned coursework and a diverse mentoring, advisory, and collaborative team, this proposal provides the opti- mal vehicle for Dr. Peyster’s maturation into an investigator with proven expertise in multi-modality diagnostics.

NIH Research Projects · FY 2025 · 2021-09

Since the completion of the Human Genome Project and the HapMap Project, genetic science has identified a wealth of associations between common or rare variants and human complex traits, including diseases. GWAS has arguably been the most successful tool in this so called “post-genomic” era, yielding almost 200,000 robust associations between common SNPs and more than 5,000 human traits. However, because of linkage disequilibrium, GWAS only report genomic “signals” or “loci” tagged by index SNPs and not the underlying true causal variants. Even more crucially, GWAS cannot indicate the effector genes at these loci, which are necessary to translate these findings into development of new therapies for disease. The main challenges to identifying causal variants and effector genes are that 1) the majority of variants identified by GWAS reside in non-coding regions of the genome and are thought to regulate gene expression, often hundreds of kb away in linear distance and 2) gene expression regulation is exquisitely tissue and cell type specific. While consortia such as ENCODE and GTEx have already built high quality, publicly available genome-wide datasets for many epigenetic markers and gene expression in different tissues and cell types, some limitations exist such as the number and heterogeneity of cell and tissue types available, the use of post-mortem samples, and the limited power due to the large sample number needed for QTL studies. As an alternative approach, I propose a variant-to-gene mapping campaign based on genome-wide high-resolution, promoter-focused Capture C, a technique that detects contacts between different regions of the genome in 3D space. Coupled with other genomic techniques, i.e. ATAC-seq, ChIP-seq and RNA-seq, this approach will allow us to identify putative causal variants residing in open chromatin and with enhancer signatures, and their (transcriptionally active) effector genes (including non-coding RNAs). Importantly, this proposal will focus on brain-related traits and disorders, a field where many GWAS signals have been reported, but only a few have been definitely linked to their effector genes, including many neurodegenerative disorders still lacking effective therapies. Using a tractable in vitro model system such as human iPSC-derived neural cell types (neurons, astrocytes and microglia, including co-cultures and brain organoids), I will be able to incorporate a temporal and functional dimension to these studies, which will help us identify mechanisms of disease etiology and progression in neuro-developmental and neurodegenerative disorders.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY Determining how neurons are assembled into functional circuits will provide insight into developmental disorders of the nervous system and may suggest therapeutic approaches to promote nerve regeneration. To navigate to their correct targets, axons must modulate their responses to extracellular cues, and regulated intracellular protein trafficking plays a pivotal role in this process. For example, commissural axons cross the midline despite the presence of repellant ligands in order to establish connections that are essential for coordinated motor behavior. In Drosophila, the endosomal protein Commissureless (Comm) prevents commissural axons from prematurely responding to the repellant Slit, by inhibiting surface expression of the Slit receptor Roundabout1 (Robo1). In mammals, Robo receptors are also negatively regulated in commissural axons prior to midline crossing, but the mechanisms are unknown. Unlike Slit and Robo, comm is not conserved in vertebrates; however, our preliminary data indicate that the vertebrate Nedd-4 interacting proteins (Ndfip1 and Ndfip2) can act analogously to Comm to regulate the trafficking and stability of human Robo receptors in vitro, and that loss of Ndfip1or Ndfip2 function in vivo in mice results in increased expression of Robo receptors and defects in axon guidance. We will test the hypothesis that Ndfip proteins control axon guidance in the developing brain and spinal cord by recruiting Robo receptors to endosomes and triggering their degradation through interactions with Nedd-4 E3 ubiquitin ligases. In aim 1, we will use molecular, cell biological and biochemical approaches to: 1) determine whether Ndfip proteins exhibit differential effects on intracellular trafficking of Robo receptors or other axon guidance receptors, 2) delimit the sequences that are necessary and sufficient to mediate interactions between Ndfip proteins and Robo family receptors, 3) characterize the role of HECT E3 ligase activity on receptor trafficking and 4) identify the specific Nedd4 family ligase(s) that is required for Robo receptor regulation. Aim 2 will explore the embryonic expression patterns and in vivo requirements for Ndfip proteins during commissural axon guidance by examining the trajectory of commissural axons in Ndfip1 and Ndfip2 single and double mutants, using 1) immunofluorescence for pre and post-crossing commissural axon markers, and 2) unilateral lipophilic dye tracing experiments. In addition, we will generate conditional knockouts of Ndfip1, Nedd4-1 and Nedd4-2 using Cre-lines specific for commissural neurons to investigate requirements for Nedd4-1 and Nedd4-2 in spinal commissural axon guidance. Aim 3 will assess the in vivo links between Ndfip proteins and Robo receptors by 1) testing whether neurons cultured from Ndfip mutants exhibit altered repulsive responses to exogenously added Slit proteins and 2) examining genetic interactions between Ndfip and Robo mutants. Finally, a biochemical screen will be conducted to identify novel substrates of Ndfip proteins.

NIH Research Projects · FY 2026 · 2021-09

PROJECT SUMMARY Interactions between bacteria and their viruses (phages) are among the most ubiquitous in nature and have yielded transformative tools for genetic engineering, such as restriction enzymes and CRISPR-Cas. More than three dozen new bacterial immune systems have recently been discovered across many bacterial species. Some of these immune systems, such as CRISPR, target phage for cleavage, while others sense phage infection and induce bacterial death to halt phage spread. In turn, phages express “anti-immune” proteins to disarm these bacterial defenses, including “anti-CRISPR” (Acr) proteins that inhibit Cas effector functions. Phage-derived interactors (either inhibitors or activators) have not yet been found for most of these immune systems, however. The long-term objective of this proposal is to identify phage proteins that interact with or trigger activation of these immune systems. These interactions will be identified using yeast two hybrid screens and validated using affinity purification-mass spectrometry analysis in bacteria. In the two-hybrid screen, the Gal4 transcription factor will be split into an activation domain and DNA-binding domain and fused to each phage “prey” protein and bacterial immune “bait” protein, respectively. Interaction between the prey protein and bait protein should reconstitute the full transcription factor and enable expression of a reporter gene that confers survival on selective media. Rationally selected phage proteins will be screened for interactions with CRISPR- Cas proteins as well as immune proteins that lack known interactors. This versatile platform will accelerate the discovery of phage-bacterial interactions, which have long transformed molecular biology and gene therapy. In parallel, the strategies that phage use to inactivate CRISPR-Cas systems in bacteria will be applied to gene therapy in human cells to reduce cytotoxicity and off-target effects. Phages that constitutively inactivate Cas9 and Cas12a in bacteria often block both targeting and expression, which is likely optimal for long-term Cas inactivation. Mammalian gene editing performed with Cas9 delivered on viral vectors often causes off-target mutations and cytotoxicity associated with long-term Cas9 expression. To mitigate these off-target effects, strategies to inactivate CRISPR-Cas complexes and reduce their expression (after on-target editing has occurred) will be combined and compared. This work will be performed at UCSF, which hosts world-class facilities and a highly intellectual and collaborative research community. It will also provide me with the expertise in protein-protein interaction screens and gene editing that I need to fulfill my postdoctoral training goals and pioneer an independent research program in bacterial-phage interactions.

NIH Research Projects · FY 2024 · 2021-09

PROJECT SUMMARY/ABSTRACT In this application for a 5-year K23 Career Development Award, I propose mentored research and career development leading to a career as an independent clinical and translational investigator in interstitial lung disease (ILD). The goal of this project is to identify the role of body composition in frailty among subjects with idiopathic pulmonary fibrosis (IPF). The prevalence of IPF is rising, currently affecting 1 in 200 older adults. There is no cure for IPF. The only available medications slow disease progression but do not reverse disease. Frailty affects up to 50% of IPF patients, and is characterized by decreased physiologic reserve and increased susceptibility to severe manifestations of acute insults. The most common causes of death in IPF are acute insults. Frailty is thus a potentially modifiable risk factor for morbidity and mortality in IPF. This proposal builds on my preliminary work showing that (1) greater visceral adipose tissue (VAT) is associated with increased frailty, (2) subjects with both sarcopenia and visceral obesity are at greater risk of frailty than those with sarcopenia alone, (3) there may be distinct endotypes of exercise limitation defined by high inflammation alone or low inflammation with high VAT, and (4) down-regulation of the growth hormone (GH) axis may link VAT and frailty. Under the mentorship of Dr. R Graham Barr, I propose to evaluate the roles of body composition by bioelectrical impedance assay (co-mentor Gallagher), inflammation, and neuroendocrine dysregulation associated with frailty risk using a machine-learning approach (co-mentor Valeri). I will also evaluate the role of growth hormone axis dysregulation in sarcopenia with visceral obesity in a rigorous overnight protocol (co-mentor Freda). I propose to perform this in two NHLBI-funded prospective cohorts: Dr. Garcia’s Families-At-Risk for ILD (R01HL103676) and Dr. Singer’s Advanced Lung Disease Lung Transplantation Study (R01HL134851). With guidance from my mentors, I have crafted a 5-year career development plan that includes training in body composition analysis (Dr. Gallagher), measurement of complex endocrine systems (Dr. Freda), clinical trials (Dr. Freda), biostatistics (Dr. Valeri), aging in interstitial lung disease (Dr. Garcia), and epidemiology (Dr. Barr). In the last two years of this award, I will apply for R01 funding and transition to independence. The proposed activities will prepare me to conduct patient-oriented research to evaluate the role of body composition in outcomes in ILD. I will also acquire the skills and training required to design and conduct clinical trials targeting novel pathways to prevent and treat frailty in ILD.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY For the nearly 95,000 people currently waiting for a kidney transplant, their geographic residence has a major impact on whether they will get a transplant. Organ allocation is based on geographic boundaries of donor service areas (DSA) that are artificial. There are 58 DSA in the US, and they vary tremendously in size and population, which explains some of the variation in access to transplantation. The geographic boundaries of DSAs were never designed to optimize organ allocation, and do not account for population, prevalence of kidney disease, or organ donation rates. These geographic boundaries might also contribute to another important problem – unnecessary discard of donated kidneys. Nearly 20% of all kidneys donated in the US are discarded. Improving access to transplant and reducing kidney discard are national priorities under the “Advancing American Kidney Health Initiative.” A new kidney allocation policy that does not use any fixed geographic boundaries is scheduled for implementation in December 2020. However, the new organ allocation policy may have unintended effects on organ outcomes and worsen disparities in access to transplant. This grant will examine three eras of kidney allocation that reveal how the use of geographic boundaries has affected transplant benefits and equity for patients with end-stage kidney disease: 1) Historical Allocation Era: Transplants performed before 12/4/2014, when kidneys procured within a DSA were allocated primarily to recipients within the same DSA; 2) Kidney Allocation System Era (split into two sub eras): Kidneys considered “lower quality” were shared over a wider region until 9/5/2019, and this policy was subsequently reversed due to high kidney discard rates; 3) Concentric Circle Era: This system is scheduled for implementation on 12/15/2020 and eliminates DSA boundaries, and uses a 250-nautical mile radius around donor hospital to allocate kidneys. The overall objective of this scientific proposal is to determine the effects of wider geographic sharing of deceased donor kidneys on the specific outcomes of kidney discard, disparities in access to transplant, and recipient outcomes. My central hypothesis is that systems with wider sharing of deceased donor kidneys might reduce geographic inequities for patients living in areas with high wait-times, but it will worsen organ discard and fail to improve kidney allograft survival. These novel insights into the relationship between geography and kidney allocation could ultimately drive major public health gains for patients with kidney disease by showing how kidneys can be allocated to improve fairness and increase the number of transplants. The applicant has an appointment on the junior faculty at the University of Pennsylvania. With the support of a highly experienced mentorship team and the ample resources available at the University of Pennsylvania, his goal is to foster a career of enduring research as an R01 funded independent physician scientist, and to become a leader in the field of nephrology and kidney transplantation.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY/ABSTRACT Millions of patients are placed into a reversible state of unconsciousness by anesthesiologists for life saving surgeries every year. The basic goals of anesthetic care are to reliably extinguish consciousness for the duration of surgery and afterwards to swiftly return the patient to their baseline cognitive state. Neither of these goals can be reliably achieved today, however. Some patients regain consciousness during surgery. Episodes of consciousness are not reliably detected by current intraoperative EEG-based monitoring and can result in post-traumatic stress and anxiety disorders. In contrast, other patients take a long time to resume normal cognition. This can manifest as postoperative delirium and cognitive derangements. Postoperative delirium affects millions of patients, costs 34 billion dollars annually, and can be a harbinger of ongoing cognitive decline. Such persistent impairments in cognitive function can last for many months. It is presently unclear why some patients experience peri-anesthetic complications while other patients that receive seemingly identical anesthetics have an uneventful perioperative course. To address this, we propose to study individual-based anesthetic pharmacology rather than the previous population-based approach. We have recently developed experimental and computational methods to quantify individual-based measures of anesthetic responses in mice. Using these methods, we discovered that conventional population-based pharmacological concepts such as drug potency are not sufficient to describe individual responses. We identified two independent measures that do capture the range of individual responses: sensitivity and resistance to state transitions (Rst). Sensitivity describes how often an individual is awake or anesthetized at an anesthetic dose, while Rst describes how frequently transitions happen between awake and anesthetized states. We demonstrated that pharmacology can differentially modulate sensitivity and Rst. We also demonstrated that chemogenetic activation of an arousal pathway – the locus coeruleus – decreases Rst without a change in drug sensitivity. Because Rst is completely obscured in population-based pharmacological studies, we hypothesize that Rst is the hidden variable that may help explain why some patients experience peri-anesthetic complications while others do not. We propose to investigate the mechanisms through which the locus coeruleus decreases Rst. Using pharmacologic and genetic approaches, we will identify the neurotransmitter systems used by the locus coeruleus to modulate Rst. Separately, we will identify the effects of the locus coeruleus on neurophysiologic state change, including correlates of behavioral Rst, using a high-density EEG system developed by our lab. Finally, we will identify the neuronal pathways through which locus coeruleus acts to modulate Rst. The proposed lines of investigation will clarify how activity of the locus coeruleus influences individualized anesthetic responses, and will be an important step towards delivering personalized anesthesia.

NIH Research Projects · FY 2024 · 2021-09

No anti-thrombotic agent (ATA) is safe and effective in the many patients at a combined risk of acute thrombosis and bleeding, e.g., in the early post-surgery period. To address this unmet need, we develop drug delivery systems (DDS) executing two main functions: A) Block access of ATA to off- target sites, e.g., hemostatic plugs formed after surgery, while B) Optimize pharmacokinetics and deliver ATA into subsequent thrombi, where ATA is activated by thrombin. ATA fused with single- chain fragments (scFv) targeted to red blood cells (RBC) bind to these carriers that execute dual blocking/delivering function. Proof-of-concept is emerging in models of pre-existing and nascent clots in animals. Here we devise humanized scFv/ATA targeted to human RBC and will test them in a humanized microfluidic system (HMF), in transgenic (TG) mice expressing humanized target epitopes on blood cells, and in the perfusion of isolated human lungs. We will pursue three aims. Aim 1. RBC loading. We will characterize scFv/ATA loading onto RBC: A) Binding (copies/cell, on/off kinetics); B) Effect on RBC functionality, biocompatibility and biomechanics; and, B) Regulation of distribution of scFv/ATA between RBC in circulation. We also will characterize biomechanical factors modulating RBC/ATA delivery and effect on clot dynamics and structure, in particular, impact of RBC rigidification, caused by either drug loading or by intrinsic pathophysiological changes in patient's blood. Aim 2. Mechanistic insights. We will interrogate previously unrecognized yet critically aspects of the RBC/ATA workings, in particular their interaction with vascular endothelium and transfer of the drug cargo to these and other vascular cells. In this Aim we will use standard mouse in vivo models, microfluidic model and perfusion of isolated human lungs model. Aim 3. Appraisal of benefit/risk ratio. We are developing TM mice expressing human RBC determinants in mouse EBC, in order to study scFv/ATA loaded on "human RBC" in vivo: A) PK/BD, complement activation, phagocyte uptake and vascular adhesion of RBC/ATA in TG mice; B) Define the time window/extent of anti-thrombotic effect of human RBC/ATA in models of arterial vs venous thrombosis in TG mice; B) Affirm the safety of RBC/ATA. We will detect adversities of scFv/ATA including abnormalities of RBC. To defuse potential issues, if necessary, we will use more benign loading regimen. Together, these studies will advance mechanistic insights and clinical translation of a novel way to mitigate thrombosis in currently unprotected patients by providing a new and tractable approach to understanding thrombus development and a rational approach to deliver cell-directed therapeutics

NIH Research Projects · FY 2024 · 2021-09

Project Summary In response to the (PAR-18-896), the overarching goal of this proposal is to fully develop a joint effort between statisticians, medical informaticians, clinicians with a focus on developing a rigorous bias correction framework through modern knowledge engineering and data-driven statistical modeling, for improving the unbiasedness and reproducibility of health system data driven research. In this proposal, we will focus on: (1) Develop a novel prior-knowledge-guided integrated likelihood approach to enable bias correction by incorporating prior phenotyping accuracy. (2) Develop methods and algorithms to account for EHR phenotyping errors in both outcomes and predictors. And (3) Validation, Application and Software development. We will use the proposed bias correction methods to several EHR datasets to replicate existing findings and investigate new hypothesis in multiple datasets at University of Texas and University of Pennsylvania. We will also develop software for the proposed methods to facilitate ongoing EHR-based clinical studies.