Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1384&sort=abstract
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=abstract", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1405&sort=abstract", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1385&sort=abstract", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1383&sort=abstract" }, "data": [ { "type": "Grant", "id": "8089", "attributes": { "award_id": "75N92021C00001-0-9999-1", "title": "TO UPDATE THE PERFORMANCE WORK STATEMENT FOR RADX TECH PROJECT NO. 2643 - PATHOGENDX, INC. - PATHOGENDX COVID-19 MICROARRAY CLADE VARIANT DETECTION TE", "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": [], "start_date": "2021-02-22", "end_date": "2022-02-21", "award_amount": 8919208, "principal_investigator": { "id": 23976, "first_name": "MILAN", "last_name": "PATEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "With PathogenDx's solution (DetectX-Rv), over the next four months, we will deliver a 25 fold increase in test capacity for the nation without increasing lab-real-estate footprint, without adding endless lines of testing systems that depreciate instantly, upholding the level of accurate testing needed, and a solution that can ‘flex’ to the demands of the market with the different sized SBS plates. What we propose is quadrupling test capacity twice on the same actual test substrate ~ optimizing the same SBS plate from 12 well array slides to 96 wells ultimately to a 384 well format in less than 4 months. Exercising this strategy will deliver 4.15M tests per month, and result in cost savings of 55% and 70% per test. As a comparison, to deploy the same capacity using qRT-PCR technology, it will cost RaDx five times as much in CapEx and three times more per test cost.", "keywords": [ "COVID-19", "Cost Savings", "Exercise", "Performance at work", "Quantitative Reverse Transcriptase PCR", "RADx", "RADx Tech", "Slide", "System", "Technology", "Testing", "Time", "Update", "cost", "variant detection" ], "approved": true } }, { "type": "Grant", "id": "8090", "attributes": { "award_id": "75N92021C00001-P00004-9999-1", "title": "TO UPDATE THE PERFORMANCE WORK STATEMENT FOR RADX TECH PROJECT NO. 2643 - PATHOGENDX, INC. - PATHOGENDX COVID-19 MICROARRAY CLADE VARIANT DETECTION TE", "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": [], "start_date": "2021-02-22", "end_date": "2022-12-31", "award_amount": 590553, "principal_investigator": { "id": 23976, "first_name": "MILAN", "last_name": "PATEL", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1095, "ror": "", "name": "PATHOGENDX", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "With PathogenDx's solution (DetectX-Rv), over the next four months, we will deliver a 25 fold increase in test capacity for the nation without increasing lab-real-estate footprint, without adding endless lines of testing systems that depreciate instantly, upholding the level of accurate testing needed, and a solution that can ‘flex’ to the demands of the market with the different sized SBS plates. What we propose is quadrupling test capacity twice on the same actual test substrate ~ optimizing the same SBS plate from 12 well array slides to 96 wells ultimately to a 384 well format in less than 4 months. Exercising this strategy will deliver 4.15M tests per month, and result in cost savings of 55% and 70% per test. As a comparison, to deploy the same capacity using qRT-PCR technology, it will cost RaDx five times as much in CapEx and three times more per test cost.", "keywords": [ "COVID-19", "Cost Savings", "Exercise", "Performance at work", "Quantitative Reverse Transcriptase PCR", "RADx", "RADx Tech", "Slide", "System", "Technology", "Testing", "Time", "Update", "cost", "variant detection" ], "approved": true } }, { "type": "Grant", "id": "10614", "attributes": { "award_id": "1R35GM147423-01", "title": "Physics-based characterization of functionally relevant protein conformational dynamics", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 11852, "first_name": "Anne", "last_name": "Gershenson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-15", "end_date": "2027-08-31", "award_amount": 221612, "principal_investigator": { "id": 26656, "first_name": "Mahmoud", "last_name": "Moradi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 749, "ror": "https://ror.org/05jbt9m15", "name": "University of Arkansas at Fayetteville", "address": "", "city": "", "state": "AR", "zip": "", "country": "United States", "approved": true }, "abstract": "With recent advances in structural biology and supercomputing technology, all-atom molecular dynamics (MD) simulation technique has gained momentum as a prominent tool for the study of protein structural dynamics. Brute-force MD, however, is not capable of adequately sampling most functionally relevant biomolecular processes such as large-scale protein conformational changes. Various approaches have been developed over the last three decades to address the “timescale gap” that hinders the use of MD in real- world applications. Free energy calculation methods, enhanced sampling techniques, and path-finding algorithms are examples of umbrella terms that describe many of these methods. This project specifically aims at employing, tailoring, and fine-tuning state-of-the-art enhanced sampling and path-finding algorithms to address important biological and biomedical questions. The overall aim of this project is to develop and employ robust and practical sampling and analysis protocols to study functionally relevant conformational changes of various proteins from fibroblast growth factor to coronavirus spike protein. Our proposed methodological framework specifically takes advantage of (1) robust theoretical formalisms rooted in nonequilibrium statistical mechanics and differential geometry; (2) system-specific enhanced sampling protocols that are tunable for the specific problem at hand; and (3) and integrative and synergistic approach to experimental (specifically smFRET) and computational (specifically MD) techniques. Some of the systems proposed to be studied here include proton-coupled oligopeptide transporters, influenza hemagglutinin, ATP-binding transporters, coronavirus spike proteins, mechanosensitive channel of large conductance, membrane insertase YidC, serotonin transporter, and fibroblast growth factor (FGF) protein. The common theme in all of these projects is the large-scale conformational changes involved in the function of these proteins. The successful use of the methodology proposed in this project will allow the characterization of these conformational changes at the molecular level and pave the groundwork for the routine application of state-of-the-art enhanced sampling techniques in the study of real world biological problems.", "keywords": [ "Address", "Algorithms", "Binding", "Biological", "Computing Methodologies", "Coronavirus spike protein", "Coupled", "Fibroblast Growth Factor", "Free Energy", "Growth Factor", "Hand", "Human", "Influenza Hemagglutinin", "Membrane", "Methodology", "Methods", "Molecular", "Molecular Conformation", "Oligopeptides", "Physics", "Plant Roots", "Play", "Process", "Protein Conformation", "Proteins", "Protocols documentation", "Protons", "Role", "Sampling", "Statistical Mechanics", "Supercomputing", "System", "Techniques", "Technology", "base", "differential geometry", "molecular dynamics", "protein function", "real world application", "serotonin transporter", "single-molecule FRET", "structural biology", "tool" ], "approved": true } }, { "type": "Grant", "id": "5876", "attributes": { "award_id": "3R01AI127203-05S1", "title": "BDD CIS: Big Data Driven Clinical Informatics & Surveillance - A Multimodal Database Focused Clinical, Community, & Multi-Omics Surveillance Plan for COVID19", "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": 20120, "first_name": "Rosemary G", "last_name": "McKaig", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-12", "end_date": "2023-05-31", "award_amount": 626275, "principal_investigator": { "id": 20121, "first_name": "Xiaoming", "last_name": "Li", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 20122, "first_name": "Bankole", "last_name": "Olatosi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 930, "ror": "", "name": "UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true }, "abstract": "With South Carolina’s population already being vulnerable to poor health as evidenced by poor national health rankings, challenging rural geography and health professional shortages, the impact of the novel Coronavirus Disease 2019 (COVID-19) will be long lasting in the state. Patient morbidity and mortality rates already continue to increase, with ongoing economic damage to health systems and businesses. The speed of transmission and geographical spread of COVID-19 across South Carolina and the United States is alarming, which combined with the novel nature of the disease justifies the need for accelerated research to combat this pandemic. As clinicians and frontline health workers battle to save lives, creating a data environment that accelerates research is key, and necessary to fight against the disease. This proposal will build the capacity for accelerated research and intelligence gathering by coalescing multiple state partners and leveraging relevant data for discoveries around COVID-19. To accomplish this, this proposal aims to (1) create a de-identified linked database system via a HIPAA compliant secure server to collate surveillance, clinical, multi-omics and geospatial data on both COVID-19 patients and health workers treating COVID-19 patients in South Carolina; (2) examine the natural history of COVID-19 including transmission dynamics, disease progression, and geospatial visualization; and (3) identify important predictors of short- and long-term clinical outcomes of COVID-19 patients in South Carolina using machine learning algorithms. These aims will be accomplished through collaborations with multiple state agencies and stakeholders relevant to COVID-19 and the creation of a secure HIPAA compliant database that allow for coalescing relevant data in a timely fashion, combined with leveraging of statewide integrated data warehouse capabilities.", "keywords": [ "Big Data", "Businesses", "COVID-19", "COVID-19 patient", "COVID-19 surveillance", "COVID-19 treatment", "Clinical", "Clinical Informatics", "Collaborations", "Communities", "Confidentiality of Patient Information", "Coupled", "Data", "Data Discovery", "Database Management Systems", "Databases", "Disease", "Disease Progression", "Disease Surveillance", "Disease susceptibility", "Economics", "Environment", "Geography", "Health", "Health Insurance Portability and Accountability Act", "Health Professional", "Health system", "Individual", "Intelligence", "Intervention", "Learning", "Link", "Monitor", "Morbidity - disease rate", "Multiple Partners", "Natural History", "Nature", "Outcome", "Patients", "Population", "Recovery", "Research", "Rural", "Secure", "South Carolina", "Speed", "Techniques", "Time", "United States", "Visualization", "big-data science", "combat", "data infrastructure", "data warehouse", "disability", "fight against", "health data", "innovation", "machine learning algorithm", "mortality", "multimodality", "multiple data sources", "multiple omics", "novel", "novel coronavirus", "pandemic disease", "patient privacy", "systems research", "transmission process", "virology" ], "approved": true } }, { "type": "Grant", "id": "7206", "attributes": { "award_id": "3R01AI127203-04S1", "title": "BDD CIS: Big Data Driven Clinical Informatics & Surveillance - A Multimodal Database Focused Clinical, Community, & Multi-Omics Surveillance Plan for COVID19", "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": 6828, "first_name": "Rosemary G", "last_name": "McKaig", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-06-20", "end_date": "2022-05-31", "award_amount": 626275, "principal_investigator": { "id": 4919, "first_name": "Xiaoming", "last_name": "Li", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 930, "ror": "", "name": "UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 11973, "first_name": "Bankole", "last_name": "Olatosi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 930, "ror": "", "name": "UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true }, "abstract": "With South Carolina’s population already being vulnerable to poor health as evidenced by poor national health rankings, challenging rural geography and health professional shortages, the impact of the novel Coronavirus Disease 2019 (COVID-19) will be long lasting in the state. Patient morbidity and mortality rates already continue to increase, with ongoing economic damage to health systems and businesses. The speed of transmission and geographical spread of COVID-19 across South Carolina and the United States is alarming, which combined with the novel nature of the disease justifies the need for accelerated research to combat this pandemic. As clinicians and frontline health workers battle to save lives, creating a data environment that accelerates research is key, and necessary to battle the disease. Access to such information will equip frontline health workers to continue the fight against the disease. This proposal will build the capacity for accelerated research and intelligence gathering by coalescing multiple state partners and leveraging relevant data for discoveries around COVID-19. To accomplish this, this proposal aims to (1) create a de-identified linked database system via REDCap and a mobile application (app) to collate surveillance, clinical, multi-omics and geospatial data on both COVID-19 patients and health workers treating COVID-19 patients in South Carolina; (2) examine the natural history of COVID-19 including transmission dynamics, disease progression, and geospatial visualization; and (3) identify important predictors of short- and long-term clinical outcomes of COVID-19 patients in South Carolina using machine learning algorithms. These aims will be accomplished through collaborations with multiple state agencies and stakeholders relevant to COVID-19 and the creation of a REDCap database and mobile app that allow for coalescing relevant data in a timely fashion, combined with leveraging of statewide integrated data warehouse capabilities.", "keywords": [ "2019-nCoV", "Active Learning", "Affect", "Algorithms", "American", "Architecture", "Archives", "Big Data", "Big Data Methods", "Businesses", "COVID-19", "COVID-19 pandemic", "Chest", "Classification", "Clinical", "Clinical Informatics", "Collaborations", "Common Cold", "Communities", "Complex", "Computer software", "Confidentiality of Patient Information", "Coupled", "Data", "Data Analytics", "Data Discovery", "Data Sources", "Database Management Systems", "Databases", "Diagnosis", "Disease", "Disease Progression", "Disease Surveillance", "Disease susceptibility", "Early Diagnosis", "Economics", "Ensure", "Environment", "Future", "Geography", "Health", "Health Insurance Portability and Accountability Act", "Health Professional", "Health Sciences", "Health system", "High Resolution Computed Tomography", "Image", "Individual", "Intelligence", "Intervention", "Learning", "Life Style", "Link", "Literature", "Monitor", "Morbidity - disease rate", "Multiple Partners", "Natural History", "Nature", "Outcome", "Patients", "Pattern", "Population", "Precision Health", "Provider", "Recovery", "Reporting", "Reproducibility", "Research", "Research Personnel", "Rural", "SARS coronavirus", "Secure", "Series", "Source", "South Carolina", "Speed", "System", "Techniques", "Time", "United States", "Virus", "Visualization", "Work", "big-data science", "combat", "data infrastructure", "data management", "data warehouse", "deep learning", "demographics", "disability", "disease natural history", "disease transmission", "experience", "fight against", "gene therapy", "health data", "imaging modality", "improved", "innovation", "machine learning algorithm", "mobile application", "mortality", "multimodal data", "multimodality", "multiple data sources", "multiple omics", "novel", "novel coronavirus", "novel virus", "pandemic disease", "patient privacy", "precision medicine", "response", "systems research", "time use", "transmission process", "trend", "virology" ], "approved": true } }, { "type": "Grant", "id": "2558", "attributes": { "award_id": "2002313", "title": "Non-Markovian Diffusion Imaging", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Chemical Measurement & Imaging" ], "program_reference_codes": [], "program_officials": [ { "id": 7356, "first_name": "Kelsey", "last_name": "Cook", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-09-01", "end_date": "2023-08-31", "award_amount": 399932, "principal_investigator": { "id": 7357, "first_name": "Louis", "last_name": "Bouchard", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 151, "ror": "", "name": "University of California-Los Angeles", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 151, "ror": "", "name": "University of California-Los Angeles", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "With support from the Chemical Measurement & Imaging program and co-funding from the Atomic, Molecular, and Optical Physics - Experiment and Theory programs, Professor Bouchard at the University of California, Los Angeles is developing new methods to study gaseous diffusion - the random motions of molecules in gases. In traditional models of these processes, a snapshot (state) at any given moment is assumed to be independent of past collisions between molecules swimming in the gas. However, if the picture can be taken quickly enough, it is possible to detect molecules’ \"memory\" of collisions from the recent past, and thus to investigate the nature of surfaces encountered by the molecules. Dr. Bouchard's group is developing both experimental methods and the underlying theory to advance understanding in systems (e.g., catalysts and lungs) where the memory of these collisions are important. They use nuclear magnetic resonance (NMR) spectroscopy, the tool at the heart of Magnetic Resonance Imaging (MRI, an important medical diagnostic tool) which avoids the use of harmful ionizing radiation like x-rays. Graduate and undergraduate students engaged in this research receive broad interdisciplinary training, and contribute to the development of relevant introductory chemistry materials that will be made freely available to the public. \n\nSelf-diffusion in a dense gas of neutral molecules is non-Markovian and must be modeled by a Langevin equation with memory kernel. The Bouchard group has obtained experimental NMR spectroscopy results that are consistent with a generalized Langevin description, as confirmed by an unexpected temperature dependence of the NMR linewidth as well as dependence on inter-pulse spacing during Carr-Purcell-Meiboom-Gill (CPMG) experiments. While the new theory describes the results of free self-diffusion well, the diffusion behavior in the presence of boundaries has not yet been explored. Dr. Bouchard is now probing restricted diffusion in porous media possessing various types of boundaries, and developing new extensions of the underlying theory based on the stochastic calculus of bounded diffusions (sticky, reflecting, killing, and absorbing boundaries). The new NMR-based methods may shed new light into the kinetic theory of gases, benefitting chemical physics and medical imaging by offering new tools to extract information about pore structure and function in media such as porous rocks, soils, or lungs. The tools also show promise for both characterization of catalytically reactive surfaces and mass transport during reactions and provision of a better understanding of hyperpolarized gas MRI. Educational impacts will derive from the training and active participation of multiple students in the research as well as the creation of free online educational course materials disseminated via the institution's web site.\n\nThis 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": "14378", "attributes": { "award_id": "2107791", "title": "The Role of Plasmon Initiated Electron Transfer in Enhanced Raman Spectroscopy", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Chemical Measurement & Imaging" ], "program_reference_codes": [], "program_officials": [ { "id": 27122, "first_name": "Jose", "last_name": "Almirall", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": null, "award_amount": 475000, "principal_investigator": { "id": 30979, "first_name": "Zachary", "last_name": "Schultz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 308, "ror": "", "name": "Ohio State University", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true }, "abstract": "With support from the Chemical Measurement and Imaging (CMI) Program in the Division of Chemistry, Zachary Schultz and his group at Ohio State University are investigating new ways to detect and quantify trace proteins and other biomolecules using lasers. The ability to detect specific biomolecules in real-world samples is important for identifying pathogens, tracking environmental pollutants, and monitoring disease. Specialized techniques called surface-enhanced Raman scattering (SERS) and tip-enhanced Raman scattering (TERS) use nanoparticles to increase the strength of the signals observed in some laser-based measurements. Currently, there are only a limited number of molecules that are readily detected using these techniques under ambient conditions and in complex systems. In order to address this limitation, the research team led by Dr. Schultz is working to better understand the mechanism that is responsible for the increased signals when proteins are in contact with nanoparticles by using a laser to illuminate individual proteins or protein fragments through a microscope. The goal of the research is to enable more sensitive measurements that will make it possible to detect and identify a much wider range of biomolecules. The project also addresses the need for a technically skilled and scientifically informed workforce by incorporating aspects of the research project into educational materials for the approximately 8,000 students who take general chemistry courses each year at Ohio State University. The project also provides valuable research experience for undergraduate and graduate students, and supports the Schultz laboratory’s collaboration with students and faculty in Chile, broadening student perspectives on the international nature and impact of science. <br/><br/>The research team led by Dr. Zachary Schultz is testing their hypothesis that stable radicals formed from interactions with excited plasmon resonances on nanoparticles can transiently and selectively increase the Raman cross-sections of biomolecules in SERS and TERS measurements. The team’s experimental measurements suggest that such interactions occur, and even alter the observed SERS spectra of the amino acid tryptophan and some tryptophan-containing proteins. Imaging the SERS emission from a sample and applying super-resolution algorithms should allow the researchers to locate and identify individual molecules that are in contact with a nanoparticle. These measurements are expected to simultaneously resolve the SERS spectrum of the individual molecule, even in complex samples. The information the team obtains from these sophisticated measurements should enable them to identify proteins and other biomolecules that exhibit increased sensitivity, and also enable them to better understand what makes such enhancements possible. Based on the improved understanding of the mechanism for SERS and TERS enhancements, the outcomes of this research can help guide the development of new and improved chemical sensors that are important for a very wide range of applications.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3709", "attributes": { "award_id": "1709552", "title": "Novel Methods to Study Metastable Biomolecular Systems with Native LC/MS", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Chemical Measurement & Imaging" ], "program_reference_codes": [], "program_officials": [ { "id": 12108, "first_name": "Kelsey", "last_name": "Cook", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-06-01", "end_date": "2021-05-31", "award_amount": 420000, "principal_investigator": { "id": 12109, "first_name": "Igor", "last_name": "Kaltashov", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 200, "ror": "https://ror.org/0072zz521", "name": "University of Massachusetts Amherst", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 200, "ror": "https://ror.org/0072zz521", "name": "University of Massachusetts Amherst", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Prof. Igor Kaltashov and his group at the University of Massachusetts at Amherst are developing powerful analytical tools to study processes such as protein/receptor recognition and enzymatic reactions. These new tools will advance understanding of the mechanisms of complex biological processes at the molecular level, ultimately facilitating manipulation of these processes to achieve desired outcomes. Thus, the new tools can have significant impact not only in chemistry, but also in biotechnology and medicine. Elements of the research involve close interaction with industrial collaborators, adding a valuable dimension to the educational experience of the graduate and undergraduate students involved. Dr. Kaltashov and his group are also engaging in outreach activities which seek to expose local high school students to the state-of-the-art analytical instrumentation at UMass-Amherst.\n\nCharacterization of biopolymer dynamics and architecture (conformations of individual biopolymer chains and assemblies of multi-unit systems) is both challenging and important for improved understanding of biochemical processes. There is particular need for tools capable of probing transient systems, which are encountered in processes such as protein aggregation, assembly and evolution of quaternary structures, interaction with physiological partners, and enzyme catalysis and transport phenomena. Improved understanding of these phenomena requires reliable kinetics data and knowledge of conformational changes that accompany transitions. In order to improve on existing characterization capabilities, the Kaltashov group is developing a new robust, sensitive, and highly selective experimental strategy that uses a combination of liquid chromatography (LC) run under native conditions (e.g., size-exclusion chromatography) with on-line detection by native electrospray ionization mass spectrometry (MS). The new LC/MS platform incorporates ion manipulation in the gas phase to enable studies of highly heterogeneous systems (e.g., protein-polymer conjugates). Incorporation of on-column H/D exchange and chemical reduction reactions enables top-down HDX MS/MS characterization of higher order structure and conformational dynamics of proteins.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3222", "attributes": { "award_id": "1807317", "title": "Single Nanoparticle SPR Imaging Measurements of Bioaffinity Uptake and Release in Polymer and DNA-Cross-linked Nanoparticles", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Chemical Measurement & Imaging" ], "program_reference_codes": [], "program_officials": [ { "id": 10123, "first_name": "Christopher", "last_name": "Elles", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2018-07-01", "end_date": "2021-12-31", "award_amount": 462000, "principal_investigator": { "id": 10124, "first_name": "Robert", "last_name": "Corn", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 177, "ror": "", "name": "University of California-Irvine", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 177, "ror": "", "name": "University of California-Irvine", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Corn at the University of California, Irvine, is developing and applying new optical techniques that can detect, characterize and monitor in real time the size and composition of single polymer nanoparticles. Understanding how porous polymer nanoparticles uptake, transport, and then release biologically active molecules such as nucleic acids and proteins are fundamentally important and interesting. Professor Corn develops better chemical methods to improve the uniformity, reliability, and stability of characterization of these nanoparticles. Professor Corn's research outcome could lead to technological advances in the fields of sensor development, drug delivery, and disease diagnostics. Professor Corn's project provides participating students with research experience in a diverse set of disciplines: polymer materials and characterization, nanomaterials, laser microscopy, biosensors and biotechnology. Development of young scientists with such a wide range of skills is essential for both industry and academia to successfully address future multi-disciplinary technological challenges. In addition to research, this grant supports education and outreach programs that attract high school students from underfunded schools and middle school female students interested in science to the STEM fields.\n\nSingle nanoparticle near-infrared surface plasmon resonance imaging (SPRI) microscopy is developed as a novel refractive index-based method to quantify the bioaffinity uptake and release of various biomolecules into individual porous polymeric nanoparticles. SPRI is an established refractive index-based technique for monitoring molecular and nanoparticle adsorption onto gold thin films. The application of SPRI microscopy is expanded here to single nanoparticle measurements that can monitor the uptake and release of biomolecules (both single nanoparticle averages and distribution measurements) in real time by measuring changes in the single nanoparticle refractive index that occur due to changes in composition. A variety of modified N-isopropylacrylamide (NIPAm) hydrogel nanoparticles that can uptake and release different proteins, lectins, nucleic acids, peptides, and pharmaceuticals are synthesized and studied. Three specific research efforts include: (i) the synthesis and characterization of NIPAm hydrogel nanoparticles that incorporate click chemistry sites to attach sugars, peptides, or DNA for the bioaffinity uptake and release of therapeutics, proteins, and RNA, (ii) the synthesis and characterization of DNA-cross-linked NIPAm (N-isopropylacrylamide)hydrogel nanoparticles that incorporate DNA aptamers and DNAzymes, and (iii) single-nanoparticle measurements of pH and temperature-induced morphological changes in NIPAm hydrogel nanoparticles that release various cargo (e.g., peptides, enzymes, DNA, and gold nanoparticles).\n\nThis 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": "1159", "attributes": { "award_id": "2102601", "title": "Ultrafast Coherent Spectroscopy of TiO2 Photocatalytic Processes", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 2938, "first_name": "Colby", "last_name": "Foss", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": "2024-08-31", "award_amount": 413325, "principal_investigator": { "id": 2939, "first_name": "Hrvoje", "last_name": "Petek", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 272, "ror": "https://ror.org/01an3r305", "name": "University of Pittsburgh", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 272, "ror": "https://ror.org/01an3r305", "name": "University of Pittsburgh", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "With support from the Chemical Structure Dynamics and Mechanisms-A (CSDM-A) Program of the Chemistry Division, Professor Hrvoje Petek of the University of Pittsburgh is performing time-resolved photoelectron spectroscopy studies of electron dynamics in titanium dioxide (TiO2) semiconductor on the femtosecond (10^-15 s) time scale. TiO2 is a material with well-known photocatalytic properties that can convert the solar to electrical or chemical energy, as well as induce decomposition of harmful chemicals, by light promoted transfer of electrons across the molecule/TiO2 interface. It is well documented that such light-induced processes occur in TiO2, but the dynamics of how light energy is used to perform useful chemical transformations, in competition with relaxation and degradation into heat, is poorly known. Such understanding exists for electronic semiconductors and metals, but is poorly understood for a large body of chemical materials that can be classified as metal oxides, such as TiO2. The characterization of electronic and chemical processes in TiO2 can advance the use of metal oxides in light-activated applications. The project supports the formal training of graduate students and post-doctoral associates. Informal education and outreach is being done via the virtual International Ultrafast Knowledge Coffee House (\"IUNCH\") that Professor Petek initiated during the COVID-19 pandemic lockdown.Photoinduced electron dynamics at single crystal TiO2 surfaces are being examined by ultrafast time-resolved photoelectron spectroscopy. Detailed interpretation of photoexcitation dynamics in the stoichiometric TiO2 is difficult, because the measurements probe electrons that are inhomogeneously distributed in space and momentum. Titanium dioxide has many atomic defect states, which give sharp photoelectron spectra, that enable the study of electron phase and energy relaxation. Ultrafast femtosecond (10-15 s) time scale measurements will be performed on such defect features to establish intrinsic energy and momentum relaxation processes, broadly, in metal oxide materials. Titanium dioxide also has well-documented plasmonically enhanced photocatalytic activity. Studies will be performed on how light excitation in a plasmonic metal activates ultrafast electronic processes at TiO2 surfaces. The students and post-doctoral associates involved in this project will gain experience in ultrafast laser techniques and computational modeling of ultrafast coherent dynamics.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": 1405, "count": 14046 } } }