Grant List
Represents Grant table in the DB
GET /v1/grants?sort=other_investigators
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=other_investigators", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=other_investigators", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=other_investigators", "prev": null }, "data": [ { "type": "Grant", "id": "15155", "attributes": { "award_id": "2441449", "title": "CRII: III: Pursuing Interpretability in Utilitarian Online Learning Models", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Info Integration & Informatics" ], "program_reference_codes": [], "program_officials": [ { "id": 27554, "first_name": "Raj", "last_name": "Acharya", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-08-15", "end_date": null, "award_amount": 175000, "principal_investigator": { "id": 27713, "first_name": "Yi", "last_name": "He", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 414, "ror": "", "name": "College of William and Mary", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "In today's world, the real-time generation of enormous amounts of data has become commonplace, spanning domains such as e-commerce, social media, environmental science, urban disaster and pandemic monitoring, and many others. Such streaming data necessitate data mining (DM) models that can analyze them in time as they emerge, derive actionable insights, and make adjustments on the fly. For instance, predicting crowd movement due to public events (such as concerts, games, parades, and protests) based on data streaming from social media and city sensors can aid in reducing the traffic by steering clear of overcrowded areas. However, as DM models become more prevalent in practice, interpretability has emerged as a vital issue. User comprehension and trust in DM model outputs are critical for their acceptance in daily routines and workflows. Nonetheless, existing research on data streams has focused mainly on model accuracy, producing models that are too complex for human interpretation. This gap between DM researchers and practitioners calls for new research that optimizes model accuracy and interpretability simultaneously. This project aims to bridge the gap by developing novel online algorithms that are transparent to human users and can provide a complete explanation of the logic behind each prediction, earning the trust of human operators and increasing legal defensibility when used to support decision-making in crucial domains such as healthcare, economy, security, and social goods.<br/><br/>The overarching goal of this project is to advance interpretability research of online DM models through three research objectives: (1) understanding the dynamism of varying feature spaces and its impact on model structure; (2) quantifying model prediction uncertainty in the absence of adequate supervision labels; and (3) indexing and elucidating model inference paths. To achieve these objectives, the project will focus on four research thrusts. The first thrust will develop novel algorithms that capture and model the variation patterns of feature spaces through an expository feature correlation graph, allowing for joint learning of graphs and predictive models. The second thrust will focus on developing unsupervised methods to quantify the uncertainty of model predictions and identify geometric manifolds underlying data streams with memory-efficient structures. The third thrust will devise new systems to index, track, and illustrate the complete generation process of online predictions. The fourth thrust will establish evaluation metrics and protocols to standardize interpretability measurement in streaming data contexts. The project aims to contribute to interpretable data mining and machine learning research, which will help bridge the gap between data scientists and domain-specific forecasting experts. The educational component of the project will involve mentoring and educating researchers interested in pursuing DM careers in academia or industry, with a particular focus on underrepresented, financially disadvantaged, or disabled undergraduate students in computer science research. The project will also pioneer new classes at the forefront of data mining research and organize workshops at city libraries to engage with the broader public.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15200", "attributes": { "award_id": "1C06OD037781-01", "title": "A Biosafety Level 3 Laboratory for Viral Pathogens", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [ { "id": 28173, "first_name": "YONG", "last_name": "Chen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": "2027-06-16", "award_amount": 7857615, "principal_investigator": { "id": 26614, "first_name": "Hardy", "last_name": "Kornfeld", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 790, "ror": "", "name": "UNIV OF MASSACHUSETTS MED SCH WORCESTER", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "Program Summary/Abstract The University of Massachusetts Chan Medical School (UMass Chan) seeks NIH C06 funding to renovate existing space in the medical school (S) building to construct an in vitro Biosafety Level 3 (BSL-3) laboratory for viral pathogens. As an internationally recognized leader in infectious disease research, UMass Chan has made pivotal contributions to this field, with a strong focus on hazardous pathogens, including both viral and bacterial pathogens. During the COVID-19 pandemic, UMass Chan quickly became one of the leading institutes for research on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Our researchers obtained numerous awards from the NIH, other governmental agencies, and private foundations for these studies. Since then, our researchers have also obtained funding for collaborative research programs to study other BSL-3-level viruses of pandemic potential, such as viruses that cause viral hemorrhagic fever (VHF) and alphaviruses. C06 funding is critical to continue these important studies. Our BSL-3 Core Laboratories have been strained by the increased usage due to the pandemic and the addition of other BSL-3 viral pathogens, such as VHF. To accommodate this increase, we have used the satellite BSL-3 lab in the Biotech Two building, which will be lost when UMass Chan repurposes this building in 2026. The remaining S7 BSL-3 lab is already operating at capacity for Mycobacterium tuberculosis and Yersinia pestis studies and cannot adequately accommodate the researchers studying Risk Group 3 viruses. To proactively address this issue, we seek NIH C06 funding to convert existing space on the 7th floor of the S-building into a second in vitro BSL-3 lab dedicated to research on viral pathogens. The proposed new facility addresses increasing demands on our BSL-3 resources by UMass Chan faculty and other regional investigators. There is strong institutional support for this project and a commitment to fully equip the new lab, including the purchase of advanced imaging equipment currently unavailable in BSL-3. The proposed facility will enhance the safety and resilience of the BSL-3 research core, and maintain the productivity of funded and future research on Risk Group 3 viruses. Our medical school is uniquely positioned to bridge clinical and basic research studies. As a leading site for clinical trials, our researchers have access to patient samples to enhance in vitro and in vivo studies. Our findings can be translated to develop novel prevention and therapeutic strategies leveraging our world-renowned RNA Therapeutics Institute and Institute for Drug Resistance, as well as our partnership with MassBiologics for vaccine and biologic therapy development, making UMass Chan a powerhouse for bench-to-bedside translational research. Robust BSL-3 labs are needed to maintain this excellence and address current and emerging pathogens with pandemic potential.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15137", "attributes": { "award_id": "2428786", "title": "SupplyChainDCL: Enhancing Resilience, Optimizing Efficiency, and Mitigating Disruption Risks in Supply Chain Networks", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "OE Operations Engineering" ], "program_reference_codes": [], "program_officials": [ { "id": 2155, "first_name": "Georgia-Ann", "last_name": "Klutke", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": null, "award_amount": 414909, "principal_investigator": { "id": 31700, "first_name": "Agostino", "last_name": "Capponi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This award will enhance national welfare by providing a systematic framework to analyze the efficiency and resilience of demand and supply networks. These systems are challenging to analyze due to the complex interdependencies among firms in the network, which adjust their decision-making processes collectively and strategically in response to both idiosyncratic and systemic shocks. The project will develop novel tools and measures for assessing the impact of risk mitigation plans against supply and demand shocks in the network. The framework will elucidate the mechanisms by which supply shortages of specific goods and services during periods of distress can lead to price spikes and increase the fragility of the supply chain network. For instance, the project will help understand how a global semiconductor shortage can cause significant price surges in the U.S. market for second-hand cars, or how an unexpected surge in demand for hand sanitizers during the pandemic led to widespread supply shortages, impacting the industry and its related sectors. This award will also provide research opportunities for graduate students, equipping them with the tools, background, and expertise to advance research in this area.<br/><br/>The project will develop a dynamic decision-making framework to quantify the trade-offs between efficiency and resilience within supply chain networks and provide an empirical analysis of supply chain fragility. This analysis aims to assess how diversification strategies can mitigate risks associated with supply chain vulnerabilities. The research will leverage, extend, and specialize tools from dynamic games, risk management, optimization, and network theory to incorporate the incentives of firms facing information and technological constraints in establishing cost-effective demand-supply relationships and managing risks against supply and demand shocks. The framework will explicitly model both preventive actions taken by firms to hedge against potential future shocks and corrective actions implemented in response to significant disruptions. The project will lead to the development of game-theoretical algorithms for determining optimal firms' levels of investment in production capacity and for final good producers to enter into competitive risk-sharing agreements with intermediate good producers to meet unanticipated demand and hedge against production shocks. The resulting analysis will quantify the conditions under which market-based supply networks are inherently fragile, particularly when these networks prioritize routine operational efficiency over systemic robustness. Additionally, the project will explore whether public institutions can reduce inefficiencies and facilitate outcomes superior to those achieved through decentralized market operations by implementing data-driven control policies.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15176", "attributes": { "award_id": "1K01AI182501-01", "title": "Applying a Targeted Machine Learning and Causal Inference Approach to Analyzing Long-Term Sequelae of COVID-19 Infection Through the National COVID Cohort Collaborative.", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 6125, "first_name": "Timothy A.", "last_name": "Gondre-Lewis", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-04", "end_date": "2029-08-31", "award_amount": 134923, "principal_investigator": { "id": 31760, "first_name": "Zachary", "last_name": "Butzin-Dozier", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1079, "ror": "", "name": "UNIVERSITY OF CALIFORNIA BERKELEY", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "/ ABSTRACT Candidate: I am an epidemiologist in the Division of Biostatistics at the University of California, Berkeley School of Public Health, and I completed my Ph.D. in Epidemiology in August 2022 at UC Berkeley. Since my graduation, I have worked with the Center for Targeted Machine Learning and Causal Inference (CTML) to apply cutting-edge biostatistical and causal inference methods to pressing COVID-19 research questions using data from the National COVID Cohort Collaborative (N3C). I led a group of CTML epidemiologists and biostatisticians in the NIH Long COVID Computational Challenge (L3C) competition, where we were honored with third place for our ensemble machine learning model that accurately predicted the risk of Long COVID diagnosis based on individual electronic health record (EHR) data in N3C. I aim to become a leader in the application of innovative biostatistical, causal inference, and machine learning methods to impactful research questions related to infectious disease epidemiology. Environment: In order to attain my career goals, my training and mentorship plan will focus on recent advances in biostatistics, causal inference, and data science methods (Targeted Machine Learning) as well as immunology and infectious disease epidemiology. I have assembled an interdisciplinary team of expert biostatisticians, epidemiologists, and clinicians who will support my training. Alan Hubbard (primary mentor) and Mark van der Laan (co-mentor) will provide expert guidance and mentorship on biostatistics, data science, and causal inference. Rena Patel (co-mentor) and Jack Colford (scientific advisor) will provide mentorship and guidance in infectious disease epidemiology and immunology. Research: Researchers and clinicians have made enormous progress in understanding, preventing, and treating acute COVID-19 infection, but there is considerable uncertainty regarding the factors associated with long-term sequelae of COVID-19 infection. Although vaccination is a key strategy for COVID-19 epidemic control, little is known regarding the role of COVID-19 vaccination timing relative to COVID-19 infection (i.e., up-to-date vaccinations and boosters) in preventing long-term sequelae of infection, and the lack of objective Long COVID biomarkers hampers our ability to evaluate, prevent, and treat Long COVID. In Aim 1, I will evaluate the relationship between vaccination timing and Long COVID diagnosis in order to determine an optimized vaccination schedule to minimize Long COVID. In Aim 2, I will assess the relationship between COVID-19 vaccination timing and individual long-term sequelae of COVID-19 infection. In Aim 3, I will assess mediation of the relationship between acute COVID-19 infection and Long COVID via interleukin 6 (IL-6) to evaluate a biological mechanism of interest. I will apply Targeted Machine Learning methods to achieve these aims, which will prepare me for an R01-level application to apply these methods to research questions in infectious disease epidemiology.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15192", "attributes": { "award_id": "1R01HL172859-01", "title": "Mitochondrial metabolism controls alveolar epithelial cell fate", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Heart Lung and Blood Institute (NHLBI)" ], "program_reference_codes": [], "program_officials": [ { "id": 26329, "first_name": "SIDDHARTH KAUP", "last_name": "Shenoy", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": "2029-08-31", "award_amount": 616000, "principal_investigator": { "id": 31773, "first_name": "Seunghye", "last_name": "Han", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 924, "ror": "", "name": "NORTHWESTERN UNIVERSITY AT CHICAGO", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "Patients with severe pandemic SARS-CoV-2 pneumonia suffered damage of alveolar epithelial cells due to direct viral injury, subsequent immune response, and secondary bacterial pneumonia, which presents clinically as the acute respiratory distress syndrome (ARDS). Despite a similar severity of ARDS, some patients recover their lung function without sequelae, while others develop persistent respiratory symptoms and radiographic abnormalities, or progressive lung fibrosis resulting in death or requiring lung transplantation. The mechanisms driving the heterogeneous outcomes remain elusive. Mitochondrial dysfunction and metabolic changes are commonly observed in patients with severe pneumonia/ARDS and in patients with lung fibrosis but whether this dysfunction is causally related to failed epithelial repair after injury is not known. We focus on an intermediate epithelial cell population expressing genes characteristic of both alveolar epithelial type 2 (AT2) and type 1 (AT1) cells. These “transitional cells” are expanded during postnatal development and in several models of lung injury and fibrosis, and human fibrotic lungs. In our published and preliminary studies, we observed that mitochondrial complex I (MCI)-dependent NAD+ regeneration, independent of ATP synthesis, is necessary for postnatal alveologenesis. Rather than inducing a metabolic crisis and cell death, lung epithelial- specific deletion of NDUFS2, an essential MCI subunit protein, prevented AT2-to-AT1 differentiation resulting in a dramatic expansion of transitional cells and subsequent death of the animal from respiratory failure. Transitional cells lacking MCI function demonstrate activation of the integrated stress response (ISR) and a small molecule inhibitor of the ISR rescued the lethality of the knockout mice. I also observed that loss of NDUFS2 in adult AT2 cells leads to the spontaneous development of lung fibrosis and death of the animal from respiratory failure within several months, highlighting the potential importance of this pathway in lung fibrosis. Collectively, we hypothesize that the loss of MCI function increases the mitochondrial NADH/NAD+ ratio through a pathway that requires OMA1, DELE1, and HRI to activate the ISR and enhance ATF4-mediated transcription, precluding normal alveolar epithelial differentiation. I will test this hypothesis in the following two aims: Aim 1: To determine whether an increased mitochondrial NADH/NAD+ ratio and DELE1 are necessary for ISR activation that precludes AT2 to AT1 differentiation in the absence of mitochondrial complex I. Aim 2: To determine whether epithelial ATF4 activation is necessary and/or sufficient for impaired AT2 to AT1 differentiation. We propose causal experiments using sophisticated genetic murine models to link mitochondrial metabolism, activation of the ISR, and failed epithelial differentiation to the development of fibrosis. We pair our experiments with samples collected from patients with pulmonary fibrosis at the time of lung transplant, with a goal of credentialling mitochondrial metabolism and the ISR as targets for therapy to prevent and treat lung fibrosis.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15184", "attributes": { "award_id": "1R15GM155857-01", "title": "Investigating the role of helix-1 in the fibrillization of SAA1-76", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 31765, "first_name": "Thomas Y", "last_name": "Cho", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": "2027-08-31", "award_amount": 496648, "principal_investigator": { "id": 31766, "first_name": "RUEL Z B", "last_name": "DESAMERO", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2515, "ror": "", "name": "YORK COLLEGE", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "AA amyloidosis is a severe complication of chronic inflammatory disorders and is potentially fatal. The amyloid fibrils involved in AA amyloidosis are derived from serum amyloid A (SAA), which is an acute phase reactant protein. In AA amyloidosis, circulating amyloid fibrils are deposited in organs, ultimately leading to their failure. Serum amyloid A (SAA) is the major protein component of amyloid fibrils associated with AA amyloidosis. There is accruing evidence that overexpression of SAA is correlated with the severity of inflammation caused by COVID-19. These highlight the need to unravel the mechanism of SAA misfolding that could in turn facilitate the design of potential inhibitors. Molecular dynamic (MD) simulations have yielded an in silico model for SAA misfolding where the N-terminal helical (helix-1) region plays a pivotal role. Helix-1 is believed to transition from a -helix to -hairpin. Once formed, the -hairpin units are postulated to associate and stack upon themselves to yield fibrils. We propose to investigate the veracity of the in silico model of SAA misfolding by synthesizing and characterizing peptide mutants derived from the helix-1 region of SAA and the longer fragment, SAA1-76. The roles of specific amino acids will be probed along with the trajectory each takes during SAA misfolding. Using standard spectroscopic methods, we will determine changes in amyloidogenic propensity, conformation, key molecular interaction, and amyloid morphology of each peptide during or after SAA fibrillization. Experimental data will be correlated with the findings of the in silico results to yield information on the mechanism. The data obtained from helix-1 fragments SAA1-13 and SAA1-27 will be extended to the truncated peptide, SAA1-76, found in amyloid deposits of SAA. We intend to emply in silico and in vitro study to help yield important mechanistic clues. One of the major goals of this project is to provide students, >50% of whom are underrepresented minorities, with the opportunity to conduct research and gain experience working in a modern biomedical laboratory. Undergraduate researchers involved in the project will be expected to synthesize and spectroscopically characterize peptides, verify spectroscopic data using MD simulation, and characterize amyloid morphology. Each student will focus on aspects of the project that best interest them and fit their background. Regular research group meetings will ensure that students participate in the planning of experiments and analysis of data. Students will have the opportunity to apply theories learned in the classroom to real world biochemical investigation. Research experiences that are based on current technology allow students to solidify and fortify their knowledge. Hands-on experiential learning is one of the most effective approaches to develop students’ critical thinking, perseverance, and confidence that could translate to a fulfilling career. Their experience will help them enter graduate programs and/or find employment in biomedical careers. The educational impact of this project also extends to local high school and community college students working in the PI’s laboratory. The research experiences of these students will help ensure the vibrancy of the scientific infrastructure in the US.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15208", "attributes": { "award_id": "1S10OD034344-01A1", "title": "Thermo IQ-X high-resolution mass spectrometer", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)", "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [ { "id": 28173, "first_name": "YONG", "last_name": "Chen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": "2025-08-31", "award_amount": 737125, "principal_investigator": { "id": 31789, "first_name": "A.Clementina", "last_name": "Mesaros", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 232, "ror": "https://ror.org/00b30xv10", "name": "University of Pennsylvania", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "The requested instrumentation in this proposal is an ultra-high resolution mass spectrometer coupled to an ultra-high performance liquid chromatography system that will be used for lipidomics, metabolomics, isotope tracing, and structural elucidation experiments. Specifically, we are requesting funds for a Thermo Scientific™ Orbitrap™ IQ-X™ Tribrid™ Mass Spectrometer coupled to a Vanquish dual column liquid chromatography system, to expand our technological capabilities and offerings to its user base. This instrument will be housed in the Translational Biomarker Core (TBC) in the Center of Excellence in Toxicology (CEET) at the Perelman School of Medicine of the University of Pennsylvania (Penn). The TBC currently serves over 80 investigators from Penn and beyond. These collaborations range from fee-for-service customers to extensive grant-based collaborations. Until 2016, the TBC only offered targeted quantification assays and proteomics methodologies. In 2016, the Core acquired a Dionex™ Ultimate™ HPG-3400RS ultra high-pressure liquid- chromatography (UPLC) that was interfaced with an Orbitrap QE-HF that was running proteomics using a nano- flow-LC in the Blair laboratory. With limited instrument time, the Core developed its lipidomic platform by combining the HRMS raw data with Lipids Search (Thermo) software for lipids identification. This assay is one of the most requested assays offered by the Core, and through collaborations, we have now more than 300 lipids standards used for calibration curves. During the University restrictions due to Covid-19 in spring 2020, we ran the 600 metabolomics standards commercially available, building a library for Compound Discoverer 3.2 (Thermo). The metabolomics workflow was used for several successful grant submissions during the last two years. The Core would like to expand its capabilities to run these types of highly multiplexed and untargeted omics routinely, to expand technological capabilities, and fit offerings to its user base needs. This proposal highlights the need of omics assays from 29 users (28 with NIH funding). Additionally, the core has established ongoing collaborations with institutes and centers at Penn including Children’s Hospital of Philadelphia (CHOP), the Institute for Translational Medicine and Therapeutics, and the Institute of Immunology. Given the focus of the users on the identification of novel small molecule biomarkers of inflammation and related chronic diseases such as cancer and diabetes, this mass spectrometer is urgent and vital for our research projects. Expertise in the Core includes staff that is responsible for instrument maintenance, sample preparation, method development, and data analysis, including large data sets that require the use of bioinformatics software for differential analysis. Furthermore, having a dedicated HRMS instrument will complement the recent expansion of our Core staff. It will allow method development time to expand core capabilities and the continuation of a more extensive education and training arm of our mission, to provide our expertise in LC-HRMS analysis, experimental planning and training to collaborators who are interested in better understanding mass spectrometry applications.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15995", "attributes": { "award_id": "1IK2HX003695-01A2", "title": "Improving Specialty Care Through Virtual Care Models", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2026-01-01", "end_date": "2030-12-31", "award_amount": null, "principal_investigator": { "id": 44448, "first_name": "Rebecca", "last_name": "Tisdale", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3442, "ror": "", "name": "VETERANS ADMIN PALO ALTO HEALTH CARE SYS", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "1 Background: Specialty care deserts—the absence of specialists in geographic regions—have led to an access 2 crisis for the VA. In addition to increasing wait times and causing delays in care, these access needs drive many 3 Veterans to seek care outside VA, resulting in fragmented care, increased risks for hospitalization and hospital 4 readmission, and higher costs. In response, VA has launched the Clinical Resource Hub (CRH) program, which 5 seeks to deliver virtual care from “hub” to “spoke” sites in VA. VISN 21 has begun implementing this model in 6 cardiology at several spoke sites, but little is known about how care utilization and quality within the program. 7 Significance/Impact: This work seeks to better understand the effects of a virtual model of specialty care, in 8 this case cardiology care, on Veterans’ care access and quality. In addition, it aligns closely with several VA and 9 HSR&D priorities, chiefly access to care, virtual care/telehealth, and advancing the goals of the MISSION Act. 10 Innovation: The CRH program and the virtual care model at its core have yet to be studied in depth, and there 11 is no research in progress regarding specialty CRH despite strong interest at the national VA level in 12 understanding how specialty CRH is used and associated outcomes. Given that virtual cardiology care was very 13 limited prior to the COVID-19 pandemic, cardiology CRH is particularly novel. Hence, this project would add to 14 the limited body of research examining virtual cardiology care in the VA. In addition, the proposed work seeks to 15 evaluate this virtual care model at a time of unprecedented choice for Veterans between in-person and virtual 16 care, and limited data on how best to integrate these modalities. 17 Specific Aims: The proposed CDA will offer mentorship and training for me to pursue the following aims: 18 Aim 1. Evaluate quality of cardiology care associated with CRH implementation with administrative data. 19 I will use adjusted difference-in-difference event studies to compare cardiology quality metric achievement for 20 patients who received cardiology care via CRH versus those who received conventional VA-based cardiology care. 21 Aim 2. Assess Veteran perceptions of quality of cardiology care delivered via CRH. 22 I will interview Veterans participating in the CRH program and their caregivers regarding their experiences and 23 perceptions of quality of CRH cardiology care and elicit suggestions for key metrics to focus on for improvement. 24 Aim 3. Construct intervention to track and improve access to high-quality, equitable care through CRH. 25 Building on finding from Aims 1 and 2, I will interview clinicians and employ a facilitated deliberative process with 26 an expert advisory group to construct and pilot an intervention to improve quality. 27 Methodology: In Aim 1, I will use a difference-in-difference event study design to assess the impact of the program 28 on a battery of validated and/or guideline-based quality of cardiology care metrics. In Aim 2, guided by the Fortney 29 model of care access and quality, I will conduct semi-structured interviews of Veterans and caregivers receiving 30 care through the VISN 21 CRH program to understand their experiences with the CRH program and what outcomes 31 they recommend to include in a quality improvement intervention. In Aim 3, I will interview clinicians (Aim 3.1) and 32 conduct a facilitated deliberation process (Aim 3.2) to inform the construction of an intervention (proactive panel 33 management using a clinical dashboard tool) to track and improve quality of care and pilot the intervention. 34 Next Steps/Implementation: To continue moving this research into practice to improve health outcomes for 35 Veterans, I will extend the analysis of cardiology quality of care to compare cardiology care in the community to 36 CRH care. In addition, I will assess the effect of the intervention constructed in Aim 3 on patient outcomes and 37 clinician satisfaction via a hybrid implementation-effectiveness trial. I will continue to work with operational partners 38 to ensure cardiology CRH is improving access to high-quality cardiology care for Veterans. This project supports 39 my goal of becoming an independent VA health services researcher and leader in optimizing cardiovascular 40 disease care access, value, and equity for Veterans through virtual care innovations and implementation.", "keywords": [ "Achievement", "Address", "Area", "COVID-19 pandemic", "California", "Cardiology", "Cardiovascular Diseases", "Cardiovascular system", "Caregivers", "Caring", "Characteristics", "Cladribine", "Clinical", "Clinical Services", "Communities", "Community Health Care", "Dangerousness", "Data", "Disease", "Ensure", "Equity", "Evaluation", "Event", "Geographic Locations", "Goals", "Guidelines", "Health", "Health Services", "Health Services Accessibility", "Heart failure", "Homogeneously Staining Region", "Hospitalization", "Hospitals", "Improve Access", "Intervention", "Interview", "Medical", "Mentors", "Mentorship", "Methodology", "Methods", "Modality", "Modeling", "Morbidity - disease rate", "Nevada", "Outcome", "Pacific Islands", "Patient-Focused Outcomes", "Patients", "Perception", "Persons", "Physicians", "Policies", "Positioning Attribute", "Process", "Qualitative Methods", "Quality of Care", "Recommendation", "Research", "Research Design", "Research Personnel", "Resources", "Risk", "Rural Health", "Safety", "Site", "Specialist", "Structure", "Suggestion", "Telemedicine", "Telephone", "Testing", "Time", "Training", "Training Activity", "Veterans", "Visit", "Wait Time", "Work", "adverse outcome", "care fragmentation", "care seeking", "care utilization", "clinical implementation", "connected care", "cost", "dashboard", "design", "effectiveness/implementation trial", "experience", "follow-up", "health economics", "hospital readmission", "hospitalization rates", "implementation efforts", "implementation science", "improved", "innovation", "insight", "interest", "intervention effect", "medical specialties", "mortality", "novel", "operation", "patient subsets", "pilot test", "preference", "programs", "rapid growth", "research to practice", "response", "rural counties", "satisfaction", "sociodemographics", "southern nevada", "telehealth", "therapy design", "tool", "virtual", "virtual delivery", "virtual health care", "virtual model" ], "approved": true } }, { "type": "Grant", "id": "15169", "attributes": { "award_id": "1R01HS029862-01A1", "title": "Effects of COVID-19 Related Medicaid Policy Changes in the Marshallese COFA Migrant Population", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "Agency for Healthcare Research and Quality (AHRQ)" ], "program_reference_codes": [], "program_officials": [ { "id": 24040, "first_name": "Fred", "last_name": "Hellinger", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": "2028-06-30", "award_amount": 372996, "principal_investigator": { "id": 31753, "first_name": "Jennifer Audrey", "last_name": "Andersen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 772, "ror": "", "name": "UNIV OF ARKANSAS FOR MED SCIS", "address": "", "city": "", "state": "AR", "zip": "", "country": "United States", "approved": true }, "abstract": "Access to healthcare is a persistent public policy concern, particularly for Marshallese Compact of Free Association (COFA) migrants in the United States. This research addresses the impact of Medicaid policy changes, prompted by the COVID-19 pandemic, on healthcare access for Marshallese COFA migrants residing in Northwest Arkansas, where the largest settlement of this population (~15,000) exists. Despite their eligibility for Medicaid under the 1986 RMI-US COFA agreement, subsequent legislative changes, notably the 1996 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), resulted in a significant portion (approximately 50%) of the Marshallese population being devoid of healthcare coverage. Even after the enactment of the Affordable Care Act and Medicaid expansion in 2014, which did not reinstate Medicaid coverage for COFA migrants, these disparities persisted. The Consolidated Appropriations Act of December 2020 reinstated Medicaid access after a 25-year gap. However, the effectiveness of this policy change in ensuring enrollment and optimizing healthcare service utilization remains unknown. The overall objective of this study is to determine the effect of Medicaid policy changes enacted in response to the COVID-19 pandemic for Marshallese COFA migrants. We will leverage our long-standing community-engaged relationship with the Marshallese community in Arkansas to collect primary data to generate important data on the barriers and facilitators to Medicaid enrollment for Marshallese COFA migrants, and to inform effective community-based interventions. Our Specific Aims are: Aim 1: Examine the Medicaid enrollment process and identify barriers and facilitators to healthcare for Marshallese newly eligible under Medicaid policy changes. We will conduct four focus groups with 50 Marshallese to qualitatively explore barriers and facilitators to Medicaid enrollment and accessing healthcare services. Aim 2: Conduct a needs assessment to assess barriers and facilitators to inform community-based interventions to improve Medicaid enrollment and use of primary and preventative healthcare services. We will develop and administer a survey to 750 Marshallese to assess the need for community-based interventions to increase enrollment and the use of healthcare services. The survey will focus on barriers and facilitators to Medicaid enrollment and primary/preventative healthcare utilization, and use the themes that emerge in Aim 1 to direct the selection of additional existing validated survey measures. The study's findings will contribute essential information for the development of community-based interventions tailored to enhance Medicaid enrollment and healthcare service utilization among COFA migrants and other underserved populations. The established rapport with the Marshallese community uniquely positions us to implement and evaluate these interventions, fostering equitable healthcare delivery.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15223", "attributes": { "award_id": "1R01AG087296-01", "title": "Alzheimer's Special Care Units in Nursing Homes: Racial and Ethnic Disparities, Resident Outcomes, and State Policies", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Aging (NIA)" ], "program_reference_codes": [], "program_officials": [ { "id": 27518, "first_name": "THERESA YOUNGJOO", "last_name": "Kim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": "2028-05-31", "award_amount": 424184, "principal_investigator": { "id": 27405, "first_name": "Huiwen", "last_name": "Xu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 265, "ror": "https://ror.org/03czfpz43", "name": "Emory University", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "Alzheimer's special care units (SCUs) are a promising care model for nursing home residents with Alzheimer's Disease & Related Dementias (ADRD). SCUs provide higher quality care and improve outcomes for residents with ADRD. Our preliminary analysis further found that, in facilities with an SCU, the disparities in 3-month hospitalization rates and pressure ulcers between Hispanic and White residents were eliminated or greatly reduced. Despite the benefits of SCUs, racial and ethnic minority residents are less likely to access SCUs than White residents, suggesting that lack of SCU access may be a mechanistic pathway responsible for disparities in outcomes. Currently, SCUs are available in only 14% of nursing homes and access varies substantially across states. State Medicaid policies and SCU regulations can incentivize or disincentivize nursing homes to develop SCUs. By analyzing national Medicare claims and resident assessment data, as well as unique Ohio surveys of SCUs and resident and family satisfaction with care, we propose to understand the extent to which racial and ethnic differences in SCU access contribute to disparities in outcomes, and the associations of current state policies and regulations with SCU availability. The specific aims are: Aim 1) To examine disparities in access to Alzheimer's SCUs among Black and Hispanic residents with ADRD; Aim 2) To understand SCU access as a pathway to disparities in health outcomes among Black and Hispanic residents with ADRD; and Aim 3) To investigate which state policies are associated with increased availability of SCUs. The primary analyses will study the 819,415 newly-admitted long-stay residents with ADRD in 15,305 nursing homes from 2011 to 2019. The decomposition method will uncover factors that explain disparities in SCU access among Black and Hispanic residents, and mediation analyses will assess how differences in SCU access contribute to racial and ethnic disparities in health outcomes. Dominance analyses will evaluate the contribution of specific SCU characteristics (physical environment, staffing, and physician involvement) to health outcomes and resident and family satisfaction, as well as reduced racial and ethnic disparities. We will also analyze 2020- 2024 data to examine whether our findings hold during and after the COVID-19 pandemic. Hierarchical Generalized Linear Mixed Models and Difference-in-Differences method will explore which state policies (e.g., supplementary payments for SCU care, Medicaid payment-to-cost ratios, regulations about staffing or training) are associated with SCU availability. Understanding the role of SCU access in racial and ethnic disparities in ADRD-related outcomes can inform policymakers as they seek to mitigate disparities in nursing home care.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1, "pages": 1424, "count": 14236 } } }