Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=3&sort=-end_date
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-end_date", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=-end_date", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=4&sort=-end_date", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=-end_date" }, "data": [ { "type": "Grant", "id": "15990", "attributes": { "award_id": "1R01AI191459-01A1", "title": "Living Microrobot for Active Therapeutic Delivery to Treat Severe Pulmonary Infections", "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": 44442, "first_name": "MEENU MISHRA", "last_name": "UPADHYAY", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-02-02", "end_date": "2031-01-31", "award_amount": 720035, "principal_investigator": { "id": 27606, "first_name": "Victor", "last_name": "Nizet", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 27607, "first_name": "Liangfang", "last_name": "Zhang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 44443, "first_name": "JOSEPH", "last_name": "WANG", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2637, "ror": "", "name": "UNIVERSITY OF CALIFORNIA, SAN DIEGO", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Multidrug-resistant (MDR) lower respiratory tract infections represent the single leading cause of infectious disease-associated mortality in the United States. Particularly worrisome trends are being observed in the case of ventilator-associated pneumonia (VAP), which affects vulnerable patient populations in intensive care units (ICUs). Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA) are the most common causative agents in global epidemiology of VAP, and they are becoming increasingly prevalent as antibiotics continue to be used indiscriminately and with waning effectiveness. It is imperative that more effective treatment modalities be advanced to adequately manage serious pulmonary infections in the clinical setting. Here we describe a highly innovative delivery and therapeutic concept, living microrobot therapeutics, for critically ill patients with severe P. aeruginosa and MRSA lung infections. The microrobot platform is consisting of Chlamydomonas reinhardtii microalgae modified with neutrophil membrane-coated and drug-loaded polymeric nanoparticles (denoted ‘algae-NP-robots’), and has unique multifold mechanisms of action. The microalgae help to improve tissue penetration and retention of the drug payload within the lungs, while the neutrophil membrane- coated nanoparticles help to shield the drug payload from biological environments, reduce immune clearance, and enable specific binding with target pathogens. Besides carrying drug payload, the neutrophil membrane- coated nanoparticles can further serve as ‘nanosponges’ that act to neutralize excessive pro-inflammatory cytokines, thus reducing the danger of cytokine storm. By combining the unique properties of these two systems, the algae-NP-robots have proven to be a capable platform for active drug delivery and excel at treating bacterial pulmonary infections. In this proposal, we describe our extensive prior published and preliminary results that strongly support the novel therapeutic concept of algae-NP-robots for the treatment of severe Gram-negative and Gram-positive pulmonary bacterial infections in ICU patients. In Aim 1, we will focus on further optimizing the algae-NP-robot formulation to maximize its therapeutic potential. In Aim 2, we seek to better understand the mechanisms by which drug-loaded algae-NP-robots can effectively clear bacterial infection using P. aeruginosa lung infection model, in which efficacy has already been demonstrated. In Aim 3, we will extend the algae-NP- robot platform for the treatment of Gram-positive pathogen (MRSA) lung infection in order to demonstrate the generalizability of the platform. Each of the Aims can be completed independently, although the information gleaned from one can be used to improve the overall approach, which can then benefit the others.", "keywords": [ "Active Biological Transport", "Acute", "Aerosols", "Affect", "Algae", "Antibiotics", "Antimicrobial Resistance", "Attention", "Automobile Driving", "Bacteria", "Bacterial Infections", "Benchmarking", "Binding", "Biological", "Biomimetics", "Blood Platelets", "Cell membrane", "Cells", "Chlamydomonas reinhardtii", "Chronic", "Clinical", "Clinical Management", "Communicable Diseases", "Complex", "Critical Illness", "Data", "Development", "Disease", "Drug Delivery Systems", "Effectiveness", "Encapsulated", "Environment", "Epidemiology", "Formulation", "Glean", "Goals", "In Vitro", "Inflammatory", "Inhalation", "Inherited", "Intensive Care Units", "Intervention", "Location", "Lower Respiratory Tract Infection", "Lower respiratory tract structure", "Lung", "Lung infections", "Medical", "Medicine", "Membrane", "Methods", "Microbial Biofilms", "Modality", "Modeling", "Motion", "Multi-Drug Resistance", "Nebulizer", "Pathologic", "Patients", "Penetration", "Pharmaceutical Preparations", "Property", "Proteins", "Pseudomonas aeruginosa", "Publishing", "Robot", "Route", "Safety", "Source", "Staphylococcus aureus infection", "Structure", "Structure of parenchyma of lung", "System", "Testing", "Therapeutic", "Tissues", "Toxic effect", "Toxin", "Treatment Efficacy", "United States", "Vancomycin", "absorption", "bactericide", "clinical translation", "combat", "comorbidity", "cytokine", "cytokine release syndrome", "design", "effective therapy", "efficacy testing", "fabrication", "immune clearance", "improved", "in vivo", "in vivo evaluation", "innovation", "lung pathogen", "methicillin resistant Staphylococcus aureus", "microrobot", "mortality", "mouse model", "nanomedicine", "nanoparticle", "nanopolymer", "neutrophil", "novel therapeutics", "particle", "pathogen", "patient population", "pulmonary", "success", "trend", "ventilator-associated pneumonia" ], "approved": true } }, { "type": "Grant", "id": "15972", "attributes": { "award_id": "1R01AI195981-01", "title": "Understanding programmed ribosomal frameshifting in coronaviruses", "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": 32891, "first_name": "MARY KATHERINE BRADFORD", "last_name": "PLIMACK", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-02-19", "end_date": "2031-01-31", "award_amount": 414029, "principal_investigator": { "id": 44426, "first_name": "Victoria Manuel", "last_name": "D'Souza", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3425, "ror": "", "name": "HARVARD UNIVERSITY", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "Coronaviruses (CoV) are associated with severe diseases as demonstrated by the 2003 severe acute respiratory syndrome (SARS)-CoV1 epidemic and the SARS-CoV2 pandemic. One of the critical steps of infection involves viral mRNA mediated recoding of gene expression; a -1 frameshifting event that occurs during translation. It is this elegant mechanism that allows the ribosome to bypass a stop codon and synthesize viral enzymatic proteins. Furthermore, the frequency by which this event occurs is important for efficient viral infectivity and is regulated by domains in the translating mRNA (in the case of the SARS-CoV, this domain is a pseudoknot). Although structural studies of frameshifting have received considerable aOention and various structures have been proposed and solved, information on exactly which structure causes the frameshifting is lacking. Our preliminary studies indicate that CoV gene expression is regulated by a dynamic, proton-driven equilibrium between an active, and two inactive pseudoknot conformations that allows for strict control over the protein ratios. This proposal aims to gain a complete structural and mechanistic understanding of the frameshifting frequency in CoV by combining structural studies with biochemical and in vivo experiments. Our aims will be: (#1) to understand the basis for how the frameshifting frequency is maintained by engineering structure-guided mutants to test our equilibrium model, (#2) to determine the structures of the pseudoknot signal in both configurations: permissive and nonpermissive for frameshifting, and (#3) to determine the structure of ribosomes as they encounter the permissive conformation of the pseudoknot.", "keywords": [ "2019-nCoV", "Anti-viral Agents", "Biochemical", "Bypass", "COVID-19 pandemic", "Cell Line", "Characteristics", "Chemicals", "Code", "Complex", "Coronavirus", "Cryoelectron Microscopy", "Data", "Development", "Disease", "Engineering", "Equilibrium", "Event", "Frequencies", "Gene Expression", "Genetic", "In Vitro", "Infection", "Mediating", "Messenger RNA", "Molecular Conformation", "Mutation", "Nuclear Magnetic Resonance", "Nucleotides", "Outcome", "Population", "Preparation", "Process", "Proteins", "Protocols documentation", "Protons", "RNA", "Reading Frames", "Respiratory Disease", "Ribosomal Frameshifting", "Ribosomes", "SARS coronavirus", "Sampling", "Signal Transduction", "Structure", "Terminator Codon", "Testing", "Translating", "Translations", "Viral", "Virus", "Virus Replication", "conformer", "drug discovery", "equilibrium model", "experimental study", "in vivo", "insight", "live cell imaging", "mutant", "pandemic disease", "permissiveness", "protonation", "ribosome profiling", "sensor", "translation assay" ], "approved": true } }, { "type": "Grant", "id": "15978", "attributes": { "award_id": "1R01AI196176-01", "title": "Inhibiting Chikungunya Virus Protease using MTase-like Domain Interactions for Novel Antiviral Therapies.", "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": 32808, "first_name": "MINDY I", "last_name": "DAVIS", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-02-23", "end_date": "2031-01-31", "award_amount": 632994, "principal_investigator": { "id": 44433, "first_name": "Jeanne Ann", "last_name": "Hardy", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3429, "ror": "", "name": "UNIVERSITY OF MASSACHUSETTS AMHERST", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "Chikungunya (CHIKV) is an RNA alphavirus that infects 3 million people in 45 countries including the US annually. Acute infection is flu-like, but in 40% of infections, debilitating joint pain emerges that can last for years. Infection during pregnancy also results in severe encephalopathy in newborns or aborted fetuses. Viral proteases are effective antiviral drug targets and are the standard of care for viral diseases (e.g HIV, hepatitis C, SARS-CoV- 2). The activity of the nsP2 protease from CHIKV (CHIKVP) is vital for infection. Inhibition of CHIKVP blocks processing of the viral polyprotein, prevents viral replication, lowers viral titers and stops disease progression. Thus, CHIKVP is an excellent antiviral drug target. To date, no effective antivirals of CHIKVP have been approved for acute or chronic infection. Our ultimate goal is to use insights into CHIKVP structure and dynamics to develop an inhibitor to oppose CHIKV infection, the resulting chronic pain and prevent pediatric neurological syndromes. CHIKVP is composed of a protease domain and a methyltransferase-like domain (MTL). To date, no functions of the MTL have been identified. In a search for novel CHIKVP binders, we identified ligands that bind to the MTL at an elongated cavity and allosterically inactivate the protease. The site shares structural homology with S-adenosyl methionine (SAM) cofactor binding sites, but does not bind SAM. The allosteric site binds to GTP, which suggests that a function such as RNA binding may be conserved in the MTL. Here we propose a research strategy for the development and direct comparison of CHIKVP active-site and allosteric inhibitors. We will build compounds derived from a large compound screen and also build from MTL-binding fragments we have already identified. We have developed NMR approaches that allow us to readily distinguish active-site from allosteric inhibitors. Importantly, we have developed approaches that allow us to monitor activity, binding and dynamics in solution without having to rely on freezing samples which is required for other structural techniques, to inform our inhibitor design. Recent data have suggested that RNA plays a critical role in CHIKVP function, enhancing protease activity. We have identified a site that we hypothesize binds RNA and describe a series of studies to understand the mechanism by which RNA impacts protease function. We will bring all these structural insights into our inhibitor development approach. At each step of development, we will closely monitor efficacy against viral infection for CHIKV and other related alphaviruses to determine whether pan-alphaviral inhibition is achievable with a given class of compounds. Critically, we will also implement a directed evolution approach across both domains of CHIKVP to predict the susceptibility of our inhibitors to resistance mutations. This will enable us to develop enduring antivirals and will also address longstanding unanswered questions about the favorability of allosteric inhibition in antiviral drug development.", "keywords": [ "2019-nCoV", "Aborted Fetus", "Active Sites", "Address", "Adult", "Allosteric Site", "Alpha Virus", "Anti-viral Agents", "Anti-viral Therapy", "Arthralgia", "Back", "Binding", "Binding Sites", "Characteristics", "Chikungunya virus", "Child", "Childhood", "Clinical", "Country", "Data", "Development", "Directed Molecular Evolution", "Disease", "Disease Progression", "Drug Targeting", "Drug resistance", "Encephalopathies", "FDA approved", "Family", "Fluorogenic Substrate", "Freezing", "Future", "Goals", "Guanosine Triphosphate", "HIV", "HIV Care", "Hepatitis C", "Hepatitis C virus", "Infection", "Inflammation", "Intervention", "Late pregnancy", "Ligand Binding", "Light", "Mediating", "Methyltransferase", "Molecular", "Monitor", "Motion", "Myalgia", "Nervous System Disorder", "Neurologic", "Newborn Infant", "Peptide Hydrolases", "Persons", "Pharmaceutical Chemistry", "Play", "Polyproteins", "Predisposition", "Pregnancy", "Pregnant Women", "Property", "Protease Domain", "Protease Inhibitor", "RNA", "RNA Binding", "Reporting", "Research", "Role", "S-Adenosylhomocysteine", "S-Adenosylmethionine", "SARS-CoV-2 infection", "Sampling", "Series", "Site", "Structure", "Syndrome", "Techniques", "Testing", "Time", "Vaccination", "Vaccines", "Viral", "Virus Diseases", "Virus Inhibitors", "Virus Replication", "acute infection", "antiviral drug development", "chikungunya infection", "chronic infection", "chronic pain", "cofactor", "design", "drug resistance development", "emerging pathogen", "enzyme mechanism", "flu", "high throughput screening", "inhibitor", "insight", "mosquito-borne", "novel", "pain symptom", "pandemic potential", "pandemic virus", "pharmacologic", "prevent", "resistance mutation", "screening", "small molecule", "standard of care", "unborn child" ], "approved": true } }, { "type": "Grant", "id": "15982", "attributes": { "award_id": "1R01AI189532-01A1", "title": "Biophysical constraints on antibody affinity maturation to SARS-CoV-2", "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": 32599, "first_name": "MICHELLE MARIE", "last_name": "ARNOLD", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-02-19", "end_date": "2031-01-31", "award_amount": 815762, "principal_investigator": { "id": 44437, "first_name": "Angela Marie", "last_name": "Phillips", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2635, "ror": "", "name": "UNIVERSITY OF CALIFORNIA, SAN FRANCISCO", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The objective of this proposal is to develop a quantitative understanding of how the biophysical properties of antibodies impact their capacity to evolve affinity to divergent SARS-CoV-2 spike variants. Though there is substantial evidence that mutations acquired during affinity maturation impact antibody expression, affinity for distinct viral variants, and self-reactivity, we lack a quantitative understanding of (1) how mutations impact these biophysical properties and (2) how these properties, and trade-offs between them, collectively determine the fate of the corresponding B-cell lineage. Here, we propose three Aims to test our hypothesis that mutations differentially impact antibody expression, affinity, and self-reactivity, resulting in biophysical trade-offs that constrain the evolution of antibodies that bind divergent SARS-CoV-2 spike variants. In Aim 1, we quantitate the biophysical effects of mutations in anti-SARS-CoV-2 spike antibodies, using high-throughput mammalian cell- display methods we recently developed. By measuring the expression, affinity, and self-reactivity for millions of anti-spike antibodies, including broadly neutralizing antibodies (bnAbs) that bind divergent spike variants, their evolutionary predecessors, and systematically mutagenized antibody sequences, we will unveil biophysical constraints that shape affinity maturation to rapidly evolving viral antigens. In Aim 2, we evaluate the contributions of antibody biophysical properties to B-cell fitness, or proliferation, using longitudinally-sampled patient B-cells following exposure to divergent strains of SARS-CoV-2. This approach will reveal the relative importance of distinct antibody biophysical properties in driving B-cell evolutionary dynamics in human repertoires and enable development of quantitative models for predicting the outcomes of affinity maturation. In Aim 3, we define the impact of selection pressure during affinity maturation on the biophysical properties of the resulting antibodies, focusing on selection regimes known to favor the maturation of bnAbs that bind distinct spike variants. To this end, we leverage a B-cell directed evolution platform that mimics the mutagenic load of somatic hypermutation, enables fine-tuning of the antibody selection conditions, and supports longitudinal B-cell sampling to profile the evolutionary dynamics of the B-cell response and the biophysical properties of the corresponding antibody lineages. The resulting data will be used to define the impact of the selection regime on the biophysical determinants of B-cell fitness. Successful completion of these Aims will yield quantitative insight into (1) how antibody biophysical properties change during affinity maturation, (2) how they collectively determine B-cell fate in human repertoires, and (3) how their relative importance varies across distinct selection regimes. Thus, this work will advance our fundamental understanding of the biophysical mechanisms that shape antibody affinity maturation to rapidly evolving pathogens like SARS-CoV-2, supporting efforts to design and elicit antibodies that bind existing and novel viral variants.", "keywords": [ "2019-nCoV", "Affinity", "Antibodies", "Antibody Affinity", "Antibody Repertoire", "Antigens", "Autoantibodies", "Automobile Driving", "B-Cell Antigen Receptor", "B-Lymphocytes", "Binding", "Biophysical Process", "Biophysics", "Cell Lineage", "Cell membrane", "Cell surface", "Data", "Development", "Directed Molecular Evolution", "Engineering", "Epitopes", "Evolution", "Exposure to", "Frequencies", "Future", "Goals", "Human", "Immunoglobulin Somatic Hypermutation", "Knowledge", "Mammalian Cell", "Measures", "Membrane", "Methods", "Modeling", "Molecular", "Mutagens", "Mutation", "Outcome", "Patients", "Population", "Process", "Proliferating", "Property", "Protein Engineering", "Proteins", "Regimen", "Relaxation", "Research", "SARS-CoV-2 antibody", "SARS-CoV-2 exposure", "SARS-CoV-2 spike protein", "SARS-CoV-2 variant", "Sampling", "Shapes", "Surface", "Testing", "Vaccines", "Variant", "Viral", "Viral Antigens", "Virus", "Work", "adaptive immunity", "antigen binding", "biophysical properties", "design", "efficacy evaluation", "empowerment", "fitness", "improved", "insight", "interest", "neutralizing antibody", "novel", "outcome prediction", "pathogen", "predictive modeling", "pressure", "response", "trafficking", "vaccine development" ], "approved": true } }, { "type": "Grant", "id": "15984", "attributes": { "award_id": "1R01AI195471-01", "title": "Molecular evolution of entry receptor usage underlying zoonotic human betacoronaviruses", "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": 32891, "first_name": "MARY KATHERINE BRADFORD", "last_name": "PLIMACK", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-02-20", "end_date": "2031-01-31", "award_amount": 481520, "principal_investigator": { "id": 7514, "first_name": "Tyler Nelson", "last_name": "Starr", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 757, "ror": "", "name": "FRED HUTCHINSON CANCER RESEARCH CENTER", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 3434, "ror": "", "name": "UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH", "address": "", "city": "", "state": "UT", "zip": "", "country": "United States", "approved": true }, "abstract": "Most human viruses originate from recent zoonotic spillover, but the upstream evolutionary processes in animal reservoirs that drive zoonosis-promoting traits remain poorly understood. Our long-term goal is to elucidate the evolutionary forces enabling animal viruses to acquire traits facilitating human spillover and adaptation, with a focus on viral entry receptor usage as a critical determinant of cross-species transmission. Toward this end, this proposal investigates the evolutionary dynamics underlying changes in receptor-binding specificity in beta-coronaviruses (CoVs) linked to past and potential future zoonoses: SARS-CoV-2, MERS- CoV, and HKU1 alongside their bat, rodent, and other animal relatives. Our central model is that long-term evolutionary arms races between viruses and wildlife hosts drive evolvable mechanisms of receptor- engagement promoting subsequent human spillover and adaptation. This model will be examined through three specific aims: (1) Identify mechanisms driving human receptor binding in bat SARS-related CoVs; (2) Dissect the origins and consequences of receptor-switching in bat MERS-related CoVs; and (3) Identify evolutionary origins of and functional constraints imposed by a newly discovered HKU1 CoV receptor. In each aim, we combine phylogenetic surveys across diverse animal CoVs with high-throughput mutagenesis screens to map the evolutionary, genetic, and structural mechanisms driving receptor-use transitions and their downstream evolutionary consequences. These studies will illuminate how host-virus dynamics shape receptor-binding architectures to enable zoonotic potential and post-spillover antigenic evolution. The resulting large-scale genotype-phenotype maps will inform computational models for assessing viral zoonotic risk and guide the design of broad-spectrum antibody and vaccine therapeutics for pandemic preparedness. Taken together, this work advances understanding of mechanisms of viral evolution while providing actionable insights for proactive ecological, diagnostic, and therapeutic interventions.", "keywords": [ "2019-nCoV", "ACE2", "Animals", "Antibodies", "Architecture", "Automobile Driving", "Binding", "Biological Factors", "Chiroptera", "Communicable Diseases", "Computer Models", "Coronavirus", "Development", "Diagnostic", "Dissection", "Distal", "Epidemic", "Event", "Evolution", "Future", "Genetic", "Genetic Screening", "Genotype", "Glycoproteins", "Goals", "Human", "Immune", "Infection", "Link", "Maps", "Middle East Respiratory Syndrome", "Middle East Respiratory Syndrome Coronavirus", "Modeling", "Molecular", "Molecular Evolution", "Mutagenesis", "Mutation", "Orthologous Gene", "Pathogenicity", "Pathway interactions", "Phenotype", "Phylogenetic Analysis", "Process", "Proteins", "Public Health", "Research", "Risk", "Rodent", "Role", "SARS coronavirus", "Shapes", "Specificity", "Surveys", "TMPRSS2 gene", "Testing", "Therapeutic", "Therapeutic Intervention", "Vaccines", "Viral", "Viral reservoir", "Virus", "Work", "Yeasts", "Zoonoses", "animal coronavirus", "arms race", "betacoronavirus", "biophysical analysis", "coronavirus receptor", "cross-species transmission", "design", "experience", "future pandemic", "human coronavirus", "improved", "insight", "mutation screening", "novel", "pandemic preparedness", "predictive tools", "pressure", "prevent", "receptor", "receptor binding", "respiratory", "tool", "trait", "transmission process", "vaccine development", "viral outbreak", "zoonotic spillover" ], "approved": true } }, { "type": "Grant", "id": "15980", "attributes": { "award_id": "1R01AI189659-01A1", "title": "Durable and broad airway immunity through next-generation intranasal boosters", "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": 32831, "first_name": "JENNIFER L", "last_name": "GORDON", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-02-06", "end_date": "2031-01-31", "award_amount": 662465, "principal_investigator": { "id": 44435, "first_name": "David R.", "last_name": "Martinez", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3431, "ror": "", "name": "YALE UNIVERSITY", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "Intramuscular SARS-CoV-2 mRNA-LNP do not reliably nor durably elicit respiratory mucosal IgA. Moreover, vaccinated individuals who become infected are more durably protected and this is thought to be mediated by respiratory mucosal IgA. Currently, there are no mucosal respiratory vaccines for human use. We identified a mucosal booster vaccine admixed with a mast cell agonist adjuvant, mastoparan-7, and a toll-like receptor 9 agonist adjuvant, CpG, that elicits durable mucosal IgA. Importantly, mice intranasally boosted with a multivalent nanoparticle vaccine adjuvanted with mastoparan-7 and CpG are protected from bat SARS-like virus challenge. We propose to study the mechanism of mast cell and antigen-presenting cell signaling modulated by this novel mucosal adjuvant combination. We will pursue our central objective which is to understand how mucosal IgA is elicited and maintained following respiratory mucosal vaccination with our exciting universal vaccines to ultimately achieve durable and broadly protective immunity against zoonotic coronaviruses. To achieve this objective, we will complete these aims: Aim 1: Test the hypothesis that mast cells and antigen-presenting cells elicit specific cytokines and chemokines that modulate durable IgA. We propose to study the impact of intranasal boost dose and interval on IgA kinetics and durability. We will also define if the mastoparan-7 and CpG adjuvant combination requires mast cell and antigen presenting cells that signal through CpG via the TLR-9 pathway. We will then define gene expression profiles from respiratory tract mast cells and antigen presenting cells that are activated by mastoparan-7 and CpG and modulate durable mucosal IgA responses. Aim 2: Test the hypothesis that M7/CpG nanoparticle vaccine elicits durable IgA secreting cells and IgA memory B cells in the respiratory tract using lineage-tracing, fluorescent reporter mice pre- immune with common-cold CoV. We will determine how intranasal boosting modulates IgA-secreting plasma cells and IgA memory B cells that home back to the respiratory mucosa in SARS-CoV-2 immune mice and in mice immune against common-cold coronaviruses. We will use cre-lox inducible, IgA-secreting cell and IgA memory B cell fluorescent reporter mice to define how intranasal boosting modulates mucosal IgA immunity. We will also test adjuvant and intranasal safety using a human lymph node organoid model from upper- respiratory tract draining lymph tissue from humans. Aim 3: Test the hypothesis that durable mucosal IgA can protect against transmissible SARS-CoV-2 variants in hamster transmission models and protect against SARS-related coronaviruses. We will determine if the mastoparan-7 and CpG adjuvanted nanoparticle intranasal booster reduces transmission of SARS-CoV-2 variants in hamster models. We will also use IgA knockout mice to determine if IgA is required for protection against SARS-like viruses.", "keywords": [ "2019-nCoV", "Adjuvant", "Agonist", "Antigen Targeting", "Antigen-Presenting Cells", "Antigens", "B-Lymphocytes", "Back", "COVID-19 vaccine", "Cell Degranulation", "Cell secretion", "Chiroptera", "Common Cold", "Coronavirus", "Coupled", "Data", "Disease", "Dose", "Ferritin", "Frequencies", "Gene Expression Profile", "Generations", "Genes", "Goals", "Hamsters", "Health", "Home", "Human", "Immune", "Immune response", "Immune signaling", "Immunity", "Immunobiology", "Immunoglobulin A", "Immunologics", "Intramuscular", "Intranasal Administration", "Kinetics", "Knockout Mice", "Knowledge", "Length", "Lineage Tracing", "Lymph", "Mediating", "Memory B-Lymphocyte", "Messenger RNA", "Middle East Respiratory Syndrome Coronavirus", "Modeling", "Monitor", "Mucosal Immunity", "Mucous Membrane", "Mus", "Organoids", "Pathogenicity", "Pathway interactions", "Patients", "Peptides", "Plasma Cells", "RNA vaccine", "Receptor Signaling", "Reporter", "Respiration", "Respiratory Mucosa", "Respiratory System", "SARS coronavirus", "SARS-CoV-2 transmission", "SARS-CoV-2 variant", "Safety", "Severe Acute Respiratory Syndrome", "Signal Transduction", "TLR9 gene", "Tamoxifen", "Testing", "Upper respiratory tract", "Vaccinated", "Vaccination", "Vaccine Adjuvant", "Vaccinee", "Vaccines", "Virus", "Work", "Zoonoses", "antiviral immunity", "booster vaccine", "chemokine", "coronavirus vaccine", "cross immunity", "cytokine", "experimental study", "gene panel", "human tissue", "lipid nanoparticle", "lymph nodes", "mast cell", "mastoparan", "mucosal vaccination", "mucosal vaccine", "nanoparticle", "next generation", "novel", "novel coronavirus", "pandemic disease", "preclinical safety", "respiratory", "respiratory virus", "response", "single-cell RNA sequencing", "tool", "transmission process", "universal vaccine", "vaccine evaluation", "zoonotic coronavirus" ], "approved": true } }, { "type": "Grant", "id": "15954", "attributes": { "award_id": "1R01AG092810-01A1", "title": "The Impact of Changes in Primary Care Clinicians' Work Effort on the Health of Older Adults", "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": 44399, "first_name": "MARCEL", "last_name": "SALIVE", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-04-01", "end_date": "2031-01-31", "award_amount": 680086, "principal_investigator": { "id": 44400, "first_name": "Bruce E.", "last_name": "Landon", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 44401, "first_name": "Lisa", "last_name": "Rotenstein", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2635, "ror": "", "name": "UNIVERSITY OF CALIFORNIA, SAN FRANCISCO", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "There are demonstrated benefits of comprehensive, continuous, and coordinated primary care for older adults, ranging from higher rates of appropriate preventive care receipt to lower rates of hospitalization and mortality. However, the benefits of strong primary care are threatened by an impending primary care workforce crisis, exacerbated by prevalent trends of primary care physician (PCP) workforce attrition and clinical effort reduction. Partly in response to these trends, there is increasing representation of NPs and PAs, collectively referred to as advanced practice clinicians (APCs), in the primary care workforce. However, burnout, intent to leave, and intent to reduce clinical effort are also prevalent among primary care APCs. These trends across primary care clinicians (PCCs; comprising physicians, NPs, and PAs) may significantly threaten quality of and access to care for older adults. At present, there is limited evidence to inform healthcare leaders and policy makers about how primary care workforce disruptions impact access to and quality of primary care received by older adults. There is additionally insufficient information on the actionable factors associated with PCC turnover and PCC reductions in clinical effort. In this grant, we will leverage data from Medicare fee-for-service and Medicare Advantage, which together provide coverage for 93% of older adults, in order to: 1) quantify the number of Medicare patients impacted by PCC turnover and sustained reductions in billed clinical effort and identify factors associated with these work effort changes; 2) assess the impact of PCC turnover and PCCs’ sustained reductions in billed clinical effort on patterns of primary care receipt and non-primary care utilization, including emergency department visits and hospitalizations; and 3) assess the impact of PCC turnover and sustained reductions in billed clinical effort on quality of care for older adults. All analyses will be conducted for the overall population of older adults as well as for subgroups of more vulnerable older adults, including those with dementia, multiple chronic conditions, and from underserved groups (e.g., dually eligible for Medicaid). Additionally, analyses will be conducted for physicians and APCs separately, and for the overall study period and comparing the pre- and post-COVID periods. The results from this study will elucidate how changes in PCCs’ work patterns influence the care of the growing US population of older adults. They will provide actionable insights for leaders seeking to design clinical systems and policies that enhance primary care for older adults. Overall, this proposal will enhance the ability of clinical, operational, and policy leaders to maintain the effort of the primary care workforce and optimize care for older adults.", "keywords": [ "Accident and Emergency department", "Address", "Affect", "COVID-19 pandemic", "Caring", "Clinical", "Complex", "Continuity of Patient Care", "Counseling", "Data", "Dementia", "Documentation", "Educational process of instructing", "Emergency department visit", "Fee-for-Service Plans", "Grant", "Health", "Health Care", "Health Services Accessibility", "Hospitalization", "Investments", "Left", "Location", "Measures", "Medicaid eligibility", "Medical Students", "Medicare", "Modeling", "Occupations", "Older Population", "Outcome", "Patients", "Pattern", "Physicians", "Policies", "Policy Maker", "Preventive care", "Primary Care", "Primary Care Physician", "Process", "Quality of Care", "Reporting", "Specialist", "Subgroup", "System", "Testing", "Time", "Underserved Population", "United States", "Visit", "Work", "acute care", "beneficiary", "burnout", "care delivery", "care providers", "care systems", "care utilization", "cost", "demographics", "design", "dual eligible", "hospitalization rates", "improved outcome", "insight", "large scale data", "mortality", "multiple chronic conditions", "older adult", "post-COVID-19", "primary care clinician", "response", "screening", "social", "trend" ], "approved": true } }, { "type": "Grant", "id": "15971", "attributes": { "award_id": "1R35GM162359-01", "title": "The multifaceted pathways of astrovirus entry and egress", "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": 22244, "first_name": "MICHAEL", "last_name": "SAKALIAN", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-02-24", "end_date": "2030-12-31", "award_amount": 422677, "principal_investigator": { "id": 44425, "first_name": "Valerie", "last_name": "Cortez", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3424, "ror": "", "name": "UNIVERSITY OF CALIFORNIA SANTA CRUZ", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Astroviruses are a major cause of pediatric diarrhea worldwide. Despite causing one of the most common early childhood infections, astroviruses are one of the least studied enteric RNA viruses. We previously discovered that the virus infects small intestinal goblet cells, specialized epithelial cells that secrete mucus. Few studies have investigated viral infection in goblet cells due to the lack of cell-specific models. Because the mechanisms by which viruses replicate inside of goblet cells are completely unknown, my lab is interested in addressing 1) how do astroviruses enter cells with highly dynamic apical membranes? and 2) what role does mucus secretion play in viral egress? We have established new in vitro models and tools to address these questions and have built a strong and collaborative investigative team with complementary expertise that will ensure the success of these projects. To evaluate receptor-mediated and fluid-phase endocytosis entry pathways into goblet cells, we will use a combination of CRISPR-Cas9 engineering, biochemical analysis, and high-resolution microscopy. We will use a similar suite of techniques as well as cryo-electron microscopy to define the egress pathway of astrovirus from goblet cells via mucus secretion. In addition to murine and human astroviruses, other respiratory and enteric viruses have also been shown to target goblet cells for infection. Thus, our work aims to initially provide foundational knowledge on the basic biology of astroviruses before shedding light on key host pathways in goblet cells that are co-opted by viruses from other families, including influenza and SARS-CoV2. Completion of these studies will provide the first major insights into the virus-host interactions at the apical membrane surface of intestinal goblet cells, which will pave the way for the future development of targeted drug treatments for the numerous viruses that target this unique cell population.", "keywords": [ "2019-nCoV", "Address", "Astrovirus", "Biochemical", "Biology", "CRISPR/Cas technology", "Cell model", "Cells", "Childhood", "Cryoelectron Microscopy", "Development", "Diarrhea", "Endocytosis", "Engineering", "Ensure", "Enteral", "Family", "Foundations", "Future", "Goblet Cells", "Human", "Infection", "Influenza", "Intestines", "Knowledge", "Light", "Liquid substance", "Mediating", "Microscopy", "Modeling", "Mucous body substance", "Mucus-Secreting Cell", "Mus", "Pathway interactions", "Phase", "Play", "Population", "Prevention strategy", "RNA Viruses", "Resolution", "Role", "Small Intestinal Goblet Cell", "Specialized Epithelial Cell", "Surface", "Techniques", "Viral", "Virus", "Virus Diseases", "Virus Replication", "Work", "apical membrane", "early childhood", "enteric virus infection", "in vitro Model", "insight", "interest", "novel", "receptor", "respiratory", "success", "targeted treatment", "tool", "treatment strategy", "virus host interaction" ], "approved": true } }, { "type": "Grant", "id": "15961", "attributes": { "award_id": "1R35GM161641-01", "title": "Methods for quantifying selection and predicting evolutionary dynamics", "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": 44409, "first_name": "RONALD", "last_name": "ADKINS", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-03-01", "end_date": "2030-12-31", "award_amount": 417620, "principal_investigator": { "id": 44410, "first_name": "John P", "last_name": "Barton", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3416, "ror": "", "name": "UNIVERSITY OF PITTSBURGH AT PITTSBURGH", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Natural selection is central to many challenges in biology and medicine, from the emergence of drug resistance in pathogens to cancer evolution. Understanding selection can also aid in protein engineering and help identify clinically relevant mutations in human disease genes. Temporal genetic data — sequences and phenotypes sampled over time — can be an especially powerful tool for understanding selection because it allows us to observe evolutionary dynamics directly. But while temporal data from sources like pathogen surveillance, ancient DNA, and experimental evolution have grown tremendously in recent years, statistical analyses of these data remain challenging. My lab will continue to pioneer the development of new computational methods to learn from temporal genetic data, revealing variants and phenotypes under selection and harnessing this information for predictive models of evolution. Over the past five years, we have developed several approaches to quantify selection from temporal data. Thanks to the use of mathematical methods from statistical physics, our methods are fast and accurate despite the inclusion of complex features such as linkage disequilibrium, epistasis, and time-varying selection. We demonstrated the power of these approaches through studies of HIV-1 immune escape and SARS-CoV-2 adaptation during the COVID-19 pandemic, where our analysis identified key mutations affecting viral transmission even before their importance was validated experimentally. Building on this foundation, we will pursue three synergistic research directions: First, we will develop new methods to jointly analyze selection on both individual mutations and phenotypic traits, fusing concepts from population genetics, quantitative genetics, and machine learning. Second, we will apply these methods to study rapid evolution in viral pathogens. Phenotypic models will help us to understand how immune pressure drives antigenic change in respiratory viruses and to compare evolutionary constraints on pathogens across host species. As an ambitious new direction, we will leverage these insights to develop predictive models of pathogen evolution, with influenza as a first target. Our research will systematically identify the features with the greatest power to predict evolution and characterize how and why predictive power may decline over time. Finally, we will extend our approaches to improve the interpretation of high-throughput mutagenesis experiments that measure the effects of thousands of mutations simultaneously. The proposed research will transform our understanding of how selection guides evolution across biological scales, from individual mutations to complex phenotypes, with applications ranging from predicting viral evolution to protein engineering. These advances could ultimately improve our ability to anticipate and control evolutionary processes across a wide range of biological contexts.", "keywords": [ "2019-nCoV", "Affect", "Biological", "Biology", "COVID-19 pandemic", "Complex", "Computing Methodologies", "DNA", "Data", "Data Sources", "Development", "Drug resistance", "Evolution", "Foundations", "Genes", "Genetic", "Genetic Epistasis", "Genotype", "HIV-1", "Immune", "Immunity", "Individual", "Influenza", "Learning", "Linkage Disequilibrium", "Machine Learning", "Malignant Neoplasms", "Maps", "Measures", "Medicine", "Methods", "Modeling", "Mutagenesis", "Mutation", "Natural Selections", "Phenotype", "Physics", "Play", "Population Genetics", "Process", "Protein Engineering", "Public Health", "Quantitative Genetics", "Research", "Resistance development", "Role", "Sampling", "Shapes", "Statistical Data Interpretation", "Statistical Methods", "Time", "Variant", "Viral", "clinically relevant", "experimental study", "genetic variant", "human disease", "improved", "insight", "mathematical methods", "pathogen", "pathogenic virus", "predictive modeling", "pressure", "respiratory virus", "tool", "trait", "viral transmission" ], "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 } } ], "meta": { "pagination": { "page": 3, "pages": 1424, "count": 14236 } } }