Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=4&sort=-id
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-id", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=-id", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=5&sort=-id", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=-id" }, "data": [ { "type": "Grant", "id": "15965", "attributes": { "award_id": "1P50DC022549-01A1", "title": "Sensory and molecular studies of human taste dysfunction", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute on Deafness and Other Communication Disorders (NIDCD)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2026-03-01", "end_date": "2031-02-28", "award_amount": 786679, "principal_investigator": { "id": 44417, "first_name": "PeiHua", "last_name": "Jiang", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3419, "ror": "", "name": "MONELL CHEMICAL SENSES CENTER", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Project 3. Sensory and molecular studies of human taste dysfunction Taste dysfunction is a cardinal feature of COVID. Project 3 of this P50 Clinical Research Center (CRC) proposal focuses on (1) molecular description of taste tissue from people with sustained COVID-19-associated taste dysfunction, compared to people with no current taste problems (regardless of infection history) (Aim 3.1), and (2) mechanistic interrogation of COVID-associated taste dysfunction using taste organoids (Aim 3.2). We will test the hypothesis that people with COVID taste dysfunction have fewer taste receptor cells, reduced expression of taste-relevant genes, and immune cell infiltration due to sustained inflammation. In Aim 3.1, we will sample taste tissue from people with and without sustained COVID-19-associated taste dysfunction to measure taste receptor cell number and gene expression of inflammatory (e.g., cytokines and chemokines) and other molecules with single-cell RNA sequencing (scRNA-seq) methods. In Aim 3.2, we will use taste organoids derived from wild-type mice, humanized-ACE2 mice, and humans to examine SARS-CoV-2 tropism in taste tissue to determine if taste tissue homeostasis is altered by (a) SARS-CoV-2 infection or (b) inflammatory molecules identified in Aim 3.1 and/or known to be elevated in COVID. Project 3 of this CRC proposal is supported by Project 1 and the Chemosensory Clinical Services Core, which will perform and support remote and in-house sensory screening of all participants in this research program. The investigators here are experts in their fields, particularly in single-cell biology, genetics, and stem cell biology of taste tissue. We have engaged consultants who are inflammation, infection, and immunology experts. Several types of pilot data support this application, including scRNA-seq data from human fungiform tissue and taste organoid data after treatment with inflammatory molecules. Institutional support for this project is outlined in a Letter of Support from administrative officials, and the Monell Chemical Senses Center is well suited to complete this project because of its cross-disciplinary focus on chemosensory biology and its connection with an experienced coronavirus expert at the nearby University of Pennsylvania. This project is part of a larger program to understand and treat people with communication disorders of taste and smell dysfunction due to COVID. We anticipate our data will answer key unsolved questions regarding taste dysfunction and point to potential avenues of treatment for this debilitating condition.", "keywords": [ "2019-nCoV", "3-Dimensional", "ACE2", "Acute", "Address", "Affect", "Aftercare", "Age", "Ageusia", "Biological Models", "Biology", "COVID-19", "COVID-19 patient", "COVID-19 susceptibility", "Cell Count", "Cell Physiology", "Cell secretion", "Cells", "Cellular Structures", "Cellular biology", "Chemicals", "Clinical Research", "Clinical Services", "Communication impairment", "Coronavirus", "Data", "Desire for food", "Functional disorder", "Fungiform Papilla", "Gene Expression", "Gene Expression Profile", "Genes", "Genetic", "Health", "Homeostasis", "Human", "Immune", "Immunology", "Individual", "Infection", "Inflammation", "Inflammatory", "Institution", "Knock-in", "Knowledge", "Letters", "Long COVID", "Measures", "Methods", "Modeling", "Molecular", "Mucous body substance", "Mus", "Nose", "Organoids", "Participant", "Patients", "Pennsylvania", "Persons", "Phase", "Predisposition", "Psychophysics", "Race", "Receptor Cell", "Recording of previous events", "Research", "Research Personnel", "Resources", "SARS-CoV-2 infection", "SARS-CoV-2 variant", "Saliva", "Salivary", "Sampling", "Sensory", "Signal Transduction", "Smell Perception", "Symptoms", "System", "Taste Buds", "Taste Disorders", "Taste Perception", "Testing", "Tissues", "Tropism", "United States National Institutes of Health", "Universities", "Viral", "Virus", "Virus Diseases", "Wild Type Mouse", "acute COVID-19", "biobank", "cell regeneration", "cell type", "chemokine", "cytokine", "experience", "human RNA sequencing", "human data", "humanized mouse", "immune cell infiltrate", "immunocytochemistry", "inflammatory marker", "novel therapeutic intervention", "programs", "response", "screening", "sex", "single-cell RNA sequencing", "stem cell biology", "stem cells", "synergism", "tongue papilla", "tool" ], "approved": true } }, { "type": "Grant", "id": "15964", "attributes": { "award_id": "1F31HL176102-01A1", "title": "The Pathogenic Role of IL-33 in the SARS-CoV-2-Infected Lung", "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": 32818, "first_name": "MARISOL", "last_name": "ESPINOZA-PINTUCCI", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-03-01", "end_date": "2028-02-28", "award_amount": 38922, "principal_investigator": { "id": 44416, "first_name": "Claire", "last_name": "Fleming", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3391, "ror": "", "name": "UNIVERSITY OF VIRGINIA", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), remains a significant threat to global public health. Pulmonary immunopathological damage plays a role in driving pneumonia, acute respiratory distress syndrome (ARDS), and multiorgan failure in severe COVID-19. Therefore, dissecting the pulmonary immune response to SARS-CoV-2 infection is critical to under- stand disease pathogenesis and develop more effective therapeutics. Targeting of type 2 immune pathways is a potential avenue of therapeutic intervention in severe COVID-19. In particular, research has demonstrated a link between the type 2 cytokine IL-13 and COVID-19 severity. This proposal builds on the preliminary experi- ments demonstrating that blockade of the alarmin cytokine IL-33 confers protection in a mouse model of COVID- 19. IL-33 is a potent inducer of type 2 immunity in the lung, as its receptor ST2 is constitutively expressed by type 2 cells including type 2 innate lymphoid cells (ILC2s). It is hypothesized that IL-33/ST2 signaling induces a pathogenic inflammatory environment in the acutely infected lung by activating IL-13-secreting ILC2s and that IL-33-mediated inflammation enhances disruption of the respiratory epithelial barrier. To test this hypothesis, the impact of IL-33/ST2 signaling axis blockade on the inflammatory environment in the acutely infected lung will be described through assessment of the immune cell populations and the transcriptional profile of the respiratory epithelium (Aim 1). Considering that SARS-CoV-2-mediated ARDS is characterized by pulmonary inflammation and respiratory epithelial barrier disruption, these descriptive studies will elucidate pathways through which IL- 33 may drive pathogenesis. Further, the mechanism through which the IL-33/ST2 signaling axis drives patho- genesis will be directly tested (Aim 2). Mouse models of ILC2 depletion, selective ST2 knockout in ILC2s, and adoptive ILC2 transfer will be used to test whether IL-33-activated ILC2s drive pulmonary pathogenesis in the context of acute SARS-CoV-2 infection. Collectively, the proposed experiments will determine the mechanism underlying IL-33-mediated pathogenesis. This research is significant because it will further our understanding of how modulation of type 2 immunity can serve as a novel and promising therapeutic strategy in the treatment of respiratory viral infection-induced pulmonary pathology.", "keywords": [ "2019-nCoV", "Acute", "Acute Respiratory Distress Syndrome", "Adoptive Transfer", "Adrenal Cortex Hormones", "Affect", "Alveolar Macrophages", "Anti-Inflammatory Agents", "Automobile Driving", "COVID-19", "COVID-19 severity", "Cell Death", "Cells", "Cessation of life", "Clinical Trials", "Diphtheria Toxin", "Disease", "Epithelial Cells", "Epithelium", "Fibroblasts", "Flow Cytometry", "Gene Expression Profile", "Genetic Transcription", "Goals", "Helminths", "Hospital Mortality", "Human", "IL-6 inhibitor", "Immune", "Immune response", "Immunity", "Immunomodulators", "Individual", "Infection", "Inflammation", "Inflammatory", "Interleukin-13", "Interruption", "Intervention Studies", "Knock-out", "Knowledge", "Link", "LoxP-flanked allele", "Lung", "Lung immune response", "Lymphoid Cell", "Mediating", "Modeling", "Multiple Organ Failure", "Mus", "Neurons", "Pathogenesis", "Pathogenicity", "Pathway interactions", "Patients", "Plasma", "Play", "Pneumonia", "Population", "Probability", "Production", "Public Health", "Pulmonary Inflammation", "Pulmonary Pathology", "Pulmonary function tests", "Regenerative pathway", "Research", "Role", "SARS-CoV-2 infection", "Severity of illness", "Signal Induction", "Signal Transduction", "Testing", "Therapeutic", "Therapeutic Intervention", "Viral Respiratory Tract Infection", "Wild Type Mouse", "acute COVID-19", "airway epithelium", "cell type", "cytokine", "experimental study", "follow-up", "improved", "inflammatory milieu", "information gathering", "inhibitor", "mast cell", "mouse model", "new therapeutic target", "novel", "pharmacologic", "post SARS-CoV-2 infection", "pulmonary", "receptor", "reconstitution", "secondary endpoint", "severe COVID-19", "spatial transcriptomics", "success", "systemic inflammatory response", "therapeutic development", "therapeutically effective", "ventilation" ], "approved": true } }, { "type": "Grant", "id": "15963", "attributes": { "award_id": "1R01AG083894-01A1", "title": "Longitudinal MRI Measures of Cerebrovascular Injury and AD Atrophy in a Study of Latinos (SOL-INCA-MRI Long)", "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": 44413, "first_name": "MARYAM X", "last_name": "GHALEH", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-03-15", "end_date": "2030-11-30", "award_amount": 3517625, "principal_investigator": { "id": 44414, "first_name": "Charles", "last_name": "DeCarli", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 44415, "first_name": "Hector M", "last_name": "Gonzalez", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 3418, "ror": "", "name": "UNIVERSITY OF CALIFORNIA AT DAVIS", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Latinos constitute a heterogeneous population which accounted for slightly more than 50% of the United States (US) population growth for 2010 to 2020. Latinos are also becoming a larger proportion of older individuals in the US. Despite this, biomarker studies of normal aging and cognitive impairment remain limited, and the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) constitutes the only known representative sample. Moreover, epidemiological data indicate that Latinos have a higher prevalence of vascular risk factors, lower cardiovascular health metrics, and a greater likelihood of having mild cognitive impairment (MCI) or dementia due non-Alzheimer’s disease processes that differ by heritage. Consequently, diagnosis and treatment of Latino persons with cognitive impairment may be more challenging, but more amenable to prevention through reduction of vascular risk factors than non-Hispanic White persons where vascular risk and disease is less prevalent. The first cycle of “MRI Measures of Cerebrovascular Injury and Alzheimer’s disease Atrophy in a Study of Latinos (RF1 AG054548; AKA SOL-INCA-MRI)” was designed to identify biological underpinnings of normal cognitive aging, MCI and Alzheimer’s disease and related dementias (ADRD) in a representative subgroup of the HCHS/SOL 62 + 9 years of age on average. Despite restrictions imposed by the COVID pandemic, our investigators successfully obtained brain MRI from 2668 individuals or >95% of the proposed study cohort. From these data we have published on 1) differences in brain structure from ages 35-85; 2) the impact of vascular risk and sleep on brain structure; 4) the association of cognition with subsequent MRI measures; and 4) genetic influences on select brain measures. These early results, while of scientific value, are cross- sectional and do not reflect ongoing degeneration or incident vascular injury, limiting inferential power that might extend scientific knowledge of brain aging and ADRD in this unique cohort. For this application, we propose to extend our work to include longitudinal MRI analysis, leveraging longitudinal biomarker and clinical data from 3 visits, spanning approximately 12 years of HCHS/SOL and its cognitive ancillary study (SOL-INCA- AD; R01 AG075758, Gonzalez, DeCarli Co-PIs) on a deeply characterized and diverse Hispanic/Latino cohort. Adding longitudinal image analysis in combination with longitudinal lifestyle, medical risk factors, plasma ATN biomarkers, genetics and cognitive assessment in this Latino cohort will address multiple ADRD research milestones and priorities while enabling stronger statistical inference of risk and resilience factors amongst representative, yet relatively young-old members of diverse Latino communities, creating the opportunity to identify modifiable risk factors, potentially reducing societal burden due to later-life ADRD in this rapidly growing portion of the older US population.", "keywords": [ "9 year old", "Age", "Aging", "Alzheimer's Disease", "Alzheimer's disease related dementia", "Amyloid beta-Protein", "Ancillary Study", "Atrophic", "Biological", "Biological Markers", "Blood Vessels", "Brain", "Brain Injuries", "COVID-19 pandemic", "Cerebrovascular Trauma", "Clinical Data", "Cognition", "Cognitive", "Cognitive aging", "Communities", "Data", "Dementia", "Diagnosis", "Disease", "Funding", "Genetic", "Genetic Risk", "Growth", "Hemorrhage", "High Prevalence", "Hispanic", "Hispanic Community Health Study/Study of Latinos", "Image Analysis", "Impaired cognition", "Individual", "Infarction", "Intercept", "K-Series Research Career Programs", "Knowledge", "Latino", "Latino Population", "Life", "Life Style", "Magnetic Resonance Imaging", "Measures", "Mediating", "Medical", "Nerve Degeneration", "Not Hispanic or Latino", "Older Population", "Participant", "Pathologic", "Persons", "Plasma", "Population", "Population Growth", "Population Heterogeneity", "Prevention", "Process", "Publishing", "Research", "Research Personnel", "Risk", "Risk Factors", "Sampling", "Sleep", "Structure", "Study of Latinos", "Subgroup", "Time", "United States", "United States National Institutes of Health", "Vascular Diseases", "Visit", "Water", "White Matter Hyperintensity", "Work", "aging brain", "brain magnetic resonance imaging", "cardiovascular health", "cerebral microbleeds", "cognitive performance", "cognitive testing", "cohort", "cohort research", "design", "disparity reduction", "endophenotype", "epidemiologic data", "gray matter", "magnetic resonance imaging biomarker", "member", "mild cognitive impairment", "modifiable risk", "morphometry", "normal aging", "resilience factor", "serial imaging", "social culture", "sociocultural determinant", "tau-1", "vascular injury", "vascular risk factor", "white matter" ], "approved": true } }, { "type": "Grant", "id": "15962", "attributes": { "award_id": "1R35GM162151-01", "title": "Correlated factor models for exploratory analysis of complex multimodal study designs", "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": 44411, "first_name": "PEGGY", "last_name": "WANG", "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": 406250, "principal_investigator": { "id": 44412, "first_name": "Brielin", "last_name": "Brown", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3417, "ror": "", "name": "UNIVERSITY OF PENNSYLVANIA", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Most human diseases are complex, manifesting from an interplay between genes and environment over the lifespan that involve myriad biological processes. Genome-wide association studies have primarily implicated non-coding variation that is thought to lead to disease via disruption of complex, multi-level biological systems. Thus, improvements in our understanding of these fundamental processes underlying disease necessitates studying the relationship between multiple omics (multi-omic) modalities, both longitudinally and in conjunction with non-omic data. While recent years have seen an explosion of studies collecting multi-omic data in human populations, analysis of these data remains challenging both statistically and computationally. Here, I propose several new methods based on correlated latent factor models that will extend the capabilities of multi-omic inference methods to more complex study designs. I will develop model-based imputation methods that allow robust handling of missing data, enabling larger-scale studies of multi-omic biological contexts, and allowing researchers to design targeted multi-omic panels to extract the maximum amount of clinically-relevant information. I will develop multi-omic analysis methods that integrate across tissues and time points, enabling the study of dynamic molecular process and detection of systems-level impacts of intervention or disease onset. Finally, I will develop integration methods based on non-linear representation learning. This will enable detection of complex relationships between omics methods and integration with structured non-omics data such as doctor’s notes and radiographic images. To demonstrate the broad utility of the proposed methods, I will conduct collaborative analyses of varied cohorts. These include a population of individuals with subclinical atherosclerosis (MESA), a study anlyzing the relationship between microbiome features and immune health in the context of the COVID-19 pandemic (ImmunoMicrobiome), and a study of the impact of Alzheimer’s disease on neuroimaging and spinal uid biomarkers (ADNI). Completion of this research program will provide new insights into the fundamental biological processes underlying a host of common conditions, while bootstrapping the larger multi-omics research community by providing new tools that can handle complex study designs and integration tasks.", "keywords": [ "Alzheimer's Disease", "Atherosclerosis", "Biological", "Biological Markers", "Biological Process", "COVID-19 pandemic", "Communities", "Complex", "Computing Methodologies", "Data", "Data Analyses", "Detection", "Disease", "Environment", "Etiology", "Explosion", "Genes", "Human", "Image", "Individual", "Intervention", "Learning", "Machine Learning", "Methods", "Modality", "Modeling", "Multiomic Data", "Onset of illness", "Population", "Process", "Research", "Research Design", "Research Personnel", "Spinal", "Structure", "Time", "Tissues", "Untranslated RNA", "Variant", "biological systems", "clinically relevant", "cohort", "data imputation", "design", "detection platform", "genome wide association study", "human disease", "immune health", "improved", "insight", "life span", "microbiome", "molecular dynamics", "multimodality", "multiple omics", "neuroimaging", "novel", "programs", "radiological imaging", "statistics", "tool" ], "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": "15960", "attributes": { "award_id": "2R25NS117281-06", "title": "Training in Advanced Statistical Methods in Neuroimaging and Genetics", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Neurological Disorders and Stroke (NINDS)" ], "program_reference_codes": [], "program_officials": [ { "id": 44407, "first_name": "LETITIA ALEXIS", "last_name": "WEIGAND", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-04-01", "end_date": "2031-03-31", "award_amount": 261311, "principal_investigator": { "id": 44408, "first_name": "ROBERT C.", "last_name": "WELSH", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3415, "ror": "", "name": "UNIVERSITY OF CALIFORNIA LOS ANGELES", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "This education project is a continuation of our current, national class, Training in Advanced Statistical Methods in Neuroimaging and Genetics. Over the past 15 year the National Institutes of Health has greatly increased funding of grants that utilized advanced neuroimaging methods, genetic methods, and advanced statistical methods. While introductory courses are offered, ours is the only advanced course offered in the United States that provides an intensive, hands-on (“doing”) learning opportunity to better prepare biomedical and clinical researchers in advanced statistical methods. In one decade the combined budgets that utilize these advanced analysis techniques from the National Institute of Neurological Disorders and Stroke, National Institute of Mental Health, National Institute on Aging, National Institute on Drug Abuse, and National Institute of Biomedical Imaging and Bioengineering grew 5-fold, and there continues to be a great need to provide an educational opportunity to ensure the workforce is well positioned to carry out important work that has been identified by these and other institutes. Our program will continue to meet this need. We bring together a group of diverse world-class scientists and educators in a two-week intensive format to provide theoretical lectures paired with hands-on computer tutorials. Our course has served 103 students (55 total in 2021-2022 via Zoom due to COVID-19), and in 2023 (our 1st year of in-person) we taught 20 students, and 28 students in 2024 (in-person). We will enroll 26-30 students in April 2025 session. In our competitive renewal we will continue to enroll 26-30 students per year. With this being an advanced course, we ensure that the students accepted are a good education-level match for the content. We also implement mechanisms to maximize diverse perspective in our students and our teaching faculty. These students are accepted from across the United States, with attention to attracting a diverse student cohort. This education program will continue to distribute Tuition Awards based on financial need. We have evolved our course based on feedback from our current course alumni. In our class, over two weeks, students learn and put into practice methods such as: hierarchical statistical models, Bayesian statistics, network science, functional and structural connectomics, disease driven degeneration of the brain, and methods for analysis of genetics data such as polygenic risk scoring and structural equation modeling. The course concludes with lectures and labs on multi-modal analysis (imaging and imaging-genetics), and classification methods for biomarker development. Our course now includes 5 guest lecturers and team building activities outside of the classroom. To ensure students apply the acquired knowledge and skills to their independent research projects back at their home institutes, we supplement the course with our innovative continuing education: zoom-based sessions with the faculty for 8-months post formal course and students having near-real-time access regarding technical implementation questions through the Slack. This continued education portion greatly increases success utilizing their new practical skills in their own research.", "keywords": [ "Address", "Attention", "Award", "Back", "Bayesian Analysis", "Behavioral Research", "Biomedical Research", "Brain", "Budgets", "COVID-19", "Classification", "Clinical", "Clinical Research", "Communities", "Computers", "Continuing Education", "Course Content", "Data", "Disease", "Education", "Education Projects", "Educational Curriculum", "Educational Status", "Educational process of instructing", "Effectiveness", "Electronic Mail", "Enrollment", "Ensure", "Equation", "Evolution", "Faculty", "Feedback", "Funding", "Genetic", "Grant", "Home", "Image", "Institution", "Instruction", "Internet", "Knowledge", "Knowledge acquisition", "Learning", "Link", "Manuscripts", "Measures", "Methods", "Mission", "Modeling", "Monitor", "National Institute of Biomedical Imaging and Bioengineering", "National Institute of Drug Abuse", "National Institute of Mental Health", "National Institute of Neurological Disorders and Stroke", "National Institute on Aging", "Output", "Persons", "Positioning Attribute", "Postdoctoral Fellow", "Preparation", "Productivity", "Publishing Peer Reviews", "Qualifying", "Reporting", "Reproducibility", "Research", "Research Ethics", "Research Personnel", "Research Project Grants", "Resources", "Scholarship", "Science", "Scientist", "Secure", "Statistical Data Interpretation", "Statistical Methods", "Statistical Models", "Structure", "Students", "Study Section", "Techniques", "Time", "Training", "United States", "United States National Institutes of Health", "Universities", "Utah", "Work", "YouTube", "biomarker development", "career", "cohort", "data mining", "educational atmosphere", "equity diversity and inclusion", "follow-up", "genetic analysis", "graduate student", "imaging genetics", "implementation questions", "innovation", "instructor", "lecturer", "lectures", "meetings", "multimodal data", "multimodality", "neuroimaging", "polygenic risk score", "predictive modeling", "programs", "response", "skills", "success", "symposium", "undergraduate student" ], "approved": true } }, { "type": "Grant", "id": "15959", "attributes": { "award_id": "1R21AI196878-01", "title": "A Microfluidic-Free Droplet Technology for Rapid and Quantitative Airborne Pathogen Monitoring", "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": 32597, "first_name": "BROOKE ALLISON", "last_name": "BOZICK", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-04-01", "end_date": "2028-03-31", "award_amount": 451000, "principal_investigator": { "id": 44406, "first_name": "Daniel", "last_name": "Weisgerber", "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": "Pathogen transmission via indirect routes such as fomite, waterborne, and airborne transmission are hallmarks of both endemic and pandemic spread. Viruses such as Influenza, SARS-CoV-2, and measles are notable examples, in addition to deadly microbes such as Bordetella pertussis, Mycobacterium tuberculosis, and Coccidioides species. However, the rapid detection and analysis of airstreams as part of biosurveillance, public health monitoring, or epidemiological research remains challenging. Current state-of-the-art methods rely on bulky apparatuses for both the collection and detection of airborne agents; most of these methods are ill suited to rapid response point-of-testing within medical facilities, workplace locals, or public spaces. Further, these technologies are based on bulk Polymerase Chain Reaction (PCR) and Loop-mediated isothermal amplification (LAMP) methods that have limited quantitative accuracy. Thus, more portable and accurate platforms are needed to address the types of rapid response and ubiquitous monitoring that is required to minimize outbreaks in the 21st century. Towards this objective, this grant will address the need for an improved method of airborne pathogen detection through the development of the digital droplet Aerosol Capture & Quantification (ddACQ) system. The ddACQ system consists of two novel technologies, a filter particle array and a droplet buoyancy counter. The filter particle array allows for the capture of airborne pathogens or biological agents and generation of microfluidic droplets when mixed with an oil and water reagent solution. A phone-powered heat block then drives a one-step isothermal digital droplet reaction. Digital techniques have several key advantages over classical quantitative PCR and LAMP techniques, namely single molecule detection and direct quantification without a standard curve. Finally, the droplet buoyancy counter allows for smartphone based read out of the reaction immediately at the testing site in under an hour. Together, the innovations within and implementation of the ddACQ system represents a novel application of microfluidic principles and an enabling technology for both pathogen transmission research and public health monitoring applications.", "keywords": [ "2019-nCoV", "Address", "Aerosols", "Air", "Air Movements", "Biological Assay", "Biological Monitoring", "Biological Products", "Bordetella pertussis", "COVID-19", "Cellular Phone", "Characteristics", "Coccidioides", "Collection", "Complex", "Detection", "Development", "Devices", "Disease Outbreaks", "Elements", "Epidemiologic Research", "Etiology", "Generations", "Goals", "Grant", "Heating", "Hour", "Human Resources", "Hydrogels", "Individual", "Influenza", "Influenza A virus", "Influenza B Virus", "Lighting", "Measles", "Measurement", "Measures", "Mediating", "Medical", "Methods", "Microbe", "Microfluidics", "Microscope", "Modeling", "Modernization", "Monitor", "Mycobacterium tuberculosis", "Oils", "Pathogen detection", "Polymerase Chain Reaction", "Public Health", "Quarantine", "Reaction", "Reagent", "Recovery", "Research", "Route", "Running", "Sampling", "Site", "Stream", "Structure", "Surface", "Syndrome", "System", "Techniques", "Technology", "Telephone", "Testing", "Training", "Virus", "Water", "Workplace", "aerosolized", "air sampling", "biosecurity", "contaminated water", "cost", "design", "detection platform", "digital", "experience", "improved", "innovation", "instrumentation", "isothermal amplification", "method development", "new technology", "novel", "pandemic disease", "particle", "pathogen", "pathogenic bacteria", "pathogenic fungus", "portability", "rapid detection", "rapid testing", "respiratory", "respiratory virus", "response", "risk stratification", "single molecule", "targeted agent", "transmission process", "waterborne" ], "approved": true } }, { "type": "Grant", "id": "15958", "attributes": { "award_id": "1R01AI190181-01A1", "title": "Advancing iPSC-derived Thymic Epithelial Cells as Cell Therapy for T Cell Immune Reconstitution in Vulnerable Populations(original application ID AI190181-01)", "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": 44292, "first_name": "MERCY R", "last_name": "PRABHUDAS", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-04-08", "end_date": "2031-03-31", "award_amount": 809250, "principal_investigator": { "id": 44405, "first_name": "Katja Gabriele", "last_name": "Weinacht", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 3414, "ror": "", "name": "STANFORD UNIVERSITY", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "| NARRATIVE The thymus instructs T cell immunity and central tolerance, yet its therapeutic potential remains clinically untapped as the signals that drive thymic epithelial cell (TEC) differentiation remain incompletely understood. The thymic epithelium comprises a highly specialized set of cells that attract lymphoid progenitors, promote their proliferation and maturation into thymocytes, and facilitate the selection of a diverse, self-tolerant T cell receptor (TCR) repertoire. The role of the thymus in building immune identity begins before birth. The organ peaks in size in infancy and then structurally and functionally involutes over time. This process causes the decline in immune competence with age (immune senescence). The impact of this phenomenon was exposed during the COVID-19 pandemic when waning immunity left the elderly more vulnerable to adverse outcomes. Thymus insult also occurs in many patients through medications, radiation, infections and graft-versus-host disease. The most severe form of thymic compromise is congenital athymia, the inborn absence of the thymus due to genetic mutations. Genetic or acquired thymic injury leads to immunodeficiency, autoimmunity, inflammation and increased cancer risk. Regenerating thymic function, e.g., through human induced pluripotent stem cell (iPSC)-derived regenerative thymic tissues holds greatest therapeutic promise for these patients. We have used single-cell transcriptomics of human fetal anterior foregut-derived organs to uncover the signals that drive TEC differentiation. We have translated these insights into a novel differentiation platform for the derivation of TECs from iPSCs in vitro. When iPSC-derived TEC organoids are transplanted into athymic NSG nude (NSG-Foxn1-/-) mice engrafted with human hematopoietic stem cells, they function like the human thymus, giving rise to human ab-T cells with a diverse TCR repertoire, gd-T cells and regulatory T cells. In this application, we now seek to advance the translation of iPSC-derived TECs (iTECs) by testing their safety and efficacy as cell therapy for vulnerable patient populations in need of improved T cell immunity. In Aim 1, we will determine the capacity of iTECs to promote T cell reconstitution, functional antigen-specific T cell responses and the development of a broad TCR repertoire in vivo. In Aim 2, we will assess if T cells educated on iTEC are tolerant to “self” but respond to “non-self”. In addition, we will directly analyze the HLA-associated peptide repertoire presented on iTECs using immunopeptidomics. In Exploratory Aim 3, we will test if HLA-editing of iPSCs for iTECs derivation affects antigen-specific immune responses, TCR repertoire, and immunopeptidome in vivo. Advancing the translation of iPSC-derived TECs into a cell therapy is an entirely new strategy to leverage the therapeutic potential of T cells from inside the body and could begin a new chapter of immunotherapeutics.", "keywords": [ "Affect", "Age", "Aging", "Allogenic", "Anterior", "Antibody Response", "Antigens", "Autoimmunity", "Birth", "CD8B1 gene", "COVID-19 pandemic", "Cancer Vaccines", "Cell Differentiation process", "Cell Maintenance", "Cell Physiology", "Cell Therapy", "Cells", "Child", "Clinical", "Defect", "Derivation procedure", "Development", "Elderly", "Engraftment", "Epithelium", "Future", "Genetic", "Genetic Transcription", "Goals", "Hematopoietic Stem Cell Transplantation", "Hematopoietic stem cells", "Histocompatibility", "Histologic", "Human", "Immune", "Immune response", "Immune system", "Immunity", "Immunocompetence", "Immunocompromised Host", "Immunosuppression", "Immunotherapeutic agent", "Immunotherapy", "In Vitro", "Infant", "Infection", "Inflammation", "Injury", "Interferons", "Lead", "Left", "Life", "Malignant Neoplasms", "Medical", "Mixed Lymphocyte Culture Test", "Mus", "Mutation", "Natural regeneration", "Nude Mice", "Organ", "Organ Donor", "Organ Transplantation", "Organoids", "Output", "Pathogenicity", "Patients", "Peptides", "Pharmaceutical Preparations", "Population", "Primitive foregut structure", "Process", "Prognosis", "Proliferating", "Radiation", "Regulatory T-Lymphocyte", "Rejuvenation", "Role", "Safety", "Self Tolerance", "Signal Transduction", "Solid", "T cell reconstitution", "T cell response", "T cell therapy", "T-Cell Development", "T-Lymphocyte", "T-cell receptor repertoire", "Testing", "Tetanus", "Therapeutic", "Thymic Tissue", "Thymic epithelial cell", "Thymus Gland", "Time", "Translating", "Translations", "Transplantation", "Vulnerable Populations", "Work", "adverse outcome", "antigen-specific T cells", "athymia", "cancer risk", "central tolerance", "differentiation protocol", "efficacy evaluation", "efficacy testing", "engineered T cells", "fetal", "graft vs host disease", "human data", "human induced pluripotent stem cells", "human leukocyte antigen testing", "immune checkpoint blockade", "immune reconstitution", "immunodeficiency", "immunosenescence", "improved", "in vivo", "induced pluripotent stem cell", "infancy", "insight", "lymphoid progenitors", "novel", "novel strategies", "organoid transplantation", "pandemic disease", "patient population", "prevent", "regenerative", "response", "risk mitigation", "stem cell derived tissues", "technology platform", "thymic aplasia", "thymic regeneration", "thymocyte", "transcriptomics" ], "approved": true } }, { "type": "Grant", "id": "15957", "attributes": { "award_id": "1R01AI196011-01", "title": "Protective mRNA Vaccines Against Tuberculosis", "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": 44404, "first_name": "KATRIN", "last_name": "EICHELBERG", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-04-06", "end_date": "2031-03-31", "award_amount": 717003, "principal_investigator": { "id": 27480, "first_name": "ADEL M", "last_name": "TALAAT", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 799, "ror": "", "name": "UNIVERSITY OF WISCONSIN-MADISON", "address": "", "city": "", "state": "WI", "zip": "", "country": "United States", "approved": true }, "abstract": "Protective mRNA Vaccines Against Tuberculosis. Summary. Tuberculosis (TB), caused by Mycobacterium tuberculosis (M. tb), remains a significant global health challenge, affecting approximately one-third of the world’s population and resulting in nearly 1.4 million deaths annually. The existing vaccine, M. bovis BCG (BCG), offers variable protection, with efficacy ranging from 0% to 80%. Our previous research has identified several innovative platform technologies aimed at enhancing vaccine development for major infections impacting both human and animal health. Notably, we have developed unique nano-adjuvant systems (NAS) that have demonstrated effectiveness against respiratory infections, including coronavirus and M. avium. In this project, we will utilize our expertise in tuberculosis vaccine development and nanoparticle vaccine platforms to assess the protective efficacy of a novel combination vaccine against TB. Our approach incorporates cutting-edge mRNA vaccine technology delivered via QuilA-DOTAP (QTAP), a novel lipid nanoparticle delivery adjuvant that ensures stable mRNA transcript delivery at various temperatures suitable for use in TB- endemic regions. Preliminary analyses of QTAP-adjuvanted combination mRNA vaccine encoding three mycobacterial antigens (Ag85B, Hsp70, and EsxH), referred to as QRNA, have shown robust protective immunity in mouse models challenged with both low and high doses of the virulent M. tb Erdman strain. In this project, we plan to First; examine the safety and immunogenicity of QRNA vaccines in variable murine models using both immune-compromised (Rag1-/-) and immune-competent (C3HeB/FeJ) murine models. Second; analyze the protective role of QRNA vaccine as a homologous or heterologous vaccine primed with BCG against challenge with M. tb Erdman (lineage 4, laboratory strain) or HN878 (lineage 2, hypervirulent clinical strain). Finally, we will assess protective immunity of QRNA vaccines in guinea pigs to identify vaccine-induced immune correlates of protection elicited by the mRNA vaccine candidates in guinea pigs, a TB model that mimic human infection. Once achieved, results from those aims will enhance our understanding of RNA-based immunization against TB. Future projects will further dissect the generated immunity in non-human primates, a more relevant model for human TB.", "keywords": [ "Address", "Adjuvant", "Adopted", "Adult", "Aerosols", "Affect", "Animals", "Antigens", "Area", "BCG Vaccine", "Bacille Calmette-Guerin vaccination", "C3HeB/FeJ Mouse", "CD8B1 gene", "Categories", "Cavia", "Cells", "Cessation of life", "Clinical", "Combined Vaccines", "Coronavirus", "Developing Countries", "Development", "Disease", "Disease Outbreaks", "Dose", "Effectiveness", "Emerging infection", "Ensure", "Flow Cytometry", "Future", "Generations", "Health", "Human", "IL17 gene", "Immune", "Immune response", "Immunity", "Immunization", "Immunocompetent", "Infection", "Interferon Type II", "Interleukin-2", "Laboratories", "Maps", "Messenger RNA", "Modeling", "Mus", "Mycobacterium Infections", "Mycobacterium avium", "Mycobacterium bovis", "Mycobacterium tuberculosis", "Outcome", "Outcomes Research", "Pathology", "Population", "Public Health", "RNA", "RNA vaccination", "RNA vaccine", "Rag1 Mouse", "Regimen", "Research", "Respiratory Tract Infections", "Rodent Model", "Role", "Safety", "System", "T-Lymphocyte", "TNF gene", "Technology", "Temperature", "Tissues", "Transcript", "Tuberculosis", "Tuberculosis Vaccines", "United States National Institutes of Health", "Vaccination", "Vaccines", "Virulent", "authority", "cytokine", "global health", "immunogenicity", "improved", "innovation", "lipid nanoparticle", "mRNA Stability", "mouse model", "mycobacterial", "nano", "nanoparticle", "nanoparticle delivery", "nonhuman primate", "novel", "protective efficacy", "technology platform", "transcriptome sequencing", "transcriptomic profiling", "tuberculosis immunity", "vaccine candidate", "vaccine development", "vaccine formulation", "vaccine immunogenicity", "vaccine platform", "vaccine safety" ], "approved": true } }, { "type": "Grant", "id": "15956", "attributes": { "award_id": "1R01AI189721-01A1", "title": "Decoding cellular networks governing respiratory mucosal IgA immunity", "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": 44403, "first_name": "HARIHARAN", "last_name": "SUBRAMANIAN", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2026-04-01", "end_date": "2031-03-31", "award_amount": 773388, "principal_investigator": { "id": 20818, "first_name": "Jie", "last_name": "Sun", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1426, "ror": "", "name": "MAYO CLINIC ROCHESTER", "address": "", "city": "", "state": "MN", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 3413, "ror": "", "name": "UNIVERSITY OF VIRGINIA", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "Abstract/summary The factors and mechanisms driving robust respiratory mucosal immunity, particularly respiratory IgA responses, post-infection or vaccination are largely unknown. This represents a significant gap in our understanding necessary for designing future vaccination strategies aimed at providing enhanced mucosal protection against respiratory viral infections including new SARS-CoV-2 variants. This RO1 grant proposal aims to address this critical knowledge gap. Our central hypothesis is that the generation of mucosal IgA and respiratory protective immunity is contingent upon the localized interactions among pulmonary macrophages, CD4 T cells, and B cells within the respiratory tract. Three specific aims (SA) are proposed. Aim 1: Identify the associated mechanisms by which respiratory CD4+ T cells promote IgA production in situ. Aim 2: Elucidate TGFβ-dependent macrophages and B cell interactions in mucosal IgA production. Aim 3: Define the molecular and functional signatures of mucosal cross-reactive IgA-producing B cells. We believe that the insights obtained will be crucial in developing next-generation mucosal vaccines designed to effectively counter SARS-CoV-2 variants and other respiratory pathogens, significantly enhancing public health prevention strategies against respiratory infections. .", "keywords": [ "2019-nCoV", "Address", "Adenoviruses", "Alveolar Macrophages", "Animals", "Antibodies", "Applications Grants", "Area", "Automobile Driving", "B-Lymphocytes", "B-cell receptor repertoire sequencing", "Blood", "CD4 Positive T Lymphocytes", "Cell Communication", "Circulation", "Clinical Research", "Cloning", "Exhibits", "Future", "Generations", "Goals", "Hybrids", "Immune Evasion", "Immune response", "Immunity", "Immunoglobulin A", "Immunoglobulin G", "Immunologics", "In Situ", "Individual", "Infection", "Inhalation", "Intramuscular", "Knowledge", "Link", "Macrophage", "Maintenance", "Molecular", "Morbidity", "Mucosal Immunity", "Mucous Membrane", "Plasma Cells", "Prevention strategy", "Production", "Public Health", "RNA vaccination", "RNA vaccine", "Research", "Respiratory Mucosa", "Respiratory System", "Respiratory Tract Infections", "Role", "SARS-CoV-2 exposure", "SARS-CoV-2 infection", "SARS-CoV-2 variant", "Sea", "Secondary Immunization", "Severity of illness", "Shapes", "Signal Transduction", "Testing", "Th1 Cells", "Transforming Growth Factor beta", "Vaccinated", "Vaccination", "Vaccine Design", "Viral Respiratory Tract Infection", "Virus", "booster vaccine", "cross reactivity", "design", "dimer", "influenzavirus", "insight", "interleukin-21", "mortality", "mucosal vaccination", "mucosal vaccine", "next generation", "novel vaccines", "pathogenic virus", "pulmonary", "recruit", "respiratory", "respiratory pathogen", "response", "single-cell RNA sequencing", "transmission process", "vaccination strategy", "variants of concern", "viral transmission" ], "approved": true } } ], "meta": { "pagination": { "page": 4, "pages": 1424, "count": 14236 } } }