# data[].attributes.grants[].title
RAPID: Who is (Not) Complying with the Social Distancing Directive and Why?

# data[].attributes.grants[].abstract
In the current COVID-19 pandemic, one approach to minimizing the spread of the virus focuses on people’s behavior – social distancing. Since the start of the pandemic, government leaders and health experts have requested citizens to follow social distancing directives. Despite this repeated message and despite the fact that many people are taking the message seriously, many others are violating the new norms. That raises important questions: who is and who is not complying, and why? Understanding why people choose not to practice social distancing is crucial for designing effective public service campaigns.  This research investigates who complies, what specific beliefs should be addressed, and what factors make public campaigns believable. The project seeks to identify the factors that lead to greater compliance for the greater good, and will inform future public service campaigns. A series of studies examines how social distancing behaviors vary as a function of belief systems. An innovative measure of social distancing is developed – one that is more behavioral in nature than the typical survey. The critical beliefs that are to be examined stem from a conceptual framework regarding a directive as involving three essential components.  One is the source -- someone is requesting people to change their behavior.  A second is the surrounding context --  the request is in response to some challenge.  The third component is the target -- the persons to whom the request is addressed. Belief systems relevant to each of these three components are expected to influence the likelihood that people will comply with the request.  As a result, an entire network of beliefs is expected to influence how people respond and why. Some individuals’ belief systems will lead them to view the request favorably, thus promoting appropriate social distancing behaviors. Others will reach more negative conclusions and subsequently refuse to take directives seriously. Once the concerns about the pandemic have lessened, study participants will be re-contacted and asked to again respond to social distancing behavioral scenarios and to indicate if they had experienced virus symptoms in the interim.  Those follow-up data will shed light on the relationship between individuals’ social distancing behaviors and their subsequent likelihood of infection.  The research aims to inform theory regarding social compliance processes, and will provide a stronger foundation for developing future public service campaigns.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.

# data[].attributes.grants[].keywords
['social distancing behavior', ' contracting COVID', ' political polarization', ' conspiracist ideation', ' disgust sensitivity']

# data[].attributes.grants[].title
Prevention Research Center: Parenting Among Women Who Are Opioid Users

# data[].attributes.grants[].abstract
The global SARS-CoV-2 pandemic that causes the severe respiratory illness COVID-19 is the worst health crisis the United States has faced in a century. Although this highly contagious virus has infected millions of Americans already, the disease burdens are disproportionately born by historically underserved populations such as Latinx communities. Nationally, Latinx people with COVID-19 are hospitalized at four times the rate of Whites and have much higher rates of morbidity and mortality. This disparity is notable in Oregon, where the 13% of our population that is Latinx represents approximately 44% of COVID-19 cases. An urgent need exists to reach Oregon’s Latinx community with public health and prevention messages to increase testing. This project will implement a culturally-tailored community outreach and testing program to increase the reach, access, and uptake of testing in Latinx communities in Oregon. The project will bring together a world-class team of prevention scientists, public health experts, Latinx researchers, community partners, and biologists who have been working together to conduct SARS-CoV-2 diagnostic testing since March, soon after the pandemic first arrived in the U.S. This team has established a CLIA-certified laboratory and honed molecular testing protocols, hired and trained laboratory personnel and a field research team, procured diagnostic testing equipment and supplies, and partnered with county public health offices and hospitals throughout the state to conduct testing. The team also conducted a comprehensive community assessment using community-based participatory methods to gather Latinx community feedback on modes of communication, health messages, and testing protocols, and staffed multiple county-led testing sites serving Latinx communities. Using these resources and expertise as a foundation, a Sequential Multiple Armed Randomized Trial (SMART) will enable the evaluation of strategies for increasing testing rates and promoting health behaviors in Latinx communities. Specifically, culturally informed, community-oriented interventions will determine tools and best practices to increase testing rates and health behaviors. The efficacy of different types of approaches for increasing access to and utilization of testing will be evaluated. Lastly, the work will examine a set of county-level variables thought to affect communities’ abilities to sustain testing capacity. With support from a Latinx Community and Scientific Advisory Board, the project will ramp up to ultimately support 36 community testing sites across six counties in Oregon to serve Latinx communities. Over time, this project will help communities institutionalize optimal local testing frameworks supported by UO laboratory facilities for testing capacity, technical support for testing logistics, and collection of data on health behaviors, testing rates, and sustainability. The resulting structures and systems will be poised for future scale-up to other vulnerable communities and/or for other public health purposes (e.g., vaccination campaigns). If successful, this project will lead to a major reduction in COVID-19 health disparities in underserved populations.

# data[].attributes.grants[].keywords
['2019-nCoV', 'Address', 'Adoption', 'Affect', 'Alcohol or Other Drugs use', 'American', 'Area', 'CLIA certified', 'COVID-19', 'Centers for Disease Control and Prevention (U.S.)', 'Charge', 'Child Rearing', 'Communication', 'Communities', 'Community Outreach', 'County', 'Data Collection', 'Data Science', 'Development', 'Diagnostic tests', 'Equipment and Supplies', 'Evaluation', 'Event', 'Family', 'Feedback', 'Foundations', 'Friends', 'Future', 'Genomics', 'Goals', 'Health', 'Health Promotion', 'Health behavior', 'Hospitals', 'Individual', 'Infection', 'Infrastructure', 'Intervention', 'Laboratories', 'Laboratory Personnel', 'Leadership', 'Location', 'Logistics', 'Methods', 'Modeling', 'Molecular', 'Molecular Biology', 'Morbidity - disease rate', 'Motivation', 'Oregon', 'Pamphlets', 'Penetration', 'Phase', 'Population', 'Prevention', 'Prevention Research', 'Protocols documentation', 'Public Health', 'Ramp', 'Research', 'Research Personnel', 'Research Project Grants', 'Resources', 'Science', 'Scientist', 'Site', 'Structure', 'System', 'Testing', 'Time', 'Underserved Population', 'United States', 'Vaccination', 'Virus', 'Visit', 'Woman', 'Work', 'base', 'behavior test', 'burden of illness', 'community based participatory research', 'design', 'experience', 'health disparity', 'health literacy', 'implementation science', 'improved', 'laboratory experience', 'laboratory facility', 'mortality', 'operation', 'opioid user', 'outreach', 'outreach services', 'pandemic disease', 'programs', 'psychoeducation', 'randomized trial', 'recruit', 'research study', 'respiratory', 'response', 'scale up', 'social determinants', 'tool', 'transmission process', 'uptake', 'Latinx', ' Promotora de Salud', ' health promotion', ' testing']

# data[].attributes.grants[].title
Prevention Research Center: Parenting Among Women Who Are Opioid Users

# data[].attributes.grants[].abstract
The global SARS-CoV-2 pandemic that causes the severe respiratory illness COVID-19 is the worst health crisis the United States has faced in a century. Although this highly contagious virus has infected millions of Americans already, the disease burdens are disproportionately born by historically underserved populations such as Latinx communities. Nationally, Latinx people with COVID-19 are hospitalized at four times the rate of Whites and have much higher rates of morbidity and mortality. This disparity is notable in Oregon, where the 13% of our population that is Latinx represents approximately 44% of COVID-19 cases. An urgent need exists to reach Oregon’s Latinx community with public health and prevention messages to increase testing. This project will implement a culturally-tailored community outreach and testing program to increase the reach, access, and uptake of testing in Latinx communities in Oregon. The project will bring together a world-class team of prevention scientists, public health experts, Latinx researchers, community partners, and biologists who have been working together to conduct SARS-CoV-2 diagnostic testing since March, soon after the pandemic first arrived in the U.S. This team has established a CLIA-certified laboratory and honed molecular testing protocols, hired and trained laboratory personnel and a field research team, procured diagnostic testing equipment and supplies, and partnered with county public health offices and hospitals throughout the state to conduct testing. The team also conducted a comprehensive community assessment using community-based participatory methods to gather Latinx community feedback on modes of communication, health messages, and testing protocols, and staffed multiple county-led testing sites serving Latinx communities. Using these resources and expertise as a foundation, a Sequential Multiple Armed Randomized Trial (SMART) will enable the evaluation of strategies for increasing testing rates and promoting health behaviors in Latinx communities. Specifically, culturally informed, community-oriented interventions will determine tools and best practices to increase testing rates and health behaviors. The efficacy of different types of approaches for increasing access to and utilization of testing will be evaluated. Lastly, the work will examine a set of county-level variables thought to affect communities’ abilities to sustain testing capacity. With support from a Latinx Community and Scientific Advisory Board, the project will ramp up to ultimately support 36 community testing sites across six counties in Oregon to serve Latinx communities. Over time, this project will help communities institutionalize optimal local testing frameworks supported by UO laboratory facilities for testing capacity, technical support for testing logistics, and collection of data on health behaviors, testing rates, and sustainability. The resulting structures and systems will be poised for future scale-up to other vulnerable communities and/or for other public health purposes (e.g., vaccination campaigns). If successful, this project will lead to a major reduction in COVID-19 health disparities in underserved populations.

# data[].attributes.grants[].keywords
['2019-nCoV', 'Address', 'Adoption', 'Affect', 'Alcohol or Other Drugs use', 'American', 'Area', 'CLIA certified', 'COVID-19', 'Centers for Disease Control and Prevention (U.S.)', 'Charge', 'Child Rearing', 'Communication', 'Communities', 'Community Outreach', 'County', 'Data Collection', 'Data Science', 'Development', 'Diagnostic tests', 'Equipment and Supplies', 'Evaluation', 'Event', 'Family', 'Feedback', 'Foundations', 'Friends', 'Future', 'Genomics', 'Goals', 'Health', 'Health Promotion', 'Health behavior', 'Hospitals', 'Individual', 'Infection', 'Infrastructure', 'Intervention', 'Laboratories', 'Laboratory Personnel', 'Leadership', 'Location', 'Logistics', 'Methods', 'Modeling', 'Molecular', 'Molecular Biology', 'Morbidity - disease rate', 'Motivation', 'Oregon', 'Pamphlets', 'Penetration', 'Phase', 'Population', 'Prevention', 'Prevention Research', 'Protocols documentation', 'Public Health', 'Ramp', 'Research', 'Research Personnel', 'Research Project Grants', 'Resources', 'Science', 'Scientist', 'Site', 'Structure', 'System', 'Testing', 'Time', 'Underserved Population', 'United States', 'Vaccination', 'Virus', 'Visit', 'Woman', 'Work', 'base', 'behavior test', 'burden of illness', 'community based participatory research', 'design', 'experience', 'health disparity', 'health literacy', 'implementation science', 'improved', 'laboratory experience', 'laboratory facility', 'mortality', 'operation', 'opioid user', 'outreach', 'outreach services', 'pandemic disease', 'programs', 'psychoeducation', 'randomized trial', 'recruit', 'research study', 'respiratory', 'response', 'scale up', 'social determinants', 'tool', 'transmission process', 'uptake', 'Latinx', ' Promotora de Salud', ' health promotion', ' testing']

# data[].attributes.grants[].title
PIPP Phase I: Computational Theory of the Co-evolution of Pandemics, (Mis)information, and Human Mindsets and Behavior

# data[].attributes.grants[].funder_divisions
['Computer and Information Science and Engineering (CISE)', 'PIPP-Pandemic Prevention']

# data[].attributes.grants[].abstract
Epidemiological models are used to predict the spread of highly contagious and lethal diseases such as COVID-19. Public health officials use such models to inform pandemic response policies and advisories. Yet these models require a rigorous scientific foundation about human psychology to better predict people’s responses to information and policies about pandemics. The recent COVID-19 pandemic illustrates the central role of human decision making and behavior in the spread of such a transmissible disease. People’s decisions regarding social isolation, social distancing, mask wearing, hand washing, and vaccination are correlated with the rate at which the COVID-19 virus spreads or the seriousness of getting infected. People have different individual mindsets, and these can vary across different regions and subgroups, so different groups of people respond differently to messaging and mandates and those responses change over time. There is also an ongoing scientific debate about the degree to which pandemic information or misinformation, or the perceived credibility of information sources, influences the degree to which people change their behavior. To address these scientific needs, this project involves activities to develop a multidisciplinary research core and agenda and to develop a strong plan for a cohesive research center for Predictive Intelligence for Pandemic Prevention. The activities include exploratory research on computational models of human psychology, information flow and influence, and resulting pandemic transmission. The project will also support the training and mentoring of graduate students who represent the next generation of researchers tackling these global challenges.

This project uses computational theories and models to examine the fundamental interdependent evolution of infection, behavior, and information at multiple levels and drawing upon multiple disciplines in order to support improved pandemic intelligence, prediction, explanation, and countermeasures. The project is organized into (1) interdisciplinary, strategic research thrusts to Accelerate Convergent Science towards the Grand Challenge, (2) three invitational meetings to draw in diverse researchers to address focal research topics and research questions, to fill in gaps in the Research Challenges, and develop a strong research and education agenda for a cohesive PIPP center, and (3) Pilot Studies to Demonstrate Feasibility of integrated computational models of information, human psychology, and pandemic transmission. For the pilot research, a multidisciplinary team combines empirical assessments with computational cognitive models in an agent-based modeling system. For data the investigators draw on vaccination discussions in mass media, Twitter, geolocated timeseries data on vaccination rates, infection, death and recovery rates, state and national mandates regarding COVID-19 policies about vaccination and mask wearing from February 2020 through December 2021 in the United States. These data will be segmented by state and major cities within those states. 

This award is supported by the cross-directorate Predictive Intelligence for Pandemic Prevention Phase I (PIPP) program, which is jointly funded by the Directorates for Biological Sciences (BIO), Computer Information Science and Engineering (CISE), Engineering (ENG) and Social, Behavioral and Economic Sciences (SBE).

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.

# data[].attributes.grants[].keywords
['covid-19', ' pandemic', ' human behavior', ' decision-making', ' cognition', ' online social networks']

# data[].attributes.grants[].principal_investigator.keywords
['computational cognitive theory', ' natural language processing', ' artificial intelligence', ' machine learning', ' online social networks']

# data[].attributes.grants[].awardee_organization.name
Florida Institute for Human and Machine Cognition, Inc.

# data[].attributes.grants[].title
Experimental and natural SARS-CoV-2 infection of the human pancreas

# data[].attributes.grants[].funder_divisions
['National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)']

# data[].attributes.grants[].abstract
The possibility that infection with SARS-CoV-2 may trigger diabetes emerged as a concern in mid 2020. We have addressed this issue by developing a research roadmap that identified complementary areas of investigation according to several broad topics in the realm of relevant basic biomedical research. Based on our recent publication about the expression of SARS-CoV-2 entry factors in the non-diabetic human pancreas, we have now developed a Research Strategy that will assess the principal capacity of pancreatic SARS-CoV-2 infection and its primary consequences in a series of in vitro, in vivo and ex vivo studies distributed across three Specific Aims: In Aim 1 we will define expression patterns of ACE2 and other viral entry factors in dispersed human pancreatic cell populations; will subject islets to in vitro SARS-CoV-2 infection and quantify infection patterns as well as alterations of single-cell proteomes and transcriptomes by flow cytometry, high-dimensional mass cytometry, and scRNAseq; will determine functional islet responses under conditions of viral infection by dynamic glucose-stimulated insulin secretion; will conduct mechanistic studies with targeted ACE2 blockade and by generation of ACE2-deficient beta-like cells; and will explore SARS-CoV-2 infection in the context of living pancreas slices that provide a more “physiological” experimental platform for in vitro studies. In Aim 2, we will use the robust “minimal mass” model of human islet transplantation into immunodeficient mice to delineate metabolic perturbations (blood glucose values, plasma insulin, intraperitoneal glucose tolerance test) accrued in the wake of an in vivo SARS-CoV-2 challenge. To address the considerable experimental and logistical challenges in these studies, we have developed a tiered approach that progressively refines experimental designs (including use of a recently generated, sequenced and characterized mouse-adapted [ma] SARS-CoV-2 strain) with the goal to imbue our models with escalating biological relevance. In Aim 3, we will draw on our access to COVID-19 and control autopsy cases to reveal the ex vivo viral burden of natural SARS-CoV-2 infection in the pancreas. These studies, which build on recently published pilot data as well as extensive preparatory studies to adjust our staining protocols to the demands of at times suboptimal tissue quality, will define SARS-CoV-2 protein and mRNA abundance, cellular association and distribution patterns across the COVID-19 pancreas. We will further leverage an established immunohistochemical multiplexing strategy to define the identity, quantity and distribution of major immune cell subsets throughout COVID-19 and control pancreata. Thus, the proposed work will generate an inclusive perspective on the cardinal viral and immunological components of the potentially altered pancreatic histology in COVID-19. Collectively, the proposed work addresses, and is expected to resolve at least in part, key aspects of the hypothesis that SARS-CoV-2 infection may precipitate diabetes onset. Together with emerging epidemiological data, it may therefore provide an important foundation for future risk assessment and the prioritization of prophylactic and/or therapeutic intervention strategies.

# data[].attributes.grants[].keywords
['2019-nCoV', 'ACE2', 'Address', 'Animal Experiments', 'Area', 'Autopsy', 'Beta Cell', 'Biological', 'Biomedical Research', 'Blood Glucose', 'COVID-19', 'COVID-19 mortality', 'COVID-19 patient', 'Cell physiology', 'Cells', 'Clinical', 'Cohort Studies', 'Cytometry', 'Data', 'Detection', 'Diabetes Mellitus', 'Endocrine', 'Epidemiology', 'Experimental Designs', 'Flow Cytometry', 'Foundations', 'Future', 'Generations', 'Glucose', 'Glucose tolerance test', 'Goals', 'Histologic', 'Histology', 'Human', 'Immune', 'Immunodeficient Mouse', 'Immunologics', 'Impairment', 'In Situ', 'In Vitro', 'Infection', 'Insulin', 'Insulin-Dependent Diabetes Mellitus', 'Intervention', 'Investigation', 'Islets of Langerhans', 'Islets of Langerhans Transplantation', 'Journals', 'Letters', 'Logistics', 'Mediating', 'Medicine', 'Messenger RNA', 'Metabolic', 'Modeling', 'Mus', 'Nature', 'New England', 'Non-Insulin-Dependent Diabetes Mellitus', 'Pancreas', 'Pathologic', 'Pathway interactions', 'Pattern', 'Physiological', 'Plant Roots', 'Plasma', 'Population', 'Predisposition', 'Proteins', 'Proteome', 'Protocols documentation', 'Publications', 'Publishing', 'Reporting', 'Research', 'Research Personnel', 'Resolution', 'Risk Assessment', 'Role', 'SARS-CoV-2 infection', 'Sampling', 'Series', 'Severities', 'Slice', 'Stains', 'Therapeutic Intervention', 'Time', 'Tissues', 'Tropism', 'Viral', 'Viral Load result', 'Viral Proteins', 'Virus Diseases', 'Work', 'base', 'blood glucose regulation', 'case control', 'cell type', 'comorbidity', 'demographics', 'diabetogenic', 'epidemiologic data', 'experimental study', 'high dimensionality', 'human model', 'humanized mouse', 'in vitro Model', 'in vivo', 'influenza infection', 'insight', 'insulin secretion', 'islet', 'mRNA Expression', 'mouse model', 'non-diabetic', 'patient registry', 'prophylactic', 'receptor', 'response', 'transcriptome', 'virology', 'Diabetes', ' beta islets', ' pancreas', ' ACE2 receptor', 'preclinical diabetes models', ' obesity models', ' metabolomics', ' metabolism studies', ' metabolic biomarkers for disease']

# data[].attributes.grants[].other_investigators[].keywords
['Preclinical animal models', ' adjuvants', ' vaccines', ' host responses', ' immunology', 'Preclinical animal models', ' adjuvants', ' vaccines', ' host responses', ' immunology']

# data[].attributes.grants[].other_investigators[].desired_collaboration
Can offer assistance with preclinical infection experiments with SARS-CoV-2 variants of concern, vaccine validation, host response characterization

# data[].attributes.grants[].other_investigators[].comments
Zoom, slack, e-mail, in person, google group, teams, ...

# data[].attributes.grants[].title
Experimental and natural SARS-CoV-2 infection of the human pancreas

# data[].attributes.grants[].funder_divisions
['National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)']

# data[].attributes.grants[].abstract
The possibility that infection with SARS-CoV-2 may trigger diabetes emerged as a concern in mid 2020. We have addressed this issue by developing a research roadmap that identified complementary areas of investigation according to several broad topics in the realm of relevant basic biomedical research. Based on our recent publication about the expression of SARS-CoV-2 entry factors in the non-diabetic human pancreas, we have now developed a Research Strategy that will assess the principal capacity of pancreatic SARS-CoV-2 infection and its primary consequences in a series of in vitro, in vivo and ex vivo studies distributed across three Specific Aims: In Aim 1 we will define expression patterns of ACE2 and other viral entry factors in dispersed human pancreatic cell populations; will subject islets to in vitro SARS-CoV-2 infection and quantify infection patterns as well as alterations of single-cell proteomes and transcriptomes by flow cytometry, high-dimensional mass cytometry, and scRNAseq; will determine functional islet responses under conditions of viral infection by dynamic glucose-stimulated insulin secretion; will conduct mechanistic studies with targeted ACE2 blockade and by generation of ACE2-deficient beta-like cells; and will explore SARS-CoV-2 infection in the context of living pancreas slices that provide a more “physiological” experimental platform for in vitro studies. In Aim 2, we will use the robust “minimal mass” model of human islet transplantation into immunodeficient mice to delineate metabolic perturbations (blood glucose values, plasma insulin, intraperitoneal glucose tolerance test) accrued in the wake of an in vivo SARS-CoV-2 challenge. To address the considerable experimental and logistical challenges in these studies, we have developed a tiered approach that progressively refines experimental designs (including use of a recently generated, sequenced and characterized mouse-adapted [ma] SARS-CoV-2 strain) with the goal to imbue our models with escalating biological relevance. In Aim 3, we will draw on our access to COVID-19 and control autopsy cases to reveal the ex vivo viral burden of natural SARS-CoV-2 infection in the pancreas. These studies, which build on recently published pilot data as well as extensive preparatory studies to adjust our staining protocols to the demands of at times suboptimal tissue quality, will define SARS-CoV-2 protein and mRNA abundance, cellular association and distribution patterns across the COVID-19 pancreas. We will further leverage an established immunohistochemical multiplexing strategy to define the identity, quantity and distribution of major immune cell subsets throughout COVID-19 and control pancreata. Thus, the proposed work will generate an inclusive perspective on the cardinal viral and immunological components of the potentially altered pancreatic histology in COVID-19. Collectively, the proposed work addresses, and is expected to resolve at least in part, key aspects of the hypothesis that SARS-CoV-2 infection may precipitate diabetes onset. Together with emerging epidemiological data, it may therefore provide an important foundation for future risk assessment and the prioritization of prophylactic and/or therapeutic intervention strategies.

# data[].attributes.grants[].keywords
['2019-nCoV', 'ACE2', 'Address', 'Animal Experiments', 'Area', 'Autopsy', 'Beta Cell', 'Biological', 'Biomedical Research', 'Blood Glucose', 'COVID-19', 'COVID-19 mortality', 'COVID-19 patient', 'Cell physiology', 'Cells', 'Clinical', 'Cohort Studies', 'Cytometry', 'Data', 'Detection', 'Diabetes Mellitus', 'Endocrine', 'Epidemiology', 'Experimental Designs', 'Flow Cytometry', 'Foundations', 'Future', 'Generations', 'Glucose', 'Glucose tolerance test', 'Goals', 'Histologic', 'Histology', 'Human', 'Immune', 'Immunodeficient Mouse', 'Immunologics', 'Impairment', 'In Situ', 'In Vitro', 'Infection', 'Insulin', 'Insulin-Dependent Diabetes Mellitus', 'Intervention', 'Investigation', 'Islets of Langerhans', 'Islets of Langerhans Transplantation', 'Journals', 'Letters', 'Logistics', 'Mediating', 'Medicine', 'Messenger RNA', 'Metabolic', 'Modeling', 'Mus', 'Nature', 'New England', 'Non-Insulin-Dependent Diabetes Mellitus', 'Pancreas', 'Pathologic', 'Pathway interactions', 'Pattern', 'Physiological', 'Plant Roots', 'Plasma', 'Population', 'Predisposition', 'Proteins', 'Proteome', 'Protocols documentation', 'Publications', 'Publishing', 'Reporting', 'Research', 'Research Personnel', 'Resolution', 'Risk Assessment', 'Role', 'SARS-CoV-2 infection', 'Sampling', 'Series', 'Severities', 'Slice', 'Stains', 'Therapeutic Intervention', 'Time', 'Tissues', 'Tropism', 'Viral', 'Viral Load result', 'Viral Proteins', 'Virus Diseases', 'Work', 'base', 'blood glucose regulation', 'case control', 'cell type', 'comorbidity', 'demographics', 'diabetogenic', 'epidemiologic data', 'experimental study', 'high dimensionality', 'human model', 'humanized mouse', 'in vitro Model', 'in vivo', 'influenza infection', 'insight', 'insulin secretion', 'islet', 'mRNA Expression', 'mouse model', 'non-diabetic', 'patient registry', 'prophylactic', 'receptor', 'response', 'transcriptome', 'virology', 'Diabetes', ' beta islets', ' pancreas', ' ACE2 receptor', 'preclinical diabetes models', ' obesity models', ' metabolomics', ' metabolism studies', ' metabolic biomarkers for disease']

# data[].attributes.grants[].other_investigators[].keywords
['Preclinical animal models', ' adjuvants', ' vaccines', ' host responses', ' immunology', 'Preclinical animal models', ' adjuvants', ' vaccines', ' host responses', ' immunology']

# data[].attributes.grants[].other_investigators[].desired_collaboration
Can offer assistance with preclinical infection experiments with SARS-CoV-2 variants of concern, vaccine validation, host response characterization

# data[].attributes.grants[].other_investigators[].comments
Zoom, slack, e-mail, in person, google group, teams, ...

# data[].attributes.grants[].title
Experimental and natural SARS-CoV-2 infection of the human pancreas

# data[].attributes.grants[].funder_divisions
['National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)']

# data[].attributes.grants[].abstract
The possibility that infection with SARS-CoV-2 may trigger diabetes emerged as a concern in mid 2020. We have addressed this issue by developing a research roadmap that identified complementary areas of investigation according to several broad topics in the realm of relevant basic biomedical research. Based on our recent publication about the expression of SARS-CoV-2 entry factors in the non-diabetic human pancreas, we have now developed a Research Strategy that will assess the principal capacity of pancreatic SARS-CoV-2 infection and its primary consequences in a series of in vitro, in vivo and ex vivo studies distributed across three Specific Aims: In Aim 1 we will define expression patterns of ACE2 and other viral entry factors in dispersed human pancreatic cell populations; will subject islets to in vitro SARS-CoV-2 infection and quantify infection patterns as well as alterations of single-cell proteomes and transcriptomes by flow cytometry, high-dimensional mass cytometry, and scRNAseq; will determine functional islet responses under conditions of viral infection by dynamic glucose-stimulated insulin secretion; will conduct mechanistic studies with targeted ACE2 blockade and by generation of ACE2-deficient beta-like cells; and will explore SARS-CoV-2 infection in the context of living pancreas slices that provide a more “physiological” experimental platform for in vitro studies. In Aim 2, we will use the robust “minimal mass” model of human islet transplantation into immunodeficient mice to delineate metabolic perturbations (blood glucose values, plasma insulin, intraperitoneal glucose tolerance test) accrued in the wake of an in vivo SARS-CoV-2 challenge. To address the considerable experimental and logistical challenges in these studies, we have developed a tiered approach that progressively refines experimental designs (including use of a recently generated, sequenced and characterized mouse-adapted [ma] SARS-CoV-2 strain) with the goal to imbue our models with escalating biological relevance. In Aim 3, we will draw on our access to COVID-19 and control autopsy cases to reveal the ex vivo viral burden of natural SARS-CoV-2 infection in the pancreas. These studies, which build on recently published pilot data as well as extensive preparatory studies to adjust our staining protocols to the demands of at times suboptimal tissue quality, will define SARS-CoV-2 protein and mRNA abundance, cellular association and distribution patterns across the COVID-19 pancreas. We will further leverage an established immunohistochemical multiplexing strategy to define the identity, quantity and distribution of major immune cell subsets throughout COVID-19 and control pancreata. Thus, the proposed work will generate an inclusive perspective on the cardinal viral and immunological components of the potentially altered pancreatic histology in COVID-19. Collectively, the proposed work addresses, and is expected to resolve at least in part, key aspects of the hypothesis that SARS-CoV-2 infection may precipitate diabetes onset. Together with emerging epidemiological data, it may therefore provide an important foundation for future risk assessment and the prioritization of prophylactic and/or therapeutic intervention strategies.

# data[].attributes.grants[].keywords
['2019-nCoV', 'ACE2', 'Address', 'Animal Experiments', 'Area', 'Autopsy', 'Beta Cell', 'Biological', 'Biomedical Research', 'Blood Glucose', 'COVID-19', 'COVID-19 mortality', 'COVID-19 patient', 'Cell physiology', 'Cells', 'Clinical', 'Cohort Studies', 'Cytometry', 'Data', 'Detection', 'Diabetes Mellitus', 'Endocrine', 'Epidemiology', 'Experimental Designs', 'Flow Cytometry', 'Foundations', 'Future', 'Generations', 'Glucose', 'Glucose tolerance test', 'Goals', 'Histologic', 'Histology', 'Human', 'Immune', 'Immunodeficient Mouse', 'Immunologics', 'Impairment', 'In Situ', 'In Vitro', 'Infection', 'Insulin', 'Insulin-Dependent Diabetes Mellitus', 'Intervention', 'Investigation', 'Islets of Langerhans', 'Islets of Langerhans Transplantation', 'Journals', 'Letters', 'Logistics', 'Mediating', 'Medicine', 'Messenger RNA', 'Metabolic', 'Modeling', 'Mus', 'Nature', 'New England', 'Non-Insulin-Dependent Diabetes Mellitus', 'Pancreas', 'Pathologic', 'Pathway interactions', 'Pattern', 'Physiological', 'Plant Roots', 'Plasma', 'Population', 'Predisposition', 'Proteins', 'Proteome', 'Protocols documentation', 'Publications', 'Publishing', 'Reporting', 'Research', 'Research Personnel', 'Resolution', 'Risk Assessment', 'Role', 'SARS-CoV-2 infection', 'Sampling', 'Series', 'Severities', 'Slice', 'Stains', 'Therapeutic Intervention', 'Time', 'Tissues', 'Tropism', 'Viral', 'Viral Load result', 'Viral Proteins', 'Virus Diseases', 'Work', 'base', 'blood glucose regulation', 'case control', 'cell type', 'comorbidity', 'demographics', 'diabetogenic', 'epidemiologic data', 'experimental study', 'high dimensionality', 'human model', 'humanized mouse', 'in vitro Model', 'in vivo', 'influenza infection', 'insight', 'insulin secretion', 'islet', 'mRNA Expression', 'mouse model', 'non-diabetic', 'patient registry', 'prophylactic', 'receptor', 'response', 'transcriptome', 'virology', 'Diabetes', ' beta islets', ' pancreas', ' ACE2 receptor', 'preclinical diabetes models', ' obesity models', ' metabolomics', ' metabolism studies', ' metabolic biomarkers for disease']

# data[].attributes.grants[].other_investigators[].keywords
['Preclinical animal models', ' adjuvants', ' vaccines', ' host responses', ' immunology', 'Preclinical animal models', ' adjuvants', ' vaccines', ' host responses', ' immunology']

# data[].attributes.grants[].other_investigators[].desired_collaboration
Can offer assistance with preclinical infection experiments with SARS-CoV-2 variants of concern, vaccine validation, host response characterization

# data[].attributes.grants[].other_investigators[].comments
Zoom, slack, e-mail, in person, google group, teams, ...

# data[].attributes.title
COVID-19 policy responses, mobility, and food prices

# data[].attributes.grants[].title
Collaborative Research: Transport of model-virus through the lung liquid lining

# data[].attributes.grants[].abstract
The novel coronavirus SARS-CoV-2, responsible for the COVID-19 pandemic, is similar to other respiratory coronaviruses, such as SARS-CoV (2002) and MERS-CoV (2012). All these viruses cause dangerous respiratory disorders with high mortality and grave impacts on society. This virus destroys the cells that produce lung surfactants which, among other things, keep the alveoli air-sacks from collapsing, and eventually the lungs fill with liquid. The two primary functions of lung surfactants are regulating the interfacial tension and surface viscosities of the liquid lining of the alveoli, and providing a first line of immune defense against airborne pathogens.  The fluid dynamic interactions between the liquid lining of the lung, the lung surfactants, and the respiratory virus are presently not well understood. This project addresses this gap by conducting experiments and numerical modeling to capture the essential fluid dynamics of a model virus interacting with the primary insoluble component of lung surfactant. The expansion and contraction of the alveoli will be modeled using an open cavity with oscillatory sidewalls that expand and compress the liquid layer. The numerical models will then be used to simulate physiologically relevant scales, not accessible experimentally.  Aside from the flow in the lung liquid lining, the present knowledge gap in predictive modeling of interfacial dilation and compression is hampering developments in other areas, such as in water waves, which are of utmost importance in modeling of carbon dioxide gas exchange between the atmosphere and the oceans.Predictive models for the transport of small particles in a surfactant-covered liquid layer will be developed. A key advancement in the proposed modeling of surface elasticity is to measure the equation-of-state of the monolayer in a state corresponding to that found when it has been subjected to a large number of dilation/compression cycles. The usual approach of determining properties of a recently spread monolayer undergoing slow compression is inappropriate for modeling monolayer hydrodynamics coupled to an oscillatory bulk flow, as the monolayer is in a different state with very different interfacial properties. The role of interfacial dilatational viscosity and its significance relative to surface elasticity remains poorly understood and presents a major impediment to the predictive modeling of free-surface flows. The PIs have a proven track record of productive multidisciplinary collaboration, and will continue to provide a unique educational opportunity for the graduate and undergraduate students.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.

# data[].attributes.title
CIC-E: COVID Information Commons Extension for Pandemic Recovery

# data[].attributes.authors[].keywords
['Data science', 'analytics', 'health', 'COVID', 'coronavirus', 'cybersecurity', 'connected healthcare', 'Medical Internet of Things', 'IoT', 'TIPPSS', 'Trust', 'Identity', 'Privacy', 'Protection', 'Safety', 'Security', 'data science', 'STEM', 'researcher collaboration']

# data[].attributes.authors[].comments
Slack, google group, discord, CIC websiteThank you!

# data[].attributes.grants[].abstract
This project will create a COVID Information Commons (CIC) website to facilitate knowledge sharing and collaboration across various COVID research efforts, especially focusing on all the NSF-funded COVID Rapid Response Research (RAPID) projects. The CIC will serve as a resource for researchers as well as decision-makers from government, academia, not-for-profit and industry to leverage each other's findings, and invest in and accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic. It will also serve as a model for integrated knowledge sharing and collaboration on other public health challenges, in benefit to society. Projects will be able to enter and publish information about their efforts in ways that are most relevant and user-friendly for a variety of potential stakeholders from academia, industry, government, and non-profit sectors. Information will be organized in multiple ways, for example, by research topics areas and by geography. In addition to information from NSF COVID-19 RAPID projects, the COVID Information Commons will incorporate coronavirus-related information from NSF Open Knowledge Network projects, as well as from other NSF research projects in general. The COVID Information Commons will utilize information science methods to bring together information about the collection of COVID-19 RAPID projects funded by the National Science Foundation. A wide array of research efforts are underway to study the impacts of the pandemic in fields as far ranging as biophysics, social justice/inequity, behavioral science, public health, supply chains, and risk management. The CIC will semantically link information across projects to provide a more holistic view across distinct efforts, including efforts such as the COVID projects in the NSF Open Knowledge Network. The resulting, concise, curated, integrated resource will provide insight into NSF-funded COVID RAPID projects and facilitate collaborations among such efforts. These objectives will be achieved using information science approaches to 1) compile a comprehensive list of NSF COVID RAPID awards, along with relevant details for each project, 2) link to any publicly available data sets and data feeds, 3) organize the information and data feeds, for example, by categories of research areas and/or geography, using a meta-data schema developed for the resource and existing taxonomy and semantic frameworks; 4) design and develop a web portal to allow project teams to publish their data, or links to the data, and present project information in ways that are most relevant and user friendly for researchers in academia, industry, and government; 5) integrate the schema.org COVID-19 annotated data to enable more effective identification, retrieval, and integration of relevant data. A Minimum Viable Product for the website will be developed first, working with stakeholders in the community to prioritize features and add new functionality. In addition to the Information Commons, the project will also assess the effort and feasibility of implementing a data and model commons—to share datasets as well as data-driven models, such as machine learning models related to COVID-19.This RAPID award is made by the Convergence Accelerator program in the Office of Integrative Activities with 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.

# data[].attributes.grants[].keywords
['COVID-19', 'coronavirus', 'researcher collaboration', 'SARS-CoV-2', 'Future pandemic prevention', 'long COVID research', 'COVID research and recovery']

# data[].attributes.grants[].principal_investigator.keywords
['Data science', 'analytics', 'health', 'COVID', 'coronavirus', 'cybersecurity', 'connected healthcare', 'Medical Internet of Things', 'IoT', 'TIPPSS', 'Trust', 'Identity', 'Privacy', 'Protection', 'Safety', 'Security', 'data science', 'STEM', 'researcher collaboration']

# data[].attributes.grants[].principal_investigator.comments
Slack, google group, discord, CIC websiteThank you!

# data[].attributes.title
Development and simulation of fully glycosylated molecular models of ACE2-Fc fusion proteins and their interaction with the SARS-CoV-2 spike protein binding domain