Grant List
Represents Grant table in the DB
GET /v1/grants?sort=-awardee_organization
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-awardee_organization", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1405&sort=-awardee_organization", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=-awardee_organization", "prev": null }, "data": [ { "type": "Grant", "id": "15803", "attributes": { "award_id": "1I01HX003797-01A3", "title": "Evaluating Veterans' Reproductive Healthcare Access, Quality and Outcomes in a Changing Landscape (EVOLVE)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2025-07-01", "end_date": "2029-06-30", "award_amount": null, "principal_investigator": { "id": 32893, "first_name": "Lisa Susanne", "last_name": "Callegari", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32894, "first_name": "Deirdre A", "last_name": "Quinn", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2660, "ror": "", "name": "VA PUGET SOUND HEALTHCARE SYSTEM", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true }, "abstract": "Background: Recent years have witnessed unprecedented changes in the reproductive healthcare landscape in the US, including heightened awareness of reproductive health inequities following the 2020 nationwide racial justice reckoning, barriers to access resulting from the COVID-19 pandemic, and the proliferation of state abortion restrictions and bans following the 2022 Dobbs v Jackson Supreme Court decision. Today, access to high-quality, equitable contraceptive care has never been more vital for Veterans, who face elevated risks of poor outcomes from unintended pregnancy due to high rates of health comorbidities and psychosocial risks. The Examining Contraceptive Use and Unmet Need in Veterans (ECUUN) survey fielded in 2014-16 by study team members demonstrated high rates of unintended pregnancy and gaps in VA contraceptive access and quality, with significant disparities among Black and Latinx Veterans. While the ECUUN study helped inform VA’s reproductive health policies to date, updated data are urgently needed to capture VA’s progress in addressing disparities over time as well as its ability to meet Veterans’ needs in today’s shifted landscape. Significance: This study will generate timely quantitative and qualitative data necessary for VA as a learning health system to address gaps in access and quality and to adapt its policies and programming to meet Veterans’ changing needs. In addition, this study focuses on contraceptive counseling experiences in marginalized Veterans, for whom this care may be fraught due to the US history of reproductive oppression such as forced sterilization and policies to punish or limit reproduction in racial minority and low-income people. Findings will enable VA to respond to new White House and congressional directives related to women’s health that call for research to advance reproductive healthcare access and reduce disparities in care. Innovation & Impact: This proposal is innovative in its timeliness, use of prior data to draw novel comparisons over time, deployment of new state-of-the-art person-centered measures not yet fielded in VA such as the National Quality Forum (NQF)-endorsed Person-Centered Contraceptive Counseling (PCCC) measure, and collection of data to capture experiences of VA’s new policy to provide abortion care in select cases. Specific Aims: Aim 1: To use quantitative survey data to examine changes over time since ECUUN in contraceptive use, unintended pregnancy, and abortion, including differences by Veteran characteristics (e.g., race/ethnicity, geography). Aim 2: To use quantitative survey data to test for current disparities in novel person-centered measures (e.g., PCCC) by Veteran characteristics and characteristics of their health care. Aim 3: To contextualize Aim 1 & 2 findings, including disparities in experiences of contraceptive care and unintended pregnancy/abortion, by conducting qualitative interviews with Veterans. Methodology: This is a sequential explanatory mixed methods study beginning with a national survey of 3,600 pregnancy-capable reproductive-age Veterans who used VA primary or gynecology care in the past year. Qualitative interviews will then be conducted among Veteran survey respondents, purposively sampling at-risk subgroups (Black, Latinx, rural, residence in abortion-restrictive state) whose survey responses indicate gaps in care quality or equity. Quantitative data will inform qualitative sampling and data collection, and quantitative and qualitative data will be integrated using mixed methods analytic techniques including joint displays. Next Steps/Implementation: Next steps will include conducting a stakeholder engagement meeting with Veterans, women’s health providers, and operational partners from the Offices of Women’s Health, Health Equity, and Rural Health to share key research findings, develop strategic goals, and prioritize interventions to address disparities in contraceptive access and quality. Ultimately, this study has the potential to enhance VA’s ability to be a national leader in delivering high-quality and person-centered reproductive healthcare and to inform efforts to advance quality and equity in reproductive healthcare both within and beyond the VA.", "keywords": [ "Address", "Awareness", "Black race", "COVID-19 pandemic", "Caring", "Characteristics", "Clinic", "Clinical", "Coercion", "Collaborations", "Congresses", "Constitution", "Contraceptive Agents", "Contraceptive Usage", "Contraceptive methods", "Counseling", "Data", "Data Collection", "Development", "Disparity", "Equity", "Ethnic Origin", "Exclusion", "Female", "Geography", "Goals", "Gynecology", "Health", "Health Care", "Health Personnel", "Health Policy", "Health system", "Individual", "Intention", "Intervention", "Interview", "Investments", "Involuntary Sterilization", "Joints", "Judgment", "Justice", "Latina", "Latinx", "Lead", "Learning", "Low Income Population", "Low income", "Measures", "Medical", "Medical Records", "Mental Health", "Methodology", "Methods", "Mission", "Movement", "Outcome", "Personal Satisfaction", "Persons", "Policies", "Populations at Risk", "Pregnancy", "Proliferating", "Provider", "Punishment", "Quality of Care", "Race", "Recording of previous events", "Reproduction", "Reproductive Health", "Reproductive History", "Research", "Respondent", "Risk", "Rural", "Rural Health", "Sampling", "Services", "Subgroup", "Supreme Court Decisions", "Surveys", "Techniques", "Testing", "Time", "Trust", "United States Department of Veterans Affairs", "Update", "Veterans", "Voice", "Women's Health", "abortion", "access disparities", "analytical method", "comorbidity", "disparity reduction", "experience", "field survey", "gaps in access", "gender minority group", "health care availability", "health care disparity", "health care settings", "health equity", "health inequalities", "innovation", "marginalization", "marginalized population", "medical vulnerability", "meetings", "member", "novel", "patient oriented", "people of color", "person centered", "preference", "pregnancy related death", "prevent", "primary care provider", "psychosocial", "racial disparity", "racial minority", "reproductive", "reproductive age", "residence", "response", "rural area", "rurality", "sample collection", "sexual minority group", "sexual trauma", "social", "unintended pregnancy" ], "approved": true } }, { "type": "Grant", "id": "15801", "attributes": { "award_id": "1R21AI190246-01", "title": "Interrogating stress and viral shedding in a migratory bat model", "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": "2025-07-21", "end_date": "2027-06-30", "award_amount": 376932, "principal_investigator": { "id": 25386, "first_name": "Daniel", "last_name": "Becker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2659, "ror": "", "name": "UNIVERSITY OF OKLAHOMA", "address": "", "city": "", "state": "OK", "zip": "", "country": "United States", "approved": true }, "abstract": "Bats harbor many zoonotic viruses, including both genera of coronaviruses (CoVs) pathogenic in humans (α- and β- CoVs). Limited evidence to-date suggests that periods of active infection in bats—and thus opportunities to transmit zoonotic viruses to humans—are driven by energetically demanding periods that modulate immune tolerance of infection and facilitate viral replication and shedding. However, such work has largely ignored immune mechanisms and has focused primarily on reproductive and nutritional stress. This project will combine field studies and in vitro analyses to test long-distance migration in bats as a driver of CoV infection and shedding. We will focus on Mexican free-tailed bats (Tadarida brasiliensis), a common and widespread migratory bat species in North America for which we and others have detected CoVs similar to HCoV-229E and that are susceptible to SARS-CoV-2. In Aim 1, we will sample T. brasiliensis at monthly intervals at our established study site in western Oklahoma, capturing energetically demanding periods of spring migration from Mexico, birth and lactation, and fall migration back to Mexico. We will characterize CoV diversity and infection status in saliva and fecal samples using RT-PCR followed by Sanger sequencing and will attempt to isolate naturally occuring bat CoVs. We will also quantify stress physiology through fecal cortisol and ratios of neutrophils to lymphocytes in blood, followed by generalized additive models to assess seasonality in physiological metrics and viral infection as well as to test how bat physiology relates to viral shedding. In Aim 2, we will collect lung and intestine from male and female T. brasiliensis bats and use our established protocols to develop new primary and immortalized cell lines, expanding the limited in vitro resources currently available for this bat species from an existing lung epithelial cell line. We will then test virus susceptibility and permissivity by infecting these new cell lines with HCoV 229E, SARS-CoV-2, and MERS-CoV; if isolation of natural bat CoVs is successful, we will also include infections with these viruses. Viral replication will be assessed by qRT-PCR, immunofluorescence microscopy, and TCID50 assays. In Aim 3, we will use our novel T. brasiliensis cell lines to run factorial viral and cortisol challenge experiments to mimic the stressors observed in the field and their impacts on virus replication (i.e., HCoV 229E, SARS-CoV-2, and MERS-CoV as well as any CoVs we isolate here). Viral and cortisol challenges will be followed by global gene expression analyses via RNA-Seq to discover the response of bat cells to field-relevant cortisol concentrations in the face of CoV infection. This project will thus characterize relationships between the physiological demands of migration and CoV infection in wild bats and in vitro systems, establishing a pipeline for studying how stressors affect bat-borne zoonoses.", "keywords": [ "2019-nCoV", "Affect", "Back", "Biological Assay", "Birth", "Blood", "COVID-19 detection", "COVID-19 susceptibility", "Cell Line", "Cell Physiology", "Cells", "Chiroptera", "Coronavirus", "Coronavirus Infections", "Couples", "Coupling", "Data", "Dideoxy Chain Termination DNA Sequencing", "Digestion", "Disease", "Enzyme-Linked Immunosorbent Assay", "Epithelial Cells", "Feces", "Female", "Gene Expression Profiling", "Genes", "Glucocorticoids", "Goals", "Hour", "Human", "Hydrocortisone", "Immune", "Immune Tolerance", "Immunocompetent", "Immunofluorescence Microscopy", "Immunosuppression", "In Vitro", "Indiana", "Infection", "Innate Immune System", "Intestines", "Lactation", "Lung", "Lymphocyte", "Mammals", "Measures", "Mediating", "Methods", "Mexican", "Mexico", "Middle East Respiratory Syndrome Coronavirus", "Modeling", "North America", "Nutritional", "Oklahoma", "Pathogenicity", "Peptide Hydrolases", "Physiological", "Physiological Processes", "Physiology", "Pilot Projects", "Predisposition", "Protocols documentation", "Quantitative Reverse Transcriptase PCR", "RNA", "Resources", "Reverse Transcriptase Polymerase Chain Reaction", "Running", "Saliva", "Sampling", "Seasonal Variations", "Seasons", "Site", "Stress", "System", "Tail", "Techniques", "Testing", "Time", "Trypsin", "Universities", "Vertebrates", "Viral", "Viral Genes", "Virulent", "Virus", "Virus Diseases", "Virus Replication", "Virus Shedding", "Washington", "Work", "Zoonoses", "bat-borne", "betacoronavirus", "cell immortalization", "cost", "experimental study", "falls", "field study", "gene network", "human coronavirus", "immunoregulation", "in vitro Model", "in vivo", "male", "medical schools", "migration", "neutrophil", "novel", "permissiveness", "reproductive", "response", "saliva sample", "sex", "stool sample", "stressor", "transcriptome", "transcriptome sequencing", "transmission process", "viral transmission", "virus testing" ], "approved": true } }, { "type": "Grant", "id": "15799", "attributes": { "award_id": "1R43CA298267-01A1", "title": "Ultra-precision diagnostics for ALK+ non-small cell lung cancer", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [ { "id": 32888, "first_name": "SWAMY KRISHNA", "last_name": "TRIPURANI", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-07-09", "end_date": "2026-06-30", "award_amount": 399153, "principal_investigator": { "id": 32889, "first_name": "David Randall", "last_name": "Armant", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32890, "first_name": "Rodrigo C", "last_name": "Fernandez-Valdivia", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2658, "ror": "", "name": "ALELOPHARMA INC.", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "Background & Significance: Identifying ALK-positive lesions, which are highly responsive to treatment with Crizotinib or Alectinib, is a high-priority for managing patients with ALK+ Non-Small Cell Lung Cancer (NSCLC). A blood-based companion diagnostic (liquid biopsy) could monitor NSCLC patients post-treatment for tumor recurrence without tissue re-biopsy, and also identify non-symptomatic ALK+ individuals for earlier, more effective treatment with ALK kinase inhibitors. Expansion of this approach to other major oncogenic mutations has potential as a non-invasive cancer screening tool that would be transformative for healthcare. Objective & Innovation: AleloPharma Inc. is achieving solutions for personalized precision medicine using AleloMAX, an innnovative high-dimensional molecular detection system that allows ultra-specific detection of target nucleic acids with an impressive 1-absolute copy per reacting assay limit-of-detection (LOD) that effectively eliminates both false positives and false negatives. We aim to offer clinicians a cutting-edge diagnostic capable of accurately detecting ALK translocations among cell-free RNA in the blood plasma of affected patients. Approach: A proof-of-principle study, supported by preliminary LOD data obtained with synthetic ALK constructs, is proposed to develop a liquid biopsy test to detect ALK translocation variants in a kit for use in clinical labs. • Specific Aim 1: Develop an ultra-specific and ultra-sensitive molecular detection platform for EML4-ALK gene fusion translocations in ALK+ NSCLC. We will probe EML4-ALK fusion RNAs using synthetic, in vitro-transcribed mRNAs encompassing the distinct EML4-ALK oncogenic variants. • Specific Aim 2: Demonstrate AleloMAX-ALK’s superior resolution power in ultra-specific molecular probing and limit-of-detection (LOD) analysis in a clinical proof-of-principle study. The EML4-ALK diagnostic platform will be tested using plasma- and/or blood-derived nucleic acid samples obtained from ALK+ NSCLC patients, ALK- NSCLC patients, and healthy control volunteers. Team & Commercialization: Led by a distinguished team with a track record of groundbreaking research in molecular pharmacology, oncology and cellular biology, we are uniquely positioned to tackle this challenge. Our clear roadmap includes patenting all IP and aspires to launch a diagnostic that will have significant clinical utility. Feasibility & Impact: The assay is expected to detect low levels of EML4-ALK mutations in blood of individuals with ALK+ NSCLC. AleloMAX demonstrated diagnostic superiority in prior studies of the NSCLC biomarker POGLUT-1, SARS-CoV-2 and RSV with impressive results. Assay parameters established in this project will be developed as a kit for use in a Phase II study to establish its clinical utility as a companion diagnostic for NSCLC. Successful development of an ALK+ cancer diagnostic will be expanded to include assays for RET, ROS1 and other onco-mutations with additional AleloMAX liquid biopsy assays to monitor a broader panel of cancers. Conclusion: Combining innovation and tangible clinical benefit, our initiative represents a transformative shift in early detection and management of cancer that will positively impact patient survival.", "keywords": [ "2019-nCoV", "ALK gene", "Acceleration", "Address", "Affect", "Aftercare", "Algorithms", "Archives", "Award", "Biological Assay", "Biopsy", "Blood", "Businesses", "COVID-19 diagnosis", "Cancer Detection", "Cancer Diagnostics", "Cancer Patient", "Cells", "Cellular biology", "Chemistry", "Chromosomal translocation", "Clinical", "DNA Sequence Alteration", "Data", "Detection", "Development", "Diagnosis", "Diagnostic", "Diagnostic tests", "Disease", "Early Diagnosis", "Evaluation", "Event", "Fluorescent in Situ Hybridization", "Future", "Gene Amplification", "Gene Fusion", "Genetic Transcription", "Health Care", "Image", "In Vitro", "Individual", "Industry", "Legal patent", "Lesion", "Malignant Neoplasms", "Malignant neoplasm of lung", "Marketing", "Methods", "Molecular", "Molecular Genetics", "Molecular Probes", "Monitor", "Mutation", "Neoplasms", "Non-Small-Cell Lung Carcinoma", "Nucleic Acids", "Oncogenes", "Oncogenic", "Oncology", "Patient Monitoring", "Patients", "Performance", "Pharmacology", "Phase", "Plasma", "Positioning Attribute", "Probability", "Procedures", "Process", "Prognosis", "Protein Tyrosine Kinase", "RNA", "ROS1 gene", "Reaction", "Recurrent tumor", "Research", "Resolution", "Sampling", "Screening for cancer", "Screening procedure", "Sensitivity and Specificity", "Series", "Signal Transduction", "Specificity", "Techniques", "Technology", "Testing", "Therapeutic", "Therapeutic Intervention", "Time", "Tissues", "Transcript", "Tube", "Tyrosine Kinase Inhibitor", "Variant", "Vision", "Work", "biobank", "cancer biomarkers", "cancer diagnosis", "chromosome fusion", "cohort", "commercialization", "companion diagnostics", "comparative", "crizotinib", "detection assay", "detection limit", "detection platform", "diagnostic platform", "diagnostic technologies", "diagnostic tool", "diagnostic value", "early screening", "effective intervention", "effective therapy", "genetic diagnostics", "high dimensionality", "improved", "inhibitor", "innovation", "kinase inhibitor", "liquid biopsy", "molecular diagnostics", "next generation", "next generation sequencing", "novel", "overexpression", "patient screening", "personalized diagnostics", "phase 2 study", "precision medicine", "screening", "sensor technology", "success", "tumor", "validation studies", "volunteer" ], "approved": true } }, { "type": "Grant", "id": "15798", "attributes": { "award_id": "1DP2AI192737-01", "title": "Decoding multidrug-resistant pathogen dynamics for clinically-relevant wastewater surveillance", "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": 32875, "first_name": "INKA I", "last_name": "SASTALLA", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-07-23", "end_date": "2030-06-30", "award_amount": 534000, "principal_investigator": { "id": 32887, "first_name": "Medini K", "last_name": "Annavajhala", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2657, "ror": "", "name": "CHILDREN'S HOSP OF PHILADELPHIA", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Multidrug-resistant bacteria (MDRB) contribute increasingly to morbidity, mortality, and healthcare costs. Extended-spectrum beta-lactam- and carbapenem-resistant Enterobacterales (ESBL-E and CRE) are MDRB of particular concern due to their demonstrated ability to evolve into highly transmissible clones and acquire and spread antibiotic resistance determinants. Traditional epidemiological surveillance typically focuses on outbreaks of MDRB causing clinical infections, underestimating the burden of these pathogens within hospital systems. Broader efforts that account for asymptomatic carriage and environmental and community reservoirs would be ideal to track and mitigate the spread of MDRB. Wastewater surveillance has proven an effective tool for public health pathogen monitoring, as shown with SARS-CoV-2, but has not been established in clinical settings. This proposal will develop new systems to leverage wastewater for clinically applicable, proactive, and readily deployable MDRB monitoring. In Aim 1, we will establish standardized longitudinal surveillance strategies to inform infection control responses. We will use long-read metagenomics and novel bioinformatic approaches to rapidly identify significant changes in relative or absolute abundance of ESBL-E or CRE compared to site-specific baselines. We will also establish methods to translate wastewater testing data into interpretable “action thresholds” for use by hospital and clinical teams. In Aim 2, we will identify factors enabling the emergence of novel ESBL-E and CRE genotypes in the wastewater environment. Wastewater sampling can identify novel resistant genotypes before detection of clinical infections. We will further develop our novel Metapore-C technique to link bacterial hosts with resistance gene-harboring mobile elements and will use this approach to identify environmental factors such as wastewater antibiotic levels and plumbing design associated with acquisition of resistance. Lastly, in Aim 3 we will devise wastewater testing methodologies suited to resource-limited clinical settings. Given the costs and infrastructure needed for comprehensive clinical surveillance, wastewater testing is better poised to aid in mitigation of MDRB under resource constraints. Yet, current wastewater surveillance approaches are often impractical in such settings. Our strategies for reducing per-sample costs and the analytical burden of wastewater data interpretation, as piloted at a pediatric hospital in Gaborone, Botswana, will serve as a proof-of-concept for wastewater MDRB testing in diverse contexts. Overall, this project will significantly broaden the ability of wastewater surveillance to inform hospital and clinical care efforts, while establishing best practices for global surveillance of antimicrobial resistance in hospital wastewater.", "keywords": [ "2019-nCoV", "Address", "Antibiotic Resistance", "Antibiotics", "Antimicrobial Resistance", "Bacterial Infections", "Bioinformatics", "Biological Testing", "Botswana", "COVID-19 pandemic", "Childhood", "Clinical", "Communities", "Complement", "Data", "Data Analyses", "Detection", "Development", "Disease Outbreaks", "Elements", "Enabling Factors", "Environment", "Environmental Risk Factor", "Epidemiologic Monitoring", "Epidemiology", "Genetic Materials", "Genomics", "Genotype", "Goals", "Health Care Costs", "Health Care Systems", "Horizontal Gene Transfer", "Hospitals", "Infection", "Infection Control", "Infection prevention", "Infrastructure", "Link", "Metagenomics", "Methodology", "Methods", "Mobile Genetic Elements", "Molecular", "Monitor", "Morbidity - disease rate", "Multi-Drug Resistance", "Outcome", "Patients", "Pediatric Hospitals", "Plasmids", "Plumbing", "Population", "Postdoctoral Fellow", "Prevalence", "Protocols documentation", "Public Health", "Research", "Resistance", "Resource-limited setting", "Resources", "Sampling", "Site", "Standardization", "System", "Techniques", "Testing", "Therapeutic", "Thinking", "Translating", "Treatment Failure", "United States", "Work", "beta-Lactams", "bioinformatics pipeline", "carbapenem resistant Enterobacterales", "clinical application", "clinical care", "clinical sequencing", "clinically relevant", "combat", "cost", "cost effective", "design", "experience", "health care settings", "hospital care", "improved", "innovation", "low and middle-income countries", "microbiome", "microbiota", "microorganism", "mortality", "multi-drug resistant bacteria", "multi-drug resistant pathogen", "novel", "pathogen", "resistance gene", "resistance mechanism", "response", "surveillance strategy", "tool", "wastewater sampling", "wastewater surveillance", "wastewater testing" ], "approved": true } }, { "type": "Grant", "id": "15796", "attributes": { "award_id": "1R44NS145848-01", "title": "Development of Tissue Engineered Tregs as a Treatment for Acute Ischemic Stroke", "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": 32884, "first_name": "FLOY ANNETTE", "last_name": "GILCHRIST", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-15", "end_date": "2027-07-31", "award_amount": 1150417, "principal_investigator": { "id": 32885, "first_name": "Payam", "last_name": "Zarin", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2656, "ror": "", "name": "GENTIBIO, INC.", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "In the U.S., nearly 800,000 individuals experience a stroke each year, predominantly ischemic strokes. The economic burden of stroke is staggering, with projected stroke-related medical costs in the U.S. expected to surpass $94 billion by 2035. This underscores the urgent need for effective therapies to address this significant public health challenge. While the potential of regulatory T cells (Tregs) in promoting stroke recovery has been recognized, translating this promise into clinical success has been hampered by several obstacles. Traditional Treg therapies face challenges in manufacturing, phenotypic instability, and a lack of tissue specificity. This proposal focuses on the development of allogeneic engineered tissue Tregs (EngTregs) as a novel off-the-shelf therapeutic approach for stroke. Overexpression of ST2, the receptor for the alarmin IL-33, enhances the ability of EngTregs to: (i) sense and respond to tissue damage (ST2-expressing EngTregs efficiently migrate to sites of inflammation and injury); (ii) suppress excessive inflammation (EngTregs exert potent anti-inflammatory effects through multiple mechanisms, including direct suppression of immune cells and modulation of the inflammatory environment); and (iii) actively participate in tissue repair (EngTregs produce growth factors and interact with other cells to promote tissue regeneration). Overexpression of FOXP3 ensures a stable and suppressive Treg phenotype, crucial for long-term therapeutic efficacy. A chemically induced signaling complex (CISC) enables tunable IL-2 signaling, promoting Treg survival and function while facilitating scalable manufacturing. These innovations culminate in a first-in-class allogeneic tissue EngTreg product with advantages in manufacturing scalability, cost-effectiveness, and therapeutic potential compared to conventional Treg therapies. Preliminary studies demonstrate the ability of allogeneic EngTregs to accumulate in the injured brain and improve motor skills, sensory function, learning, and memory following ischemic injury induced in the transient middle cerebral artery occlusion (tMCAO) mouse model of stroke. This proposal outlines three aims to further advance the preclinical development of EngTregs for stroke: Aim 1: Evaluate the therapeutic efficacy of EngTregs in two preclinical stroke models (permanent middle cerebral artery occlusion and photothrombosis) in both adult and aged mice, assessing a comprehensive range of functional and histological outcomes. Aim 2: Characterize the mechanism of action and define a comprehensive in vitro profile of the human EngTreg drug product, including assessment of cytokine sequestration, T cell suppression, macrophage polarization, and transcriptomic analysis. Aim 3: Assess the immunotoxicity and immunogenicity of human EngTregs to ensure clinical safety, including evaluation of cytokine release syndrome and allo-immunogenicity. Successful completion of these aims will provide critical preclinical data supporting the clinical translation of EngTregs as a novel and promising therapeutic strategy for stroke, addressing a significant unmet medical need.", "keywords": [ "AREG gene", "Acute", "Address", "Adhesives", "Adult", "Age", "Allogenic", "Antiinflammatory Effect", "Area", "Autologous", "Biological Assay", "Blood flow", "Brain Injuries", "C57BL/6 Mouse", "CCR5 gene", "CCR8 gene", "Cell Physiology", "Cell Survival", "Cell Therapy", "Cells", "Cessation of life", "Characteristics", "Chemicals", "Clinical", "Clinical Data", "Cognitive", "Complex", "Development", "Economic Burden", "Engraftment", "Ensure", "Evaluation", "FOXP3 gene", "Face", "Female", "Flow Cytometry", "Growth Factor", "Guidelines", "Health Care Systems", "High Prevalence", "Histologic", "Homing", "Human Engineering", "IL2RA gene", "Immune Cell Suppression", "In Vitro", "Individual", "Infarction", "Inflammation", "Inflammatory", "Injury", "Interleukin-13", "Interleukin-2", "Ischemic Stroke", "Learning", "Macrophage", "Mediating", "Medical", "Medical Care Costs", "Memory", "Middle Cerebral Artery Occlusion", "Mixed Lymphocyte Culture Test", "Modeling", "Motor Skills", "Mus", "Outcome", "Outcome Measure", "Patient-Focused Outcomes", "Patients", "Performance", "Persons", "Pharmaceutical Preparations", "Phase", "Phenotype", "Preclinical data", "Process", "Public Health", "Receptors Tumor Necrosis Factor Type II", "Recovery of Function", "Regulatory T-Lymphocyte", "Reperfusion Therapy", "Research", "Risk", "Safety", "Sensory", "Signal Induction", "Signal Transduction", "Sirolimus", "Site", "Specificity", "Stroke", "T cell therapy", "T-Lymphocyte", "TNFRSF1B gene", "Testing", "Therapeutic", "Tissue Engineering", "Tissues", "Toxic effect", "Translating", "Treatment Efficacy", "Upregulation", "Work", "aged", "angiogenesis", "axon injury", "blood-brain barrier permeabilization", "brain repair", "clinical translation", "cost", "cost effectiveness", "cytokine", "cytokine release syndrome", "disability", "disease heterogeneity", "effective therapy", "experience", "foot", "human tissue", "immunogenicity", "immunotoxicity", "improved", "inflammatory milieu", "inflammatory modulation", "innovation", "ischemic injury", "male", "manufacture", "manufacturing process", "migration", "morris water maze", "mortality", "mouse model", "neurogenesis", "novel", "object recognition", "old mice", "osteopontin", "overexpression", "patient subsets", "post stroke", "pre-clinical", "preclinical development", "preclinical evaluation", "programs", "public health relevance", "receptor", "repaired", "stroke model", "stroke recovery", "stro" ], "approved": true } }, { "type": "Grant", "id": "15795", "attributes": { "award_id": "1R21EB037846-01", "title": "Design principles for engineering therapeutic macrophages", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [ { "id": 32882, "first_name": "TUBA HALISE", "last_name": "FEHR", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-01", "end_date": "2028-07-31", "award_amount": 621158, "principal_investigator": { "id": 32883, "first_name": "Jason Hung-Ying", "last_name": "Yang", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2655, "ror": "", "name": "RUTGERS BIOMEDICAL AND HEALTH SCIENCES", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true }, "abstract": "Genetically engineered immune cells are an exciting and promising frontier for treating a wide range of complex diseases. However, hyperinflammatory toxicities such as cytokine release syndrome plague clinical trials, stymieing their widespread clinical adoption. Macrophages are innate immune cells that fulfill many roles in tissue repair, regeneration, and homeostasis and are important regulators of inflammation. However, they are significantly under-utilized as engineered immune cell therapies because significant knowledge gaps exist in understanding how to engineer synthetic gene circuits that work robustly in human macrophages. Tools do not yet exist for determining how macrophages should be biologically manipulated to activate desired effector functions (biological design principles). Tools also do not exist for determining what gene circuit architectures are needed to robustly induce desired gene circuit behaviors (gene circuit design principles). The overall goal for this proposal is to create a human macrophage design toolkit for engineering therapeutic macrophages. Our published and preliminary data demonstrate that we have developed tools that enable us to discover cell signaling interventions that can control macrophage effector functions (biological design principles) and gene circuit architectures that can exert robust behaviors in human macrophages (gene circuit design principles). Here we will apply both these approaches to elucidate biological and gene circuit design principles that can be used to engineer therapeutic macrophages that can suppress inflammatory cytokine secretion or induce anti- inflammatory cytokine secretion in inflamed tissues. We will elucidate biological design principles using an interpretable machine learning approach that we previous developed. This approach combines biochemical screening with predictive network modeling and machine learning to discover network mechanisms causally regulating cell phenotypes. We will elucidate gene circuit design principles using a recently developed ultra-high- throughput genetic screening approach (CLASSIC). This approach synthesizes and screens large, barcoded gene circuit libraries to associate gene circuit architectures with gene circuit behaviors. With these design principles we will engineer gene circuits for controlling IL-1β or IL-10 secretion in inflamed tissue contexts and validate these synthetic gene circuits in human monocyte-derived macrophages and THP-1 cells. In its entirety, this Trailblazer R21 project is a first step towards addressing the unmet need for design principles for engineering therapeutic macrophages. We envision that insights gained by this project will help establish engineered macrophages as a platform technology for treating a wide range of complex human diseases.", "keywords": [ "Address", "Adoption", "Anti-Inflammatory Agents", "Architecture", "Bar Codes", "Behavior", "Biochemical", "Biological", "Cells", "Cellular immunotherapy", "Clinical", "Clinical Trials", "Complex", "Data", "Disease", "Engineered Gene", "Engineering", "Environment", "Future", "Genes", "Genetic", "Genetic Engineering", "Genetic Screening", "Goals", "Homeostasis", "Human", "Immune", "Inflammation", "Inflammatory", "Interleukin-1 beta", "Interleukin-10", "Intervention", "Knowledge", "Libraries", "Machine Learning", "Macrophage", "Natural regeneration", "Phenotype", "Plague", "Process", "Publishing", "Role", "Signal Transduction", "Synthetic Genes", "Therapeutic", "Tissues", "Toxic effect", "Work", "cytokine", "cytokine release syndrome", "design", "explainable machine learning", "frontier", "gene discovery", "human disease", "immunoengineering", "insight", "monocyte", "network models", "prototype", "screening", "simulation", "synthetic biology", "technology platform", "tissue repair", "tool" ], "approved": true } }, { "type": "Grant", "id": "15794", "attributes": { "award_id": "1R21EB037897-01", "title": "Programmable RNA-Based Sensors for In Situ Cell Type Detection and Response", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [ { "id": 32881, "first_name": "SHAWN PATRICK", "last_name": "MULVANEY", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-01", "end_date": "2028-07-31", "award_amount": 673600, "principal_investigator": { "id": 30867, "first_name": "Lei", "last_name": "Wang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2654, "ror": "", "name": "NORTHEASTERN UNIVERSITY", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "There is a technology gap in currently developed tools that simultaneously monitor, compute, and respond to both coding and non-coding RNA in real-time within living cells or patients. The continued existence of this gap represents an urgent unmet need because, until it is filled, the accuracy of RNA-based therapeutics remains limited in complex and evolving biological systems like differentiation or cancer. The long-term goal of this proposal is to develop safe, universal, and programmable synthetic biology tools that using both coding and non- coding RNAs as disease marker inputs and program outputs to trigger therapeutic responses in patients. The objective of this particular application is to develop an RNA-based sensor (using mRNA as the delivery modality) that detects integrated changes in both mRNA and miRNA for in situ therapeutic responses within living cells and mouse models, given the crucial role of ncRNAs, especially microRNAs (miRNAs), as key regulators of post- transcriptional gene regulation, which allow only the correct set of genes to be active in each cell type. The central hypothesis is that an RNA-based sensor integrating both mRNA and miRNA inputs, using Boolean logic gate computation, can improve the specificity of cell type identification in complex biological systems. This proposed work builds on our and other’s recent works on sensing individual RNA species like mRNA in live cells. The rationale for the proposed research is that a deeper understanding of disease progression, derived from the vast RNA sequencing resources now available in user-friendly databases, creates a timely and unique opportunity for synthetic biologists to develop tools that can precisely identify diseased cells based on their RNA species and levels in living cells or even in patients. This allows for the development of treatments that specifically target diseased cells while minimizing off-target effects on healthy cells. Additionally, the success of COVID-19 mRNA vaccines using lipid nanoparticle delivery systems highlights the potential to translate RNA-based genetic circuits into practical medical applications. Given these advances, we plan to develop two independent and complementary aims for in situ cell state sensing using endogenous mRNA and miRNA as inputs: AND logic gates (requiring both inputs for an output) in Aim 1 and NOR logic gates (requiring neither input for an output) in Aim 2. This platform has broad biomedical potentials. As a proof of concept, we will demonstrate its ability to distinguish breast cancer cells from normal breast epithelial cells, evaluating its translational potential using a syngeneic mouse model of triple-negative breast cancer, which lacks key cell surface targets in current therapies. The proposed platform is innovative because it develops new platform by integration of existing miRNA sensing and RNA detecting approaches in a previously unproven combinatorial logic computation format to address a significant unmet need for accurate cell type identification for basic and translational applications. The proposed research is significant, because in situ monitoring and intervening based on endogenous RNAs will be key to addressing this unmet need, transforming disease detection and treatment.", "keywords": [ "4T1", "Address", "Animal Model", "Award", "Biological", "Biomedical Engineering", "Breast Cancer Cell", "Breast Cancer therapy", "Breast Epithelial Cells", "COVID-19", "Cell Line", "Cell Physiology", "Cell model", "Cell surface", "Cells", "Clinical", "Code", "Complex", "Data", "Databases", "Detection", "Disease", "Disease Marker", "Disease Progression", "Double-Stranded RNA", "Elements", "Engineering", "Ensure", "Gene Expression", "Genes", "Genetic", "Goals", "Human", "Immune System Diseases", "In Situ", "Individual", "Logic", "MCF10A cells", "MDA MB 231", "Malignant Neoplasms", "Medical", "Messenger RNA", "MicroRNAs", "Mission", "Modality", "Modeling", "Monitor", "National Institute of Biomedical Imaging and Bioengineering", "Nature", "Nerve Degeneration", "Output", "Patients", "Performance", "Play", "Post-Transcriptional Regulation", "Proteins", "Publishing", "RNA", "RNA vaccine", "Regulation", "Regulator Genes", "Repression", "Research", "Resources", "Role", "Sampling", "Specificity", "Survival Rate", "System", "Technology", "Testing", "Time", "Tissues", "Translating", "United States National Institutes of Health", "Untranslated RNA", "Work", "biological systems", "cell type", "combinatorial", "complex biological systems", "design", "design and construction", "differential expression", "improved", "in vitro Model", "innovation", "lipid nanoparticle", "mRNA delivery", "mammary", "model design", "model organism", "molecular sequence database", "mouse model", "nanoparticle delivery", "novel", "novel strategies", "programs", "prototype", "response", "risk mitigation", "scaffold", "sensor", "single-cell RNA sequencing", "success", "synthetic biology", "targeted treatment", "therapeutic RNA", "therapy development", "tool", "transcriptome sequencing", "transcriptomics", "translational applications", "translational potential", "treatment response", "triple-negative invasive breast carcinoma", "user-friendly" ], "approved": true } }, { "type": "Grant", "id": "15793", "attributes": { "award_id": "1R03AI188484-01A1", "title": "Establishing Human 2D and 3D Testicular Models to Elucidate Monkeypox Virus Tropism and Pathogenic Mechanisms in the Testes", "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": 32841, "first_name": "JANE M", "last_name": "KNISELY", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-01", "end_date": "2027-07-31", "award_amount": 156500, "principal_investigator": { "id": 32880, "first_name": "SAGUNA", "last_name": "VERMA", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2653, "ror": "", "name": "UNIVERSITY OF HAWAII AT MANOA", "address": "", "city": "", "state": "HI", "zip": "", "country": "United States", "approved": true }, "abstract": "One of the most important lessons learned from the recent global outbreak of the monkeypox virus, now called Mpox virus (MPXV, clade II), is the recognition that males are at a much higher risk for infection and higher occurrence of genital rash. Transmission via sexual contact is one of the main routes of virus spread. However, whether MPXV constitutes a sexually transmitted infection and can infect the male reproductive tract is still being debated, thus affecting the strategies to minimize transmission risk. Confirmed reports of MPXV shedding in seminal fluid for long after the clearance of viremia suggest the ability of MPXV to establish a productive infection in genitourinary organs. Poxviruses can also cause testicular complications, including azoospermia and seminiferous tubule atrophy. More recently, MPXV antigens have been detected in the testis of nonhuman primates both during the acute and convalescent stages, and the presence of testicular inflammation and necrosis in these macaques collectively suggests testis-tropism of MPXV, like Zika and Ebola viruses. However, direct evidence of MPXV infection in human testis is currently lacking, including cell targets of the virus and downstream consequences. Relevant human in vitro models are needed to characterize MPXV testicular infection. Human testis immune homeostasis is tightly governed by an elaborate communication network between different cells including testosterone-producing Leydig cells (LC) and Sertoli cells (SC) that form the blood-testis barrier (BTB). We recently established a 3D human testicular organoid (HTO) system comprised of undifferentiated spermatogonia cells, SC, LC, and peritubular myoid cells that closely recapitulates the cell diversity and function of the human testis to study Zika virus and SARS-CoV-2 infection. We have also established 2D cultures of primary SC, LC, and mixed seminiferous tubule cells and an in vitro BTB model to delineate cell-specific responses to viruses. Therefore, the goal of this study is to utilize our 2D and 3D testicular culture systems as an effective in vitro surrogate to model testicular infection of MPXV and understand downstream consequences. In Aim 1, we will assess MPXV infection in the 2D and 3D HTOs, identify cell targets, and characterize key infection pathologies, including cytopathic effects, antiviral response, and effect on BTB integrity. Aim 2 will utilize single-cell RNA sequencing to determine relative infectivity in each cell type and key pathways, including antiviral and inflammatory response, cell death, and spermatogenesis. Collective data will provide much-needed evidence of the testis as one of the target organs of MPXV replication after it is cleared from blood and skin lesions and lay the foundation for future in vivo studies of transmission via the sexual route. The knowledge of whether MPXV is a sexually transmitted infection is critical in providing clinical management and transmission guidelines, especially in men who have sex with men (MSM), an underrepresented group in biomedical research.", "keywords": [ "2019-nCoV", "3-Dimensional", "Acute", "Affect", "Androgens", "Anti-viral Response", "Antigens", "Area", "Atrophic", "Basic Science", "Biological Assay", "Biomedical Research", "Biomimetics", "Blood", "Blood-Testis Barrier", "CASP3 gene", "Cell Death", "Cell Differentiation process", "Cell Survival", "Cells", "Clinical", "Clinical Management", "Communication", "Data", "Development", "Discipline of Nursing", "Disease", "Disease Outbreaks", "Dissociation", "Ebola virus", "Electrical Resistance", "Environment", "Exanthema", "Foundations", "Future", "Genitalia", "Genitourinary system", "Germ Cells", "Goals", "Guidelines", "Homeostasis", "Human", "Immune", "Impairment", "In Situ Nick-End Labeling", "In Vitro", "Individual", "Infection", "Inflammation", "Inflammatory Response", "Injury", "Interferons", "International", "Investigation", "Kinetics", "Knowledge", "Macaca", "Measures", "Modeling", "Monkeypox", "Monkeypox virus", "Necrosis", "Organ", "Organoids", "Pathogenesis", "Pathogenicity", "Pathology", "Pathway interactions", "Plaque Assay", "Poxviridae", "Productivity", "Public Health", "Reporting", "Research Personnel", "Risk", "Route", "SARS-CoV-2 infection", "Seminal fluid", "Seminiferous tubule structure", "Sexual Transmission", "Sexually Transmitted Diseases", "Skin", "Spermatogenesis", "Supporting Cell", "Surface", "Suspensions", "System", "Testing", "Testis", "Testosterone", "Time", "Tropism", "Tubular formation", "Underrepresented Populations", "Undifferentiated", "United States National Institutes of Health", "Viral", "Viral Pathogenesis", "Viremia", "Virus", "Virus Diseases", "Virus Replication", "ZIKA", "Zika Virus", "cell type", "effective therapy", "high risk", "high risk population", "human model", "in vitro Model", "in vivo", "infection risk", "insight", "leydig interstitial cell", "male", "men", "men who have sex with men", "migration", "multidisciplinary", "nonhuman primate", "novel", "novel therapeutics", "public health emergency", "receptor", "reproductive tract", "response", "sertoli cell", "single-cell RNA sequencing", "skin lesion", "spermatogonial stem cells", "therapeutic development", "three-dimensional modeling", "transmission process", "viral transmission", "virus tropism" ], "approved": true } }, { "type": "Grant", "id": "15790", "attributes": { "award_id": "1R21AI193738-01", "title": "Combined pathogen and host-based diagnostic to identify etiology of lower respiratory tract infection", "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": 32875, "first_name": "INKA I", "last_name": "SASTALLA", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-05", "end_date": "2027-07-31", "award_amount": 244044, "principal_investigator": { "id": 7629, "first_name": "GAYANI", "last_name": "TILLEKERATNE", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 246, "ror": "https://ror.org/00py81415", "name": "Duke University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 2652, "ror": "", "name": "DUKE UNIVERSITY", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "Lower respiratory tract infection (LRTI) is the leading infectious cause of death globally. Despite its prevalence, the exact etiology of LRTI is unknown in the vast majority of cases. Even when identified, bacteria or viruses in nasopharyngeal (NP) or sputum samples may be colonizers in the upper tract rather than the cause of infection in the lower tract. Unclear LRTI etiology results in the overprescription of antibacterials, which in turn drives the global crisis in antibacterial resistance. Antibacterial overprescription and resistance are greater in low- or middle-income countries (LMICs), where basic diagnostic capacity is limited. Host-based diagnostics, which assess the host immune response to infection, have recently emerged as a complementary method to pathogen-based diagnostics for identifying the class of respiratory infection. Our team has developed host- based gene expression classifiers using peripheral blood samples to differentiate viral versus bacterial respiratory infection. The goal of the current application is to develop an integrated diagnostic that uses a single, non-invasive NP sample to detect both pathogen and host response to identify LRTI etiology. The following specific aims will be conducted at a collaborative research site in Sri Lanka: 1) Develop a novel NP- based gene expression classifier to identify viral versus non-viral LRTI, and 2) Design and validate an integrated pathogen and host gene expression test to identify viral versus non-viral LRTI using a quantitative real-time polymerase chain reaction (qRT-PCR) assay. For aim 1, we will use previously collected NP samples from clinically adjudicated viral and non-viral LRTI patients in Sri Lanka and conduct low-input RNA sequencing. Machine-learning approaches will identify host gene expression classifiers that discriminate viral versus non-viral LRTI. For aim 2, the genes identified in the NP-based classifier, as well as nucleic acid targets for two respiratory viruses that are frequently implicated in true infection as well as asymptomatic colonization (SARS-COV-2 and human rhinovirus [HRV]), will be migrated onto TaqMan Low-Density Array (TLDA) cards. A prospective cohort of patients will be enrolled in Sri Lanka, and etiological testing and clinical adjudications will be performed as the reference standard to identify viral (including SARS-CoV-2 and HRV) and non-viral LRTI. Using an optimally retrained and parsimonious viral versus non-viral classifier, we will perform a feasibility analysis of incorporating pathogen detection and host-response classifier. Among samples with TLDA-based pathogen detection for SARS-CoV-2 or HRV, performance of the host- response classifier to distinguish viral versus non-viral LRTI will be assessed. Successful completion of these aims will result in the development of a novel diagnostic that integrates host and pathogen detection using a single, non-invasive NP sample to identify the etiology of LRTI. Translation of this assay to a rapid platform will help shift the current diagnostic paradigm for LRTI.", "keywords": [ "2019-nCoV", "Anti-Bacterial Agents", "Bacteria", "Bacterial Drug Resistance", "Bacterial Infections", "Biological", "Biological Assay", "Blood Tests", "Blood specimen", "Bronchoscopy", "COVID-19 detection", "Cause of Death", "Clinical", "Country", "Data", "Development", "Diagnostic", "Diagnostic Procedure", "Enrollment", "Etiology", "Fever", "Future", "Gene Expression", "Gene Targeting", "Genes", "Goals", "Hour", "Human", "Immune response", "Income", "Infection", "Influenza", "Lower Respiratory Tract Infection", "Machine Learning", "Manuscripts", "Methods", "Nasopharynx", "Nucleic Acids", "Pathogen detection", "Patients", "Performance", "Pilot Projects", "Polymerase Chain Reaction", "Prevalence", "Procedures", "Prospective cohort", "Reference Standards", "Research", "Resistance", "Respiratory Signs and Symptoms", "Respiratory Tract Infections", "Respiratory syncytial virus", "Rhinovirus", "Sampling", "Site", "Sputum", "Sri Lanka", "Testing", "Time", "Training", "Translating", "Upper respiratory tract", "Viral", "Virus", "Work", "adjudication", "biobank", "density", "design", "differential expression", "experience", "migration", "novel", "novel diagnostics", "pathogen", "peripheral blood", "prospective", "respiratory virus", "transcriptome sequencing", "translation assay" ], "approved": true } }, { "type": "Grant", "id": "15788", "attributes": { "award_id": "1R16GM159146-01", "title": "Building Reliable Vision-Language Assistant for Dermatology AI through Modeling Uncertainties in Multimodal LLMs", "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": 32871, "first_name": "WUHONG", "last_name": "PEI", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-12", "end_date": "2029-06-30", "award_amount": 175470, "principal_investigator": { "id": 32872, "first_name": "Zhiqiang", "last_name": "Tao", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2651, "ror": "", "name": "ROCHESTER INSTITUTE OF TECHNOLOGY", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Diagnosis delay is one of the key factors that lead to skin cancer death, especially for melanoma diagnosis during the COVID-19 pandemic. The long examination time and limited dermatological access have been the major roadblocks to the preventive treatment of skin cancers to lower the high mortality rate. Developing a clinical AI agent that can analyze digital skin images and provide timely, interactive text responses to patient symptoms and inquiries will significantly mitigate the nationwide dermatologist shortage, thereby improving the early diagnosis chance and teledermatology accessibility for melanoma as well as other skin diseases. Conventional dermatology AI methods mainly focus on medical image recognition to identify skin lesions and malignancies, falling short in visual-language assistance for remote healthcare services. A conversational diagnostic AI model, which is able to answer medical questions by sensing subtle visual patterns of skin disorders/cancers, is still in urgent need. The long-term goal of this research program is to develop a reliable large visual-language (VL) model that enables conversational Dermatology AI to facilitate early melanoma diagnosis and general skin care. The proposed research will generate accurate and interpretable clinical responses by finetuning Large Language Models – LLMs (e.g., the generative AI models deployed in ChatGPT) through answering questions and visual reasoning in multimodal contexts. Specifically, the project will realize three aims: 1) Build a new multimodal LLM specifically for dermatology to discern melanoma and other skin diseases and to automatically answer questions relevant to skin lesions. 2) Study uncertainties stemming from data bias and distribution shifts to enhance the reliability of LLM-powered AI diagnosis in multimodal contexts and teledermatology environments. 3) Determine the visual relevance in LLM decisions based on the rich public dermatological images with clinical text annotations. The proposed research will establish a new multimodal LLM that interweaves visual reasoning and uncertainties to advance Dermatology AI in broad VL assistance tasks, enabling automatic conversational diagnostic in teled- ermatology and providing new insights about how LLM understands skin lesions and dermatological knowledge. A pixelwise visual instruction tuning approach and a novel multi-level uncertainty quantification framework will be developed, providing technical foundations to benefit a wide range of LLM-based healthcare research. This project will be the first large visual-language research study that investigates LLM's intelligence and reliability in coping with multimodal dermatology contexts – visual skin lesions and text clinical annotations/dialogues. The success of this project will provide transformative AI techniques in assisting early melanoma diagnosis and remote skin care, leading to better teledermatology accessibility for patient treatments, reducing mortality from skin cancers through timely detection, and revolutionizing dermatological access in public healthcare systems.", "keywords": [ "Accounting", "Artificial Intelligence enhanced", "Behavior", "Benchmarking", "Benign", "COVID-19 pandemic", "Cellular Phone", "Cessation of life", "ChatGPT", "Clinical", "Cutaneous Melanoma", "Data", "Death Rate", "Dependence", "Dermatologic", "Dermatologist", "Dermatology", "Dermoscopy", "Detection", "Development", "Diagnosis", "Diagnostic", "Disease", "Early Diagnosis", "Environment", "Evaluation", "Foundations", "Generations", "Goals", "Grain", "Hallucinations", "Health Care", "Health Care Research", "Health Care Systems", "Image", "Instruction", "Intelligence", "Knowledge", "Language", "Learning", "Lesion", "Life", "Machine Learning", "Malignant Neoplasms", "Medical", "Medical Imaging", "Melanoma", "Methods", "Modeling", "Morphologic artifacts", "Noise", "Patients", "Pattern", "Preventive treatment", "Prognosis", "Protocols documentation", "Public Health", "Research", "Resolution", "Risk", "Series", "Skin", "Skin Cancer", "Skin Care", "Skin Imaging", "Skin Malignancy", "Symptoms", "Techniques", "Text", "Time", "Training", "Translations", "Uncertainty", "Underserved Population", "United States", "Vision", "Visual", "artificial intelligence model", "chatbot", "clinical imaging", "coping", "data acquisition", "design", "digital", "diverse data", "generative artificial intelligence", "health care service", "improved", "insight", "large language model", "lens", "mortality", "multimodality", "neglect", "novel", "programs", "remote health care", "research study", "response", "skin disorder", "skin lesion", "stem", "success", "teledermatology", "trustworthiness" ], "approved": true } } ], "meta": { "pagination": { "page": 1, "pages": 1405, "count": 14046 } } }