cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.60773/2seb-yr47
title: Rapid Manufacturing Scale-up for Compact Point-of-Care EUA SARS-CoV-2 RT-PCR Test

description: This prospective clinical study seeks to examine the performance of the device, a sample-to-answer nucleic acid PCR amplification platform solution for the point-of-care (POC) detection of SARS-CoV-2, compared to the Roche 6800 Cobas PCR for SARS-CoV-2 assay. Secondary outcomes include usability and interpretability of results among POC device operators. The goal of this study is to extend the existing EUA approval that the device has (symptomatic participants and healthcare provider obtained specimens) to use among asymptomatic persons and using self-collected mid-turbinate specimens. Note: no device performance data will be included in the dataset.
DOI: 10.25549/examiner-c44-4198
title: Baby tigers for Nu-Pike Zoo -- Long Beach, 1951

description: 4 images. Baby tigers for Nu-Pike Zoo -- Long Beach, June 9, 1951. Earl Hardison -- zoo keeper; Arthur Luke -- zoo employee; Emery.; More descriptive information with originals.
DOI: 10.60773/5ff3-nc70
title: Ultra-Sensitive Immunoassay Test for Quantitation of SARS-CoV-2 Antigen

description: The 5534 study prospective clinical study seeks to examine the performance of the 5534 device, for the detection of SARSCoV-2 nucleocapsid protein antigen compared to the Roche 6800 Cobas PCR for SARS-CoV-2 assay. The goal of the 5534 study is for EUA approval that the device to use among symptomatic persons by trained healthcare personnel collected nasal, saliva, and dried bloodspot specimens. Note: no device performance data will be included in the dataset.
DOI: 10.60773/5061-0a66
title: COVID-19 Test At Home Efficacy Sub-Study

description: This is a sub-study of the COVID-19 Test At Home Study.  The objective is to gather data on performance of Quidel QuickVue for detection of SARS-CoV-2. This sub-study will be used to provide data to Quidel to supplement their existing EUA application for an at-home test. In this study, we will ask asymptomatic participants with known close contact to someone who was positive for SARS-CoV-2 infection within the past seven days to self-administer a Quidel QuickVue test and receive a comparator PCR test at the study site on the first day of   the study. Thereafter, participants will receive a test-kit to perform Quidel QuickVue test daily at home, preferably in the morning, for five consecutive days. Participants will be asked to return to the study site on day 2 for a second PCR test and on the final day (study day 6). However, if any of the home-tests from days 3-5 result as positive or participants develop symptoms and their PCR test result was negative on days 1-2, they will be asked to come to the study-site for a comparator PCR test earlier than day 6. Participants will be given two additional days to return to the study site if they are unable to come on day 6 for an exit PCR; for those participants, they will perform an additional Quidel QuickVue test at home before the standard test at the study site. This means that if they come in on day 6, then no at home test will be performed on days 7 and 8. If they come in on day 7 then they perform a test at home on day 7. If they come in on day 8 then they perform a test at home on days 7 and 8.The primary objective of this sub-study will be to evaluate the performance (positive percent agreement and negative percent agreement) of the Quidel QuickVue test when self-administered by participants in an unsupervised setting at the study site in comparison to a comparator PCR test performed the same day by study staff. Secondary objectives of   this sub-study will be to: 1) evaluate the performance (positive percent agreement and negative percent agreement) of the Quidel QuickVue test when self-administered by participants at home in comparison to a comparator PCR performed at the beginning and end of the study and 2) Compare self-reported interpretation of QuickVue test result with interpretation made by a study staff in-person (on day 1) and digitally (days 2-6).
DOI: 10.60773/54ae-xy13
title: 2183 SARS-CoV-2 Rapid Antigen Test

description: There are two device studies under the 2183 banner. The 2183b study uses an enhanced visual display compared to the original study (2183a), so it has been renamed. These prospective clinical studies seek to examine the performance of the 2183 device (a and b), a lateral flow immunoassay for the point-of-care (POC) detection of SARS-CoV-2 nucleocapsid protein antigen, compared to the Roche 6800 Cobas PCR for SARS-CoV-2 assay. The goal of the 2183b study is for EUA approval for the device to be used among symptomatic persons by trained healthcare personnel collected mid-turbinate specimens. Note: no device performance data will be included in the data files.
DOI: 10.60773/w5vb-c640
title: AFS/SERS Saliva-Based SARS-CoV-2 Earliest Infection and Antibodies Detection

description: This U18 application is responsive to the NIH's RADx-rad Emergency Responses to the COVID-pandemic for new or non-traditional technologies developed for single extracellular vesicle, exosome and extracellular RNA (exRNA) isolation and analysis and reposition them for detection of SARS-CoV-2. The applicant's group is a grantee in the NIH Common Fund "Extracellular RNA Communication (ERC)" Program advancing a new and emerging technology of Acoustofluidic Separation (AFS) for label-free, high yield and purity exosomes from biofluids which is coupled to extracellualr RNA characterization using Surface Enhanced Raman Spectroscopy (SERS) for single EV identification. This U18 application is to reposition the AFS EV technology and SERS for the non-invasive earliest detection of SARS-CoV-2 in saliva of infected patients. Host immunity to SARS-CoV-2 will also be assessed in the saliva samples, permitting the earliest detection of SARS-CoV-2 infection and host immunity non-invasively in a saliva sample.
DOI: 10.60773/wyqe-xw03
title: Diagnosis of MIS-C in Febrile Children

description: The recent emergence of SARS-CoV-2 and resultant pandemic of COVID-19 disease has overwhelmed global health systems and led to over 200,000 American deaths to date. While initial reports suggested that SARS-CoV-2 infection in children was generally benign, a novel post-inflammatory syndrome known as multisystem inflammatory syndrome in children (MIS-C) has now been described. MIS-C in children is characterized by fever, systemic inflammation, and end-organ involvement, and the majority of patients are IgG seropositive for SARS-CoV-2. Because the clinical features of MIS-C overlap with other infections and inflammatory disorders, new strategies for diagnosis of MIS-C in febrile children are urgently needed. Our immediate objective is to determine the reproducible changes in breath, urine, and salivary volatile composition in children diagnosed with MIS-C. We will integrate these discovery studies with clinical and immunological profiling to develop and validate a novel and much-needed MIS-C diagnostic, which is expected to have a major impact on care of febrile children. Our long-term goal to develop a diagnostic strategy to distinguish children with MIS-C from children with other causes of fever.
DOI: 10.25549/examiner-c44-4573
title: Negatives taken by Julian Hartt, 1951

description: 22 images. Negatives taken by Julian Hartt, May 18, 1951.
DOI: 10.5281/zenodo.11185973
title: ELITE SLWR: global 1km 5-min SLDR at SIN Grid-Aqua (2012_245-259)

description: The Essential thermal Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is ELITE surface longwave downward radiation (SLDR) product at 1km spatial resolution and 5-min temporal resolution. It is provided on a Sinusoidal grid and ranges from 2000 to 2022 (continuously updated). This dataset was generated from the Moderate Resolution Imaging Spectrometer (MODIS) data using the algorithms developed by Cheng et al. (2016), Cheng et al. (2017) and Yang and Cheng. (2020).

This is the ELITE SLDR product in 2012 (DOY: 245-259). Please click here to download the ELITE SLDR product in 2013 (DOY: 260-274).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2012-09-01 ~ 2012-09-15

Spatial Resolution: 1 km

Temporal Resolution: 5-min

Data Format: h5

Projection: Sinusoidal

Scale: 0.05

Offset: -1000


Citation(Please cite these papers when using the data):



Cheng J, Liang S. Global estimates for high-spatial-resolution clear-sky land surface upwelling longwave radiation from MODIS data. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(7): 4115-4129. 

Cheng J, Liang S, Wang W, et al. An efficient hybrid method for estimating clear‐sky surface downward longwave radiation from MODIS data. Journal of Geophysical Research: Atmospheres, 2017, 122(5): 2616-2630.

Yang F, Cheng J. A framework for estimating cloudy sky surface downward longwave radiation from the derived active and passive cloud property parameters. Remote Sensing of Environment, 2020, 248: 111972.


 

If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).
DOI: 10.5281/zenodo.11185974
title: ELITE SLWR: global 1km 5-min SLDR at SIN Grid-Aqua (2012_245-259)

description: The Essential thermal Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is ELITE surface longwave downward radiation (SLDR) product at 1km spatial resolution and 5-min temporal resolution. It is provided on a Sinusoidal grid and ranges from 2000 to 2022 (continuously updated). This dataset was generated from the Moderate Resolution Imaging Spectrometer (MODIS) data using the algorithms developed by Cheng et al. (2016), Cheng et al. (2017) and Yang and Cheng. (2020).

This is the ELITE SLDR product in 2012 (DOY: 245-259). Please click here to download the ELITE SLDR product in 2013 (DOY: 260-274).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2012-09-01 ~ 2012-09-15

Spatial Resolution: 1 km

Temporal Resolution: 5-min

Data Format: h5

Projection: Sinusoidal

Scale: 0.05

Offset: -1000


Citation(Please cite these papers when using the data):



Cheng J, Liang S. Global estimates for high-spatial-resolution clear-sky land surface upwelling longwave radiation from MODIS data. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(7): 4115-4129. 

Cheng J, Liang S, Wang W, et al. An efficient hybrid method for estimating clear‐sky surface downward longwave radiation from MODIS data. Journal of Geophysical Research: Atmospheres, 2017, 122(5): 2616-2630.

Yang F, Cheng J. A framework for estimating cloudy sky surface downward longwave radiation from the derived active and passive cloud property parameters. Remote Sensing of Environment, 2020, 248: 111972.


 

If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).
DOI: 10.60773/7gn8-9w03
title: Validation of Smart Masks for Surveillance of COVID-19

description: Vulnerable populations do not just need testing—they need surveillance. The ideal surveillance tool would operate in the background with minimal involvement of the population to be tested; it would be simple, affordable, reliable, and accurate. Unfortunately, no such assay yet exists.  Here, we propose a “smart mask” that changes colors when the wearer has been exposed to biomarkers (proteases) of COVID-19. This is a novel approach to surveillance because most people are already wearing masks—especially in high-risk settings. Our first goal is to optimize the reagents that will test the proteases. We will customize the peptide sequences such that the reagents change color only when two key SARS proteases are present. After characterizing the colorimetric reagents, Aim 2 will integrate these reagents into an adhesive test strip that can be affixed to any existing cloth or surgical mask. Aim 3 is validation with human subjects. First, we will use biobanked saliva samples that are confirmed to be either COVID-19-positive or COVID-19-negative. Next, we will evaluate how long people infected with SARS-CoV-2 must breathe through the smart mask before it changes colors. Finally, we will use the smart mask for surveillance of a population that is concurrently being tested regularly via PCR. We will calculate the sensitivity and specificity of the smart masks through comparison to PCR. We will measure true positives, true negatives, false positives, and false negatives and estimate needing 800 subjects, which is very feasible at our institution.
DOI: 10.60773/1qmd-nt62
title: Understanding the COVID-19, Racism, and Violence Syndemic and Its Effects on COVID-19 Testing Disparities

description: Black communities in the US are experiencing three converging public health crises: COVID-19, systemic racism, and community and police violence. Black Americans are significantly less likely to receive a needed COVID-19 test and have higher rates of COVID-19 infection and death than white Americans. Additionally, Black communities have experienced a surge in gun violence in 2020 and continue to be victims of police harassment and violence, resulting in large-scale social justice demonstrations. The convergence of these epidemics has created a syndemic, wherein racism, violence, and COVID-19 cluster in predominantly Black and low-income communities. The proposed study aims to characterize this syndemic to understand how personal and systemic racism and violence in Black communities may influence COVID-19 testing decisions. This mixed-method study with Black residents of Chicago, IL will result in community-driven recommendations to enhance COVID-19 testing and prevention strategies and address this emerging syndemic. We will examine the potential mediating pathways of medical mistrust, psychological trauma and stress, and economic injustice. Additionally, we will take a strengths-based approach to understand potential protective factors including neighborhood cohesion, social support, and access to health care. The specific aims of the study are to: 1) Qualitatively examine how experiences of racial discrimination, community violence, and police violence influence trust in and engagement with healthcare systems and contribute to decisions around COVID-19 testing and mitigation strategies (e.g. social distancing) among Black individuals in Chicago (N=S0); 2) Quantitatively assess the prevalence and correlates of COVID-19 testing among Black residents in Chicago (N = 500) and characterize the COVID-19, racism, and violence syndemic; and 3) In partnership with a Community Advisory Council, use an integrative translational workshop approach and intervention mapping techniques to develop community and data-driven recommendations and an intervention blueprint for local health departments, researchers, and public health organizations to improve COVID-19 testing among Black Americans. This study will result in policy and research recommendations, community resources, and a 'shovel-ready' intervention blueprint to enhance COVID-19 testing and address this emerging syndemic
DOI: 10.60773/dwzp-am60
title: Multi-Modal Wireless COVID Monitoring and Infection Alerts for Concentrated Populations

description: We plan to extend and improve our COH/PHD system in using wearables for the early detection of COVID-19 infection. With the over 5,000 patients who have been recruited in our original Phase 1 IRB- approved study, we will further optimize our algorithms, especially on its application in individuals with diverse ethnic backgrounds (Aim 1) . We will further integrate and optimize MyPHD and COH to enable real- time online detection of COVID-19 (Aim 2). We will deploy MyPHD/COH on the different concentrated populations including pediatric kidney transplant patients, Pac-12 student athletes, and senior living residents (Aim 3)
DOI: 10.15468/dl.dpwsu7
title: Occurrence Download

description: A dataset listing the 3533 species recorded in GBIF matching the query:
{
 "and" : [
 "DatasetKey is INSDC Host Organism Sequences",
 "TaxonKey is Viruses"
 ]
}

 The dataset's 3533 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016194-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60773/tca1-nb16
title: SF-RAD: Development and Proof-of-Concept Implementation of the South Florida Miami RADx-rad SARS-CoV-2 Wastewater-Based Surveillance Infrastructure

description: The University of Miami (UM), with three primary campuses in Miami, Florida, is geographically spread within one of the worst current COVID-19 hotbeds. UM has deployed an elaborate human surveillance testing, tracking and tracing (3T) system to monitor the student body, faculty, and staff.  This 3T system includes a major hospital that is part of UM and that treats COVID-19 patients. To augment this COVID-19 monitoring system, UM has deployed a pilot wastewater surveillance program for detecting SARS-CoV-2 from clusters of buildings on campus. Weill Cornell Medicine (WCM) is located in New York City, NY, an area that until recently had one of the worst outbreaks of COVID-19. WCM has established an international consortium for SARS-CoV-2 environmental surveillance, including in NYC and globally with the MetaSUB Consortium, which is creating metagenomic and metatranscriptomic maps of the world’s sewage. Based on this work at both UM and WCM, this proposal aims to develop, implement, and demonstrate effective and predictive wastewater surveillance by optimizing sampling, concentration, and detection strategies. Working closely with the RADx-rad Data Coordination Center (DCC), this application (SF-RAD) will develop and implement data standards and informatics infrastructure and perform integrative analyses to make all data, results, and models available to the community, thus providing a critical contribution to the national SARS-COV-2 RADx-rad Wastewater Detection Consortium. Our objectives will be addressed through three aims. Aim 1: Data Standardization, focuses on developing and implementing data standards and quality metrics, and establishing the operational infrastructure to manage SARS-CoV-2 wastewater-based surveillance datasets and metadata. Aim 2: Wastewater Characterization, focuses on optimizing wastewater surveillance protocols and parameters for wastewater sampling, sample concentration, and viral detection technologies. Aim 3: Integration with Human Health Surveillance, focuses on metatranscriptomic analyses and on the integration of wastewater quantification data with community and hospital COVID-19 prevalence, to develop predictive models to detect local and community level spread of COVID-19. All data will be made Findable, Accessible, Interoperable and Reusable (FAIR) in close collaboration with the DCC, and will be collected and managed with attention to ethical issues in surveillance and data management, including efforts to ensure research rigor and reproducibility. The results from this proposal will develop and deploy experimental and informatics infrastructure and operations as part of the national RADx-rad SARS-CoV-2 wastewater surveillance network and will provide a proof-of-concept implementation to use wastewater for infectious disease surveillance for early detection of localized COVID-19 outbreaks.
DOI: 10.25549/examiner-c44-3682
title: Luncheon, 1951

description: 4 images. Luncheon, June 8, 1951. Vivian Kellems; Paul Easton.
DOI: 10.60773/6e21-bq61
title: Bioinformatics Framework for Wastewater-based Surveillance of Infectious Diseases

description: COVID-19 is expected to become one of the largest mass casualty events in the history of the United States (U.S.). Assessment of the true burden of disease in the population is needed for the prevention and mitigation of this and future viral disease outbreaks. Currently, testing of new cases (via swabs / saliva) and those previously exposed (via serum) has limited reach in the population. However, an alternative approach relying on the analysis of community wastewater can screen up to 70% of the U.S. population on a weekly basis at <0.01% of the cost of clinical screening of individuals. As a population-wide infectious disease surveillance tool, wastewater-based epidemiology (WBE) can be used to complement current surveillance methods to better understand disease burden and how these burdens differ across communities. The goal of our proposed RADx-rad supplement is to implement and evaluate a near real-time WBE framework for SARS-CoV-2 by (i) assessing in near real-time community spread of the new coronavirus, (ii) significantly increasing the fraction of the U.S. population screened, the frequency at which this testing is being completed (weekly) and the geospatial resolution of screening (from city-wide to neighborhood-specific), (iii) comparing novel coronavirus levels in wastewater with the burdens of infection, disease and mortality reported by local health systems, (iv) harvesting high throughput sequence (HTS) data on SARS-CoV-2 variants across the U.S., (v) optimizing pipelines for HTS analysis, and (vi) immediately sharing any new knowledge gained with the RADx-rad Data Coordinating Center (DCC), research community, and the general public via an expansion of our online dashboard that was pioneered by the proposing team in collaboration with the City of Tempe, AZ.We will leverage previously developed, peer-reviewed strategies for population-wide virus monitoring via reverse transcription real-time polymerase chain reaction (RT-qPCR), HTS, sequence analysis, and data communication originally developed for our parent award to quickly provide a data stream and scientific resource for managing the COVID-19 epidemic in the U.S.In Aim 1, develop a wastewater-based epidemiology (WBE) bioinformatics framework for SARS-CoV-2 at the national, city and intra-sewershed or neighborhood-level to produce RT-qPCR and SARS-CoV-2 RNA-seq data for studying the distribution of viral levels and genetic polymorphisms in the community. In Aim 2, we will evaluate a WBE bioinformatics framework for translating SARS-CoV-2 data from RT-qPCR and high-throughput sequencing into information for monitoring population health. Successful completion of this biomedical informatics project will provide the U.S. with an early warning system for SARS-CoV-2 detection and a tracking aid for public health epidemiologists seeking to reduce morbidity and mortality from infectious diseases like COVID-19 in the U.S.