Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1384&sort=program_reference_codes
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=program_reference_codes", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=program_reference_codes", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1385&sort=program_reference_codes", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1383&sort=program_reference_codes" }, "data": [ { "type": "Grant", "id": "1666", "attributes": { "award_id": "2032273", "title": "EAGER: Coronavirus infection of human lung epithelium and leukocytes: mechanisms and treatment", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4367, "first_name": "Stephanie", "last_name": "George", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2021-05-31", "award_amount": 199999, "principal_investigator": { "id": 4368, "first_name": "Rabindra", "last_name": "Tirouvanziam", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 265, "ror": "https://ror.org/03czfpz43", "name": "Emory University", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 265, "ror": "https://ror.org/03czfpz43", "name": "Emory University", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "COVID-19, classified as a viral pandemic on 3/11/2020, has rapidly spread globally and caused over 250,000 deaths worldwide by 5/5/2020. COVID-19 symptoms range from mild fever and sore throat, to acute respiratory distress syndrome (ARDS) and death. SARS-CoV-2, the virus that causes COVID-19, avoids detection by the body’s immune system and enters the epithelial cells lining the airways, where it replicates and recruits a flood of immune cells, leading to what is called a “cytokine storm.” This “storm” can inflame the tissues surrounding the infection and eventually shut down breathing entirely. To date, basic studies on virus entry, propagation, and drug testing use non-human, non-lung models, like the Vero African green monkey kidney cell line, which severely limits efforts to understand COVID-19 disease and develop therapies. To address this problem, the objective of this project is to develop a platform emulating the human lung environment to study how SARS-CoV-2 interacts with the lung epithelial cells and with immune cells recruited to the lung and how therapies may modulate these interactions to benefit patients. The approach makes use of a model that the investigators have validated for studies of Cystic Fibrosis and Acute Respiratory Distress Syndrome (ARDS). The model features cultures of human airway epithelium grown on scaffolds that enable virus exposure, immune cell attraction and administration of existing drugs being considered for COVID-19 treatment. The platform developed will open broad opportunities for research not only on SARS-CoV-2, but also on other conditions (e.g., respiratory viruses or environmental exposures) that impact human lung physiology and health.The objective of this project is to engineer and validate a novel technological platform emulating the human lung environment to study how SARS-CoV-2, the causative agent of COVID-19 disease, interacts with epithelial cells lining the lung and with leukocytes recruited to the lung in response to infection, and how therapies may modulate these interactions to benefit patients. Unique features of the life-like platform include: (1) the use of human airway cells (both alveolar and bronchial epithelium) at ALI (Air-Liquid Interface) to propagate the virus over several days which enables the system to acquire the receptors and pathways relevant to human lung infections; (2) the use of human blood leukocytes transmigrated at chosen timepoints during infection, which is a key advantage over in vitro setups that use blood in lieu of lung leukocytes or animal models; and (3) due to the inclusion of all key components in the disease (virus, epithelium, leukocytes), the ability to assess drugs for their effects on the whole system, regardless of their primary target. The underlying hypothesis of the project is that SARS-CoV-2 causes pathology upon infection of the human lung by delaying interferon signaling, allowing the virus to infect monocytes, after which a breakdown in innate control occurs resulting in a cytokine storm, and in turn, overwhelming neutrophil recruitment and ARDS (Acute Respiratory Distress Syndrome). The research is organized under two Aims: (1) Determine the ability of the SARS-CoV-2 virus to enter and replicate in human lung epithelial cells and lung-recruited leukocytes and (2) Identify key pathways in human lung epithelial cells and lung-recruited leukocytes that can be modulated by existing drugs to prevent disease, e.g., remdesivir, baricitinib, anti-lL-6, anakinra, as well as a combination of remdesivir and baricitinibs which should impact both the virus and the inflammation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1685", "attributes": { "award_id": "2034755", "title": "EAGER: Protecting University Communities from COVID-19 with Model-based Risk Management", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4414, "first_name": "Georgia-Ann", "last_name": "Klutke", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-08-15", "end_date": "2022-07-31", "award_amount": 300000, "principal_investigator": { "id": 4417, "first_name": "Jeffrey W", "last_name": "Herrmann", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4415, "first_name": "Donald K", "last_name": "Milton", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4416, "first_name": "Hongjie", "last_name": "Liu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic has proven to be highly disruptive to the nation's higher education community, as universities struggle with safe and effective means to maintain students' progress toward their degrees. This EArly-concept Grant for Exploratory Research (EAGER) project will investigate risk-management of alternative delivery mechanisms that will enable universities to safely reopen, appropriately engaging students, faculty, and staff, while keeping the broader university community, including the neighboring businesses that serve the campus, as safe as possible from disease outbreaks. The research will generate new knowledge in the area of operational risk management and decision making related to public health and will assist university administrators and public health officials in evaluating risk management strategies to operate safely during the COVID-19 pandemic. This EAGER award supports research on a comprehensive, data-enabled disease spread model tailored specifically to university demographics and operations. The research will yield (1) novel operational risk management formulations that specifically take participant behavior and university and surrounding community demographics into account, (2) investigations into different strategic options for educational delivery in a university community, and (3) methods to integrate empirical and conceptual models of disease spread with dynamic data in this environment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1686", "attributes": { "award_id": "2032769", "title": "EAGER: Applying Paleoecosystem-Mass Extinction Theory to Socio-Economic Systems During COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4418, "first_name": "Dena", "last_name": "Smith", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2022-05-31", "award_amount": 242627, "principal_investigator": { "id": 4419, "first_name": "Peter D", "last_name": "Roopnarine", "orcid": "https://orcid.org/0000-0002-9811-1176", "emails": "[email protected]", "private_emails": "", "keywords": "['Earth sciences']", "approved": true, "websites": "['https://www.calacademy.org/staff/ibss/invertebrate-zoology-and-geology/peter-ro…', 'https://www.preprints.org/manuscript/202101.0200/v1']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 656, "ror": "https://ror.org/02wb73912", "name": "California Academy of Sciences", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 656, "ror": "https://ror.org/02wb73912", "name": "California Academy of Sciences", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The project will apply a developing theory regarding the behavior of paleoecosystems as complex adaptive systems during mass extinctions, to the response of human and socio-economic systems (SESs) during the COVID-19 pandemic. Socio-economic systems and ecosystems are examples of complex, adaptive systems. Such systems underlie much of our world’s complexity, including human genetic systems, and the global economy. System behavior depends on the number of agents, their interactions, external influences, and how agents are organized into sub-groups. In ecosystems, the agents are species, interacting through mechanisms like predation or competition, and groups of species form when they have overlapping interactions. The behavior of a complex system is difficult to understand and forecast because of structural complexity, but a lot may be learned if the system is subjected to extreme stress. This has been the case when ecosystems in the past suffered mass extinctions, driven by enormous events such as asteroid impact. It is also the case for human SESs stressed by the COVID-19 pandemic and its socio-economic fallout. Studies have shown that ecosystem resilience during mass extinctions was determined by structural complexity, and that proper recovery depended on how structural complexity was re-evolved. This project will use similarities between ecosystems and SESs to model the impact of pandemic-driven mortality, morbidity, and economics.The project will develop network models of Californian and national SESs, relating employment organized by industrial sectors to system dynamics. The pandemic’s impact on selected SESs are modeled with numbers of persons employed in sectors, and we will identify critical sectors, forecasting future system dynamics. SES recovery will be modeled as employment recovery, comparing three recovery strategies: opportunistic recovery distributed randomly among sectors (random recovery), distributed fairly among sectors (equitable recovery), or distributed unevenly to maximize recovery rate and magnitude (strategic recovery). The latter strategy will be modeled using a Markov Chain Monte Carlo Metropolis-Hastings machine learning method.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1698", "attributes": { "award_id": "2029677", "title": "EAGER: Engineered nano-scale barrier to prevent viral infections", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4445, "first_name": "Leon", "last_name": "Esterowitz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2022-04-30", "award_amount": 299999, "principal_investigator": { "id": 4447, "first_name": "Mark S", "last_name": "Humayun", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 152, "ror": "https://ror.org/03taz7m60", "name": "University of Southern California", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4446, "first_name": "Gianluca", "last_name": "Lazzi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 152, "ror": "https://ror.org/03taz7m60", "name": "University of Southern California", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "This project proposes to use in silico simulations to engineer nanoscale, biocompatible, protective barrier that will enhance our first line of defenses - prevention of pathogenic infection from entering and infecting the host. The principal investigator aims to develop a topical method that will enhance protection against virus attachment onto the nasal and oral as well as conjunctival epithelial cells, while preserving normal physiology and biochemistry. The project team will use computer models to engineer delivery devices to produce the optimal particle characteristics to maximally prevent microbial infection. If successful, this project can lead to paradigm changing alternatives to reducing public health risk to air borne infections like COVID-19 and seasonal flu which may be associated with devastating effects on the United States and World economy. The proposed approach will be swiftly conducted to present realistic solutions that may be useable in the face of this COVID-19 pandemic as well as future flu viruses of similar magnitude.This research will fundamentally contribute to modeling the interactions between viral membranes and nanoscale barriers. The production of an innovative nanoscale biodegradable barrier may reduce the socioeconomic and public health burden significantly by lowering the risk of viral infection during the flu season or pandemics. The project team comprise of an interdisciplinary team that include engineers, ophthalmologists, molecular biologist, virologist and pharmacologist to explore a problem that could have a tremendous impact on the way we respond to seasonal flu or pandemics. Besides the potential benefits to reduce COVID-19 and influenza related deaths in the US and worldwide, the proposed work will afford us the opportunity to train engineering and biomedical students in a highly interdisciplinary research activity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1712", "attributes": { "award_id": "2029900", "title": "EAGER: Collaborative Research: Design of Inhibitors for ORF7a and ORF7b Oligomerization in COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4483, "first_name": "Catalina", "last_name": "Achim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-15", "end_date": "2022-05-31", "award_amount": 150000, "principal_investigator": { "id": 4484, "first_name": "Jeffery B", "last_name": "Klauda", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "With this award, the Chemistry of Life Processes Program in the Chemistry Division and the Chemical and Biochemical Engineering Program in the Chemical, Bioengineering, Environmental and Transport Systems Division are funding Dr. Bryan Berger (University of Virginia) and Dr. Jeffery Klauda (University of Maryland) to investigate two proteins named ORF7a and OR7b from the COVID19 virus that have been implicated in how harmful the virus is to its host, e.g. the human cells. The research will focus on how these two proteins form larger protein complexes that in turn affect the interactions between the virus and the infected cells and influence the immune response of the host. The research informs the development of peptides that could be used to probe the viral propagation. The research is based on the use of a combination of computational and experimental methods. Dr. Berger and Dr. Klauda distribute to the scientific community free of charge through Addgene the plasmids and associated protocols developed for this project, thus enabling the global scientific community that works on finding a solution to the current pandemic and to minimizing the possibility of future outbreaks to quickly use the outcomes of their research. This work will provide training for post-doctoral fellows working on critical challenges using state-of-the-art experimental and computational methods. The results of the research will be disseminated by the team to the greater community through conferences and workshops at University of Virginia and University of Maryland and through publications. The researchers also plan to inform and educate students on possible mechanisms of virus transmission and prevention by participation in existing outreach programs at their Institutions.This research project seeks to understand the basis of specificity for transmembrane and juxtamembrane oligomerization of ORF7a with BST-2 and for homooligomerization of ORF7b. Using bacterial transcriptional assays for membrane protein dimerization based on the E. coli AraC protein (AraTM and DN-AraTM assays), the researches determine specific amino acid residues and structural motifs responsible for the protein oligomerization in bacterial membranes. This knowledge informs computational models for formation of BST-2/ORF7a heterooligomers and ORF7b homooligomers. In turn, the computational models are used to make critical new predictions of sequences for transmembrane peptides that could influence protein-protein interactions involving ORF7a and ORF7b. These predictions and the properties of the peptides are tested by synthesizing peptide libraries and using AraTM, DN-AraTM, and mammalian, cell-based fluorescence resonance energy transfer assays. Validation of candidate sequences are achieved using mammalian cell-based assays for BST-2 function and apoptosis. The results of these studies could provide high-resolution, experimentally validated models for OR7a and ORF7b homo and heterooligomerization, as well as peptide sequences that can be used to probe the roles of ORF7a and ORF7b in viral propagation in vivo.This grant is being awarded using funds made available by the Coronavirus Aid, Relief, and Economic Security (CARES) Act supplement allocated to MPS and ENG.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1713", "attributes": { "award_id": "2029895", "title": "EAGER: Collaborative Research: Design of Inhibitors for ORF7a and ORF7b Oligomerization in COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4485, "first_name": "Catalina", "last_name": "Achim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-15", "end_date": "2022-05-31", "award_amount": 150000, "principal_investigator": { "id": 4486, "first_name": "Bryan W", "last_name": "Berger", "orcid": "https://orcid.org/0000-0002-6135-8677", "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": "['http://www.addgene.org/']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 517, "ror": "", "name": "University of Virginia Main Campus", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 517, "ror": "", "name": "University of Virginia Main Campus", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "With this award, the Chemistry of Life Processes Program in the Chemistry Division and the Chemical and Biochemical Engineering Program in the Chemical, Bioengineering, Environmental and Transport Systems Division are funding Dr. Bryan Berger (University of Virginia) and Dr. Jeffery Klauda (University of Maryland) to investigate two proteins named ORF7a and OR7b from the COVID19 virus that have been implicated in how harmful the virus is to its host, e.g. the human cells. The research will focus on how these two proteins form larger protein complexes that in turn affect the interactions between the virus and the infected cells and influence the immune response of the host. The research informs the development of peptides that could be used to probe the viral propagation. The research is based on the use of a combination of computational and experimental methods. Dr. Berger and Dr. Klauda distribute to the scientific community free of charge through Addgene the plasmids and associated protocols developed for this project, thus enabling the global scientific community that works on finding a solution to the current pandemic and to minimizing the possibility of future outbreaks to quickly use the outcomes of their research. This work will provide training for post-doctoral fellows working on critical challenges using state-of-the-art experimental and computational methods. The results of the research will be disseminated by the team to the greater community through conferences and workshops at University of Virginia and University of Maryland and through publications. The researchers also plan to inform and educate students on possible mechanisms of virus transmission and prevention by participation in existing outreach programs at their Institutions.This research project seeks to understand the basis of specificity for transmembrane and juxtamembrane oligomerization of ORF7a with BST-2 and for homooligomerization of ORF7b. Using bacterial transcriptional assays for membrane protein dimerization based on the E. coli AraC protein (AraTM and DN-AraTM assays), the researches determine specific amino acid residues and structural motifs responsible for the protein oligomerization in bacterial membranes. This knowledge informs computational models for formation of BST-2/ORF7a heterooligomers and ORF7b homooligomers. In turn, the computational models are used to make critical new predictions of sequences for transmembrane peptides that could influence protein-protein interactions involving ORF7a and ORF7b. These predictions and the properties of the peptides are tested by synthesizing peptide libraries and using AraTM, DN-AraTM, and mammalian, cell-based fluorescence resonance energy transfer assays. Validation of candidate sequences are achieved using mammalian cell-based assays for BST-2 function and apoptosis. The results of these studies could provide high-resolution, experimentally validated models for OR7a and ORF7b homo and heterooligomerization, as well as peptide sequences that can be used to probe the roles of ORF7a and ORF7b in viral propagation in vivo.This grant is being awarded using funds made available by the Coronavirus Aid, Relief, and Economic Security (CARES) Act supplement allocated to MPS and ENG.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1744", "attributes": { "award_id": "2038087", "title": "EAGER: RCN: Wastewater Surveillance of SARS-CoV-2", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4572, "first_name": "Mamadou", "last_name": "Diallo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-08-01", "end_date": "2021-12-31", "award_amount": 299995, "principal_investigator": { "id": 4576, "first_name": "Kyle", "last_name": "Bibby", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 4573, "first_name": "Alexandria", "last_name": "Boehm", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4574, "first_name": "Rolf U", "last_name": "Halden", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4575, "first_name": "Jeseth Delgado", "last_name": "Vela", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 171, "ror": "https://ror.org/00mkhxb43", "name": "University of Notre Dame", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic has infected >10 million people and disrupted the global economy. Tracking the spread of the disease is critical to protecting public health and assessing the success of pandemic response. Wastewater surveillance for COVID-19 is based on measuring genes from SARS-CoV-2 (the virus that causes COVID-19) in municipal wastewater. This information tells us whether COVID-19 is present and how it is spreading in a community. While this technique holds promise, major knowledge gaps must be addressed to allow widespread application of this technique. The goal of this Research Coordination Network (RCN) project is to connect researchers from across the Nation who are studying this problem to maximize the discovery potential. This RCN will be completely virtual to enable widespread participation during the pandemic and allow for ‘open-door’ participation of any interested research groups or individuals. Specific activities include virtual conferences, workshops, training videos, and seminars for dissemination of knowledge. Data will be maintained in a centralized data repository to facilitate sample exchange and archiving. Exchange and knowledge transfer will be facilitated on a global scale by connecting with other international wastewater surveillance networks and efforts. Beyond aiding in the COVID-19 pandemic response, the proposed RCN will contribute to the scientific literacy of the Nation through student and postdoc training, data sharing, and broad dissemination of research findings. The infectious agent SARS-CoV-2, a member of the Coronavirus family, is the causative agent of COVID-19, a respiratory illness first detected in Wuhan, China in December 2019. COVID-19 has since grown into a global pandemic, causing >10M illnesses and >500K deaths globally. The outbreak has led to severe economic impacts resulting from interventions such as social distancing and stay at home ordinances to slow the spread of the disease. A significant challenge in responding to COVID-19 is the difficulty of measuring the prevalence of COVID-19 in a given community. SARS-CoV-2 RNA is shed in the stool of infected individuals, thereby affording the opportunity to rapidly monitor for coronavirus presence in centralized wastewater collection systems. Wastewater surveillance for SARS-CoV-2 RNA has thus emerged as an alternative for rapid assessment of COVID-19 presence within a community. However, despite its potential for efficient surveillance, there are numerous critical research questions that remain to be addressed before widespread adoption of this technique can occur. The team of investigators from the University of Notre Dame, Howard University, Stanford University, and Arizona State University will convene a one-year Research Coordination Network (RCN) effort with the goal of connecting teams from across the country studying SARS-CoV-2 in wastewater to address these knowledge gaps. Network activities will be held virtually to maximize participation during the pandemic. Specific activities include virtual conferences facilitated by the Water Research Foundation, workshops, training videos, and seminars for dissemination of knowledge. Exchange and knowledge transfer will be facilitated on a global scale by connecting with other international wastewater surveillance networks and efforts. Successful completion of this RCN will accelerate the transfer of knowledge leading to more rapid adoption of best practices that can facilitate the development of wastewater surveillance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1758", "attributes": { "award_id": "2029847", "title": "EAGER: Breath-Based Early and Fast Detection of COVID-19 Infection", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 4619, "first_name": "Stephanie", "last_name": "George", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2022-05-31", "award_amount": 199359, "principal_investigator": { "id": 4622, "first_name": "Pelagia", "last_name": "Gouma", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": "['https://acrl.osu.edu', 'https://news.osu.edu/ohio-state-researchers-testing-breathalyzer-to-detect-covi…', 'https://www.cnbc.com/2020/06/15/sacramento-kings-exploring-breathalyzer-concept…', 'https://ceramics.org/ceramic-tech-today/materials-innovations/researchers-use-b…', 'https://interestingengineering.com/researchers-testing-revolutionary-breathalyz…', 'https://www.cleveland19.com/2020/06/08/could-breathalyzer-detect-covid-osu-rese…', 'https://www.medicaldesignandoutsourcing.com/ohio-state-researchers-developing-b…']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 308, "ror": "", "name": "Ohio State University", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4620, "first_name": "Milutin", "last_name": "Stanacevic", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 4621, "first_name": "Andrew", "last_name": "Bowman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 308, "ror": "", "name": "Ohio State University", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true }, "abstract": "AbstractThe aim of this research project is to enable early and rapid detection of infection COVID-19 by sampling human breath. COVID-19 disease is a pandemic currently, according to the World Health Organization (WHO) caused by the 2019-nCoV virus. Without innate immunity to the novel virus and with the lack of therapeutic means to treat it, the only way to contain the spread of this disease further is through early diagnosis. However, for many infected individuals the disease remains asymptomatic, yet they can potentially transmit COVID-19 and unknowingly infect more of the population. This project will lead to new approach to diagnose COVID-19 infection from sampling human breath. The investigator proposes to use a disruptive approach to infectious disease diagnosis and to the detection of COVID-19 specifically. This approach involves sampling the breath of human-- or animal in the proposed work-- subjects for three gaseous signaling metabolites (i.e. COVID-19 biomarkers). The hypothesis of the project is that the magnitude of the relative change in these biomarkers upon the subject’s infection with the 2019-nCoV virus provides an early and distinct signal of this infection. The PI will test this hypotheses by producing a three-sensor array, utilizing selective resistive gas sensors based on binary metal oxides, and by testing the breath of swine infected by a beta-coronavirus as well as the breath of humans infected by COVID-19. Measurements will be made repeatedly on definitively or potentially infected subjects to map the rise and fall of the biomarkers over time. Correlating the measurements made with the relative concentration of pro-inflammatory cytokines released in them is expected to produce a diagnostic tool for the pandemic infection. The diagnostic prototype tool will be equipped with wireless capability for rapid deployment as point-of-care, early detection means. The proposed research and technology aim to set the stage for the diagnostics of the future. Establishing the pathway for the effective diagnosis of coronavirus diseases through biomarker monitoring and establishing the specifications required for the early detection of COVID-19 before any symptoms appear are expected to be the major outcomes of the proposed research. Promoting breath analysis as a first response, on-site, point-of-care, personalized diagnostics method is envisioned. Training students working on this project on interdisciplinary research is an added benefit of this research project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "2107", "attributes": { "award_id": "2031806", "title": "EAGER: Investigation of host and viral factors that influence the severity of coronaviral disease", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 5673, "first_name": "Joanna", "last_name": "Shisler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2022-09-30", "award_amount": 299999, "principal_investigator": { "id": 5676, "first_name": "James D", "last_name": "Macy", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 5674, "first_name": "Susan R", "last_name": "Compton", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 5675, "first_name": "Carmen J", "last_name": "Booth", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "Three coronaviruses (SARS-CoV1, MERS-CoV, and SARS-CoV2) have emerged from animals causing severe respiratory disease in humans. Little is known about the virus-host interactions which control disease severity and transmission, leaving society unprepared for the COVID-19 pandemic. An animal model that closely mimics SARS-CoV-2 infection and pathogenesis is needed to better inform and educate about the science of virus transmission and prevention. Mice are infected with their own, mouse-specific coronavirus [mouse hepatitis virus (MHV)] that causes respiratory disease and affects other organs, such as the heart, liver and spleen, like COVID-19. This proposal will utilize a MHV model of COVID-19 to understand disease progression and the factors involved using controlled conditions. The mouse model takes advantage of available mouse genetic tools, immunologic reagents, and detailed pathologic assessments to identify host factors, such as the type of immune cell infiltrates and cytokines produced that are associated with different disease severities. This analysis will provide insight into protective and deleterious host responses, which can identify processes to target for therapeutics. The development of this model system has the potential to be an efficient and cost effective tool to identify and screen treatment and prevention strategies that warrant escalation to more specific COVID-19 models, thereby making the best use of the limited infrastructure resources associated with the ABSL-3 requirements of actual SARS-CoV2 use. This is a Broader Impact because it will benefit society in the quest for COVID-19 therapeutics and vaccines. Models of all levels of SARS-CoV2 disease in genetically diverse populations are urgently needed. It is hypothesized that the host and virus factors controlling the severity of coronavirus respiratory infections can be identified using natural murine coronavirus infections in diverse, yet genetically defined cohorts of mice. MHV are natural pathogens of mice that are well adapted to their host and vary in both their tropisms and their disease phenotype. The range of pathological lesions and host responses caused by MHV-1 and MHV-A59, with different virulence in the respiratory tract, will be characterized. The eight genetically diverse Collaborative Cross founder mouse strains will be used to represent the genetic diversity seen in large human populations. These studies will focus on lung pathology, but the heart, liver, kidney and spleen will also be evaluated. Mice will be inoculated with MHV-1 or MHV-A59. Tissues will be examined for pathologic changes. Fibrosis and immune cell infiltrates will be characterized using histochemical stains and immunohistochemistry. Viral titers, serum chemistry, coagulation, neutralizing antibodies and cytokines will be measured. Correlations between MHV strain, mouse strain, viral load, clinical disease, pathological lesions, and immune reactions will be determined. These studies are the first step to increase knowledge about the biology of SARS-CoV-2 infections. This RAPID award is made by the Symbiosis, Defense, and Self-recognition Program in the BIO Division of Integrative Organismal Systems, and, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act. It was co-reviewed by the BIO Division of Molecular and Cellular Biology Genetic Mechanisms cluster.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "2121", "attributes": { "award_id": "2032276", "title": "EAGER: Collaborative Research: Rapid Production of Geospatial Network Inputs for Spatially Explicit Epidemiological Modeling of COVID-19 in the USA", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [ "096Z", "7916" ], "program_officials": [ { "id": 5715, "first_name": "Katharina", "last_name": "Dittmar", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2023-05-31", "award_amount": 100000, "principal_investigator": { "id": 5717, "first_name": "Andrew J", "last_name": "MacDonald", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 320, "ror": "", "name": "University of California-Santa Barbara", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 5716, "first_name": "Daniel", "last_name": "Sousa", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 320, "ror": "", "name": "University of California-Santa Barbara", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Dynamical computer models of disease transmission are used to understand and predict how infectious diseases spread through host populations. Maps of population distribution, mobility, and travel corridors are critical components of many of these models. However, accurately determining the spatial distribution of people is difficult because most sources of data (e.g., census) indicate only approximately where people reside, rather than where they work and go. Census data, in particular, are also aggregated in a way that provides fine spatial detail only in densely populated urban areas. In suburban and rural areas, census maps provide only the total number of people living in each census unit (e.g., a U.S. county), but do not show where people live and work. This research will fuse detailed satellite images of night light emitted from cities, towns and travel corridors with census counts and mobility data to produce more detailed population maps for epidemiologists to use to more accurately simulate the transmission of communicable diseases like COVID-19. The proposed collaboration will bring together expertise from geospatial dynamics and remote sensing with disease ecology and epidemiology to produce boundary spanning science with potential to advance both fields. Further, the proposed project will support two early career scientists as well as undergraduate student involvement in research.When air and vehicle travel are significantly reduced, the accuracy and detail of population movement and spatial connectedness assumes greater importance for modeling epidemic spread. Spatial networks derived from co-analysis of geospatial data (settlement and infrastructure density from remotely sensed night light and population density from census enumerations) can provide more accurate spatial domains than the administrative units (e.g., counties) used to aggregate and analyze health data. In addition, the structure and connectivity of these spatial networks can be used to quantify fundamental parameters of network structure that influence disease spread. This research will develop a progressively refined suite of network maps for use with epidemiological models. The research team, composed of geoscientists, disease ecologists and epidemiologists will develop a standardized protocol with analytic procedures and tools for production of these maps structured so as to be suited for quantitative spatiotemporal analysis of SARS-CoV-2 infections in the U.S., including detailed analyses of the New York and Los Angeles metro areas. Network flow parameters among population centers will be estimated using agent-based modeling, establishing a complete geospatial network consisting of population and mobility constraints within cities, and population fluxes among cities. Population and network flow estimates will be input directly into spatially explicit COVID-19 transmission models, and will be abstracted into boundary conditions that can streamline future epidemiological models. This RAPID award is made by the Ecology and Evolution of Infectious Disease Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1384, "pages": 1392, "count": 13920 } } }