Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=2&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=1405&sort=other_investigators", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=other_investigators", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=other_investigators" }, "data": [ { "type": "Grant", "id": "15036", "attributes": { "award_id": "5R21AI175905-02", "title": "Investigation of sarbecovirus exposure patterns and development of pan-SARS-CoV-2 neutralizing antibody responses in high-risk cohorts in Myanmar", "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": 6243, "first_name": "BROOKE ALLISON", "last_name": "Bozick", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-06", "end_date": "2025-05-31", "award_amount": 214874, "principal_investigator": { "id": 24369, "first_name": "Tierra Smiley", "last_name": "Evans", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 746, "ror": "", "name": "UNIVERSITY OF CALIFORNIA AT DAVIS", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern pose a global challenge to the effectiveness of existing and future vaccines. This project will address questions surrounding the immunological response to different sarbecovirus exposure patterns with implications for vaccine development by conducting longitudinal repeated surveillance of unique human populations, previously determined to be highly exposed to a diversity of SARS-CoV-2-related coronaviruses in Myanmar. There is a timely opportunity to follow these communities, particularly immediately following SARS-CoV-2 infection and/or vaccination to understand which previous sarbecovirus exposure patterns expand the likelihood of development of pan-sarbecovirus neutralizing antibodies. We will evaluate the impact of diverse patterns of natural and vaccination-based sarbecovirus exposure on development of pan- sarbecovirus neutralizing antibodies by following three specific human cohorts: (1) elephant loggers engaged in bushmeat hunting (including bats and pangolins) during the process of active deforestation of Myanmar’s remaining teak forests, (2) bat guano harvesting communities surrounding HpaAn cave systems in Kayin State and (3) a previously uninvestigated population engaged in religious activities within the Karst cave systems in the Northern Dawna range. Waxing and waning of specific antibody responses will be followed over time through use of pre-pandemic archived specimens from these populations and repeated prospective sampling. We will utilize a novel Luminex bead-based multi-plex sarbecovirus assay, capable of simultaneously detecting neutralizing antibodies against 21 different hACE2-binding sarbecoviruses. Exposure patterns to specific sarbecoviruses will be identified and viral characteristics evaluated for their contribution to the likelihood of developing pan-sarbecovirus antibody responses, including viral genetic and functional phenotypic similarity and host plasticity (breadth of host species a virus is known to infect). Patterns of prior natural sarbecovirus exposure coupled with natural SARS-COV-2 infection and / or vaccination will then be evaluated for contributions to broadly reactive antibody responses. Data generated through this project will inform on potential cross sarbecovirus clade vaccination strategies that could protect against both known and future emerging SARS-CoV-2 variants. We will also conduct an in-depth investigation of behavioral risk factors contributing to zoonotic sarbecovirus spillover that will aid in mitigation strategies in this critically important ecological region for coronavirus emergence.", "keywords": [ "2019-nCoV", "Age", "Antibody Response", "Behavior", "Behavioral", "Binding", "Biological", "Biological Assay", "COVID-19 pandemic effects", "Characteristics", "Chiroptera", "Communities", "Coupled", "Data", "Deforestation", "Development", "Effectiveness", "Elephants", "Exposure to", "Frequencies", "Funding", "Future", "Harvest", "Human", "Immune response", "Immunization Programs", "Individual", "Infection", "Investigation", "Medical History", "Myanmar", "Pattern", "Phenotype", "Population", "Process", "Public Health", "Religion", "Risk Behaviors", "Risk Factors", "SARS coronavirus", "SARS-CoV-2 infection", "SARS-CoV-2 infection history", "SARS-CoV-2 variant", "Sampling", "Sarbecovirus", "Serum", "Specimen", "Surveys", "System", "Time", "USAID", "United States National Institutes of Health", "Vaccination", "Vaccines", "Viral", "Virus", "Waxes", "Work", "Zoonoses", "biological specimen archives", "cohort", "exposed human population", "forest", "high risk", "high risk behavior", "neutralizing antibody", "novel", "novel coronavirus", "post SARS-CoV-2 infection", "pre-pandemic", "prospective", "vaccination strategy", "vaccine development", "vaccine strategy", "variants of concern", "virus genetics" ], "approved": true } }, { "type": "Grant", "id": "15066", "attributes": { "award_id": "5R00EB031913-03", "title": "De novo design of a generalizable protein biosensor platform for point-of-care testing", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [ { "id": 27406, "first_name": "SHAWN PATRICK", "last_name": "Mulvaney", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-01", "end_date": "2026-05-31", "award_amount": 249000, "principal_investigator": { "id": 27407, "first_name": "Hsien Wei", "last_name": "YEH", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1547, "ror": "", "name": "UNIVERSITY OF CALIFORNIA SANTA CRUZ", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "úú PROJECT SUMMARY/ABSTRACT Delivering diagnostic services at the point-of-care (POC) can improve the quality of healthcare in clinics, in emergency settings, or at home, which can potentially ease hospitals’ burden, for instance, during the COVID- 19 pandemic. Precision and personalized medicine revolution also require POC testing to provide readily available biomarker information to clinicians. The goal of this career development proposal is to create fast, inexpensive, sensitive, and reliable molecular diagnostics to address the 21st-century healthcare challenges. The central hypothesis is that we can efficiently utilize computational protein design to create modular allosteric protein switches, named LOCKR (Latching Orthogonal Cage–Key pRotein), that enable the rapid and reversible conformational changes upon interaction. As a proof of principle, we demonstrate that LOCKR- based biosensors can be configured to produce bioluminescence upon the addition of clinical targets (e.g., botulinum toxin, cardiac troponin I, HER2 receptor, Fc domain, anti-HBV mAb, anti-SARS-CoV2 antibodies, and SARS-CoV2 receptor-binding domain/spike protein, Fig 1 and 2) in homogeneous “all-in-solution” assays. Due to the modularity of LOCKR sensor platform and the advance in de novo binder design for arbitrary protein targets, we proposed the integration of both features as the universal strategy to develop tailored biosensors for user-defined targets. The main specific aims for the independent phase are to iteratively expand LOCKR-based diagnostics with the synergy of (1) de novo protein binder design to directly detect various disease protein biomarkers, and (2) indirectly detect the antibodies that compete with the designed interface, as POC devices; and (3) to repurpose the original luminescence signal with other compatible readouts by exchanging the reporter modules. For more specific proof-of-concept projects during the mentored phase, I describe in Aim 1 the use of state-of-the-art computational protein design methods to create an interleukin-6 binder and biosensor. In Aim 2, I propose a general way to develop antibody biosensors by demonstrating COVID-19 serological tests as an example. With my expertise in biosensor engineering, I attempt in Aim 3 to develop a ratiometric bioluminescence resonance energy transfer (BRET) biosensor to analyze the HBV antibody and a colorimetric biosensor to measure human cardiac troponin I level. Ultimately, I anticipate this new sensor platform is significant for the development of robust protein sensors that will be broadly applicable to arbitrary targets and enabling its POC compatible readouts for future diagnostics.", "keywords": [ "2019-nCoV", "Address", "Affinity", "Algorithms", "Antibodies", "Area", "Basic Science", "Binding", "Binding Proteins", "Biological Assay", "Biological Markers", "Bioluminescence", "Biosensor", "Body Fluids", "Botulinum Toxins", "Bypass", "COVID-19", "COVID-19 pandemic", "Cardiac", "Caring", "Clinic", "Clinical", "Collection", "Color", "Colorimetry", "Consumption", "Coupled", "Coupling", "Creativeness", "Darkness", "Detection", "Development", "Development Plans", "Devices", "Diagnostic", "Diagnostic Reagent", "Diagnostic Services", "Directed Molecular Evolution", "Disease", "Drops", "ERBB2 gene", "Economics", "Energy Transfer", "Engineering", "Enzyme-Linked Immunosorbent Assay", "Equilibrium", "Event", "Fc domain", "Future", "Gene Order", "Goals", "Health Priorities", "Healthcare", "Hepatitis B Antibodies", "Hepatitis B Virus", "Home", "Hospitals", "Human", "Incubated", "Interleukin-6", "Light", "Luciferases", "Measurable", "Measures", "Medical", "Mentors", "Mentorship", "Methods", "Mission", "Modality", "Molecular", "Molecular Conformation", "Monitor", "Monoclonal Antibodies", "Names", "Oligonucleotide Microarrays", "Patients", "Peptides", "Phase", "Protein Engineering", "Proteins", "Published Comment", "Reporter", "Reporting", "Research", "Research Personnel", "SARS-CoV-2 antibody", "Sampling", "Serology test", "Signal Transduction", "Specimen", "Surface", "System", "Technology", "Therapeutic", "Thermodynamics", "Time", "Treatment outcome", "Troponin I", "United States National Institutes of Health", "Work", "Yeasts", "antibody detection", "career", "career development", "clinically relevant", "complement system", "design", "disability", "emergency settings", "flu", "health care availability", "health care quality", "health care service", "improved", "instrument", "interest", "luminescence", "molecular diagnostics", "neutralizing antibody", "novel", "pandemic impact", "pathogen", "personalized medicine", "point of care", "point of care testing", "point-of-care diagnostics", "precision medicine", "protein biomarkers", "ratiometric", "receptor", "receptor binding", "seasonal influenza", "sensor", "synergism", "systemic inflammatory response", "tv watching" ], "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": "15081", "attributes": { "award_id": "5R21DA058581-02", "title": "Rapid measurement of novel harm reduction housing on HIV risk, treatment uptake, drug use and supply", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Drug Abuse (NIDA)" ], "program_reference_codes": [], "program_officials": [ { "id": 10174, "first_name": "Sheba King", "last_name": "Dunston", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-05-01", "end_date": "2025-04-30", "award_amount": 207369, "principal_investigator": { "id": 26304, "first_name": "TRACI C", "last_name": "GREEN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 280, "ror": "https://ror.org/05abbep66", "name": "Brandeis University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic has strained an ongoing housing crisis across cities and towns, leaving unprecedented numbers of people homeless and creating poor health conditions in precarious, concentrated homeless encampments. In Boston, Massachusetts, an October 2021 public health emergency declaration preceded a January 2022 massive relocation campaign that moved over 200 people from a large street encampment into 5 novel “harm reduction housing” (HRH) programs. The area is known for its proximity to area hospitals, its open-air drug market, and violence related to drugs and crime. These programs provide housing units with access to harm reduction supplies like sterile syringes and other safer use materials, naloxone, and low-barrier medication treatment, and staff provide these services according to policies that champion the principles of “meeting people where they are”. But the HRH sites differ in ways that may affect resident outcomes, and uptake of services vary. Data suggest that housing interventions may tragically increase isolation and thus overdose risk; others claim lives will be saved and life-saving treatments will start because of their improved access at the HRH sites. An initial case-crossover analysis of those recently relocated echoed a mixture of positive and negative effects. Lacking clear-cut, scientifically rigorous processes that consider both intended and unintended consequences of these actions, we propose a rapid, mixed methods study to efficiently examine the immediate effects of the relocation efforts and the longer-term impacts of living in the novel HRH. Specifically, this time-sensitive study will collect survey, interview, and drug supply data from the community of people who are homeless and use drugs in the concentrated area of Boston who have been affected by these recent actions. The study will help to determine short and long-term impacts of: a) rapid relocation and how residents successfully navigated it; and b) co-provision of harm reduction services and housing on individual- level behaviors and local drug supply outcomes. Specific aims are to: Aim 1) Develop a measure of harm reduction services and policies to inventory their provision and use in HRH sites for studying continuity, uptake, and evolution of care. Aim 2) Enroll an observational cohort following 100 HRH residents for 12 months to catalogue relocation effects and understand how harm reduction services use changes drug use, HIV and drug risk behaviors, treatment uptake, and the local drug supply. Data specific to new HRH resident cohort members will augment our prior case-crossover analysis of relocation impacts. Aim 3) Conduct repeat, longitudinal one-on-one interviews with 25 cohort members to gain greater insight into the nuances of relocation and HRH residence, including health and safety impacts, changes in collective efficacy, and gender considerations. Findings will contribute to harm reduction science and will be directly relevant to jurisdictions considering HRH, adapting housing contracts to incorporate harm reduction services, and planning public health-directed mitigation plans for housing relocations or disaster responses.", "keywords": [ "Abstinence", "Acute Hepatitis", "Address", "Affect", "Air", "Area", "Behavior", "Boston", "COVID-19 pandemic", "Caring", "Catalogs", "Cause of Death", "Cities", "Communicable Diseases", "Communities", "Contracts", "Crime", "Data", "Data Set", "Disasters", "Disease Outbreaks", "Drug abuse", "Drug usage", "Enrollment", "Environment", "Epidemiology", "Equipment and supply inventories", "Evolution", "Exposure to", "Fentanyl", "Gender", "Goals", "HIV", "HIV risk", "Harm Reduction", "Health", "Hepatitis A Virus", "Homeless persons", "Homelessness", "Hospitals", "Housing", "Illicit Drugs", "Improve Access", "Individual", "Injections", "Intervention", "Interview", "Leadership", "Learning", "Life", "Link", "Massachusetts", "Measurement", "Measures", "Methods", "Naloxone", "Natural experiment", "Outcome", "Overdose", "Patterns of Care", "Persons", "Pharmaceutical Preparations", "Policies", "Positioning Attribute", "Process", "Prophylactic treatment", "Public Health", "Public Housing", "Research", "Research Support", "Risk", "Risk Behaviors", "Role", "SARS-CoV-2 infection", "Safety", "Science", "Seasons", "Service provision", "Services", "Site", "Social isolation", "Social outcome", "Sterility", "Structure", "Surveys", "Syringes", "Time", "United States", "Violence", "Work", "addiction", "cohort", "drug market", "experience", "health care service", "improved outcome", "insight", "meetings", "member", "multidisciplinary", "novel", "overdose risk", "peer", "peer support", "pre-exposure prophylaxis", "prevention service", "programs", "public health emergency", "residence", "response", "risk mitigation", "service uptake", "social", "social cohesion", "social health determinants", "statistics", "success", "supported housing", "syndemic", "transitional housing", "uptake" ], "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": "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": "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": "15123", "attributes": { "award_id": "2437982", "title": "EAGER: Collaborative Research: Fostering Collective Rationality Among Self-Interested Agents to Improve Design and Efficiency of Mixed Autonomy Networks and Infrastructure Systems", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "CIS-Civil Infrastructure Syst" ], "program_reference_codes": [], "program_officials": [ { "id": 2042, "first_name": "Siqian", "last_name": "Shen", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] } ], "start_date": "2024-09-01", "end_date": null, "award_amount": 154063, "principal_investigator": { "id": 31681, "first_name": "Jia", "last_name": "Li", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 306, "ror": "https://ror.org/05dk0ce17", "name": "Washington State University", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true }, "abstract": "This EArly-Concept Grants for Exploratory Research (EAGER) project will investigate the emergence, mechanisms, and applications of collective rationality (CR) among self-interested agents in the design of mixed autonomy networks and infrastructure systems. In many natural and engineering systems, various collective phenomena, such as spontaneous cooperation, spatial segregation, and behavior evolution and formation of social norms, can emerge at system level when the decisions and maneuvers of self-interested agents interlace with each other. Strategic agent behaviors play a key role in this process. This observation suggests that one may obtain a system with desired properties by carefully designing behaviors of its agents. The research will explore this idea and put forward the concept of “collective rationality” of mixed traffic towards with the intent of explaining the formation of cooperation among self-interested driving agents in mixed autonomy transportation systems, to reduce travel cost, uncertainties, fuel emission, as well as to enhance equity among all road users. Broader applications include autonomous vehicle behavior design, emergency evacuation, and mitigation of pandemic spread. The research will be further disseminated through curriculum design, K-12 education, and collaboration with practitioners, local government, and industry partners. <br/><br/>This research project will explore and rigorously define the concept of collective rationality in mixed traffic and its application in designing strategic behaviors of autonomous driving agents in mixed autonomy environments. The core research hypothesis is that collective rationality can emerge in broad scenarios even if the involved agents are self-interested. Game theory and reinforcement learning will be leveraged to verify this hypothesis theoretically and computationally. To establish theoretical models of collective rationality in mixed traffic, two classes of models with different levels of agent behavior details will be developed, respectively focusing on the one-shot interaction of n-class driving agents, and dynamic inter- and intra-class interactions and an analytical Fokker-Planck approximation to the corresponding evolution dynamics. To develop frameworks for collective rationality-informed autonomous vehicle behavior design, researchers will consider two autonomous vehicle behavior design frameworks using reinforcement learning, which incorporate collective rationality in reward design and employ a bi-level pricing structure to equitably fine-tune the benefit of cooperation among agents. The research team will also expand and explore the CR concept for other application contexts, such disaster evacuations.<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": "15096", "attributes": { "award_id": "2403380", "title": "Collaborative Research: SHF: Medium: SCIOPT: Toward Certifiable Compression-Aware SciML Systems", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Software & Hardware Foundation" ], "program_reference_codes": [], "program_officials": [ { "id": 2785, "first_name": "Almadena", "last_name": "Chtchelkanova", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-10-01", "end_date": null, "award_amount": 272992, "principal_investigator": { "id": 31636, "first_name": "Martin", "last_name": "Burtscher", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 204, "ror": "", "name": "Texas State University - San Marcos", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The future of science-enabled discoveries critically relies on the speed of high-performance simulations conducted at large scales and high resolutions. Unfortunately, lacking such performance and scale, current approaches cannot keep up with the backlog of problems in areas of paramount societal consequence, such as climate science and the spread of pandemics. A principal reason for these shortfalls is the rising cost of moving huge amounts of simulation data between supercomputer memories and processors – a cost that increasingly dwarfs the time spent in actual computations. Thus, developing techniques to reduce the volume of data exchanged without sacrificing accuracy is key to future progress in computation-enabled research. Such data reduction is even more important in the emerging area of Scientific Machine Learning (SciML), where simulations are assisted by artificial intelligence (AI) based surrogate models, an area where the data exchange needs are often much higher. The investigators’ expertise in scientific machine learning, data compression, compilers, and program correctness will be central in our collaboration to help SciOPT achieve its goal of fast and reliable AI-assisted scientific simulations. The impact of this project will be to establish new technologies that reduce data volume without sacrificing accuracy in both high-performance computing and the emerging area of SciML. These technologies, in turn, translate directly into societal benefits such as improved healthcare and safer environments. The project will broaden participation in this area through undergraduate research plans that reach out to students from groups underrepresented in computing.<br/><br/>This research project, entitled SciOPT, will principally rely on data compression to reduce the amount of data moved: simulation data will be compressed before transmission and decoded upon reception before applying computations. The investigators will also pursue the potentially even more impactful approach of compressing the data and applying computations directly on the compressed data. SciOPT will evaluate both of these approaches in the context of challenging SciML applications that are currently bottlenecked by data exchanges. To ensure higher degrees of automation and productivity, SciOPT will develop efficient compiler-based methods to manage compressed data layout and locality. Moreover, it will automatically generate high-speed compression algorithms that are tailored to the data. To ensure the veracity of the computational results produced by these compressed-data simulations, SciOPT will include rigorous correctness-checking methods at multiple stages to guard the overall simulation workflows.<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": "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 } } ], "meta": { "pagination": { "page": 2, "pages": 1405, "count": 14046 } } }