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358 results for “SAR studies”
Simulation results for Sars-CoV2 3C-like main protease: TRAPP analysis of the binding site flexibility and results of the docking study
<p>Collection of data and scripts related to the paper:</p> <p>Jonas Gossen et al. "A blueprint for high affinity SARS-CoV-2 Mpro inhibitors from activity-based compound library screening guided by analysis of protein dynamics" </p> <p>https://www.biorxiv.org/content/10.1101/2020.12.14.422634v2 doi: https://doi.org/10.1101/2020.12.14.422634</p> <p>ACS Pharmacology and Translational Science 2021 DOI: 10.1021/acsptsci.0c00215</p> <p> </p> <p> </p> <p><strong>1. TRAPP simulation results for Sars-CoV2 3C-like main protease:</strong></p> <p>include simulation of the binding pocket druggability, physical-chemical properties, and the binding site composition</p> <p><a href="https://zenodo.org/api/files/f6c0a0ae-d53a-4e78-aaaf-b3ff674171a5/Protease_clean.ipynb">Protease_clean.ipynb</a> - Jupyter Notebook containing analysis of the generated data</p> <p><a href="https://zenodo.org/api/files/f6c0a0ae-d53a-4e78-aaaf-b3ff674171a5/allTables.zip">allTables.zip</a> - results of TRAPP simulations of the binding site flexibility using LRIP and tConcoord methods</p> <p><a href="https://zenodo.org/api/files/f6c0a0ae-d53a-4e78-aaaf-b3ff674171a5/Every10-ligand_6LU7_R3.5.zip">Every10-ligand_6LU7_R3.5.zip</a> - results of TRAPP pocket analysis on the MD frames</p> <p><a href="https://zenodo.org/api/files/f6c0a0ae-d53a-4e78-aaaf-b3ff674171a5/PDB-Giulia.zip">PDB-Giulia.zip</a> - TRAPP pocket analysis of 40 PDB complexes of main protease</p> <p><a href="https://zenodo.org/api/files/f6c0a0ae-d53a-4e78-aaaf-b3ff674171a5/TRAPP_properties_PDB.xlsx">TRAPP_properties_PDB.xlsx</a> - binding pocket properties for 40 PDB complexes of main protease summarized in a table</p> <p><a href="https://zenodo.org/api/files/f6c0a0ae-d53a-4e78-aaaf-b3ff674171a5/DrugPDB_3structures.xlsx">DrugPDB_3structures.xlsx</a> - binding pocket properties for 3 PDB structures </p> <p><strong>2. Docking & Screening Results</strong></p> <p><a href="https://zenodo.org/api/files/9165535d-aec5-4f1e-8ad1-6ca11a90e595/TRAPP_secondSelection_VS.csv">TRAPP_secondSelection_VS.csv</a> - docking/screening of selected structures from TRAPP analysis</p> <p><a href="https://zenodo.org/api/files/9165535d-aec5-4f1e-8ad1-6ca11a90e595/Fred_VS.csv">Fred_VS.csv</a> - docking of PDB structures using Fred</p> <p><a href="https://zenodo.org/api/files/9165535d-aec5-4f1e-8ad1-6ca11a90e595/Glide_VS.csv">Glide_VS.csv</a> - docking of PDB structures using Glide</p> <p><a href="https://zenodo.org/api/files/77b1679d-ccc9-4e30-add2-5f7420e04ed1/TableS1.xlsx">TableS1.xlsx</a> - Available structures of SARS-CoV-2 Mpro selected for binding site analyses. </p> <p><a href="https://zenodo.org/api/files/77b1679d-ccc9-4e30-add2-5f7420e04ed1/TableS2A.xlsx">TableS2A.xlsx</a> - SiteScore analysis of all the deposited X-ray crystal structures for the Mpro.</p> <p><a href="https://zenodo.org/api/files/77b1679d-ccc9-4e30-add2-5f7420e04ed1/TableS2B.xlsx">TableS2B.xlsx</a> - SiteScore analysis of the MSM ensemble (4-macrostates).</p>
Diet and SARS-Cov-2 Infection Risk: A Retrospective Observational Study
<p>Dataset, Analysis, Regression and Description.</p> <p>From mid-summer 2020 to January 2022, based on phase 2 to 3 of a self-reported questionnaire survey, we asked 15851 families across Iran about their diet and their COVID-19 disease. The results showed that some diets increased the risk of SARS-Cov-2 Apparent Infection Risk and some reduced it.</p> <p>The results show that the risk of reporting SARS-CoV-2 apparent infection in the second group was 12 times higher than the Third group. <strong>The two-tailed P value is less than 0.0001</strong>. Also, the risk of reporting SARS-CoV-2 apparent infection in the first group was 9 times higher than the Third group. <strong>The two-tailed P value is less than 0.0001</strong>. By conventional criteria, these differences are considered to be extremely statistically significant.</p>
Dataset of "Exposure to airborne SARS-CoV-2 in four hospital wards and ICUs of Cyprus. A detailed study accounting for day-to-day operations and aerosol generating procedures."
<p>The authors highly appreciate being contacted if the data is to be used for any purpose.</p> <p>The following data set was used in the study entitled "<strong>Exposure to airborne </strong><strong>SARS-CoV-2 in four hospital wards and ICUs of Cyprus. A detailed study accounting for day-to-day operations and aerosol generating procedures.</strong>" and published in <em>Heliyon</em> Journal.</p> <p>This study characterized the transmission dynamics of airborne SARS-CoV-2 in normal and intensive care units. The data were collected over the period of 2020. In total, 165 and 62 air and environmental samples, respectively, were collected in four COVID-19 wards and ICUs in Cyprus and analyzed by RT-PCR. The comparison between RT-PCR and an alternative method for SARS-CoV-2 detection in air that provides comparable results but is less cumbersome and time demanding, is also given in the tab "Comparison with BELD".</p> <p>The data from sampling airborne SARS-CoV-2 using a MOUDI impactor are not included in this document but can be found in the supplement of the relevant publication.</p> <p>Please refer to the manuscript and its supplementary material for more information about how the data was collected. </p> <p> </p>
Studied disinfectant substances against SARS-CoV-2 and other coronaviruses
<p>This data-sheet covers those disinfectants tested against SARS-CoV-2 or other coronaviruses. Data were extracted from several research articles indicated in the reference row. The data-sheet comprises a total of 11 fields with info regarding the virus (virus and strain/isolate names), formulation (substance(s) and its concentration in percentage) and test characteristics (suspension or surface tested, kind of surface, use dilution before testing, disinfectant and inoculum volumes, organic load type and concentrations and contact time) as well as their results, normalized in terms of Log<sub>10 </sub>viral infectivity reduction. Data is included and comented in the following journal article: <a href="https://doi.org/10.3390/foods10020283">https://doi.org/10.3390/foods10020283</a> Please reference also to this publication if using the data-sheet.</p>
Supplementary Data -A STUDY ON SOME STRUCTURAL FEATURES RESPONSIBLE FOR SARS-COV-2 INFECTION FATALITY
<p>A correlation between hydrodynamic properties like radius of gyration ( Rg ) vs Molecular weight of spike protein of SARS - COV-2 biopolymers .</p>
Epidemiology, risk factors and clinical course of SARS-CoV-2 infected patients in a Swiss university hospital: an observational retrospective study
<p>This is the dataset of the study called "Epidemiology, risk factors and clinical course of SARS-CoV-2 infected patients in a Swiss university hospital: an observational retrospective study". <br> <br> <strong>Abstract: </strong></p> <p>Background<br> Coronavirus disease 2019 (COVID-19) is now a global pandemic with Europe and the USA at its epicenter. Little is known about risk factors for progression to severe disease in Europe. This study aims to describe the epidemiology of COVID-19 patients in a Swiss university hospital.</p> <p>Methods<br> This retrospective observational study included all adult patients hospitalized with a laboratory confirmed SARS-CoV-2 infection from March 1 to March 25, 2020. We extracted data from electronic health records. The primary outcome was the need to mechanical ventilation at day 14. We used multivariate logistic regression to identify risk factors for mechanical ventilation. Follow-up was of at least 14 days. <br> <br> Results<br> 200 patients were included, of whom 37 (18·5%) needed mechanical ventilation at 14 days. The median time from symptoms onset to mechanical ventilation was 9·5 days (IQR 7.00, 12.75). Multivariable regression showed increased odds of mechanical ventilation in males (3.26, 1.21-9.8; p=0.025), in patients who presented with a qSOFA score ≥2 (6.02, 2.09-18.82; p=0.001), with bilateral infiltrate (5.75, 1.91-21.06; p=0.004) or with a CRP of 40 mg/l or greater (4.73, 1.51-18.58; p=0.013). <br> <br> Conclusions<br> This study gives some insight in the epidemiology and clinical course of patients admitted in a European tertiary hospital with SARS-CoV-2 infection. Male sex, high qSOFA score, CRP of 40 mg/l or greater and a bilateral radiological infiltrate could help clinicians identify patients at high risk for mechanical ventilation.</p>
AutoDock and CB-Dock data for (NPA)6Zn3(H2O)2 in Synthesis, structural analysis, and docking studies with SARS-CoV-2 of a trinuclear zinc complex with N-phenylanthranilic acid ligands
<p>AutoDock 4.2 and CB-Dock data for (NPA)<sub>6</sub>Zn<sub>3</sub>(H<sub>2</sub>O)<sub>2</sub> with M<sup>pro</sup> from SARS-CoV-2 from PDB Id: 6LU7. </p>
NMR data for (NPA)6Zn3(H2O)2 in Synthesis, structural analysis, and docking studies with SARS-CoV-2 of a trinuclear zinc complex with N-phenylanthranilic acid ligands
<p><sup>1</sup>H, <sup>13</sup>C, COSY, HMBC, and HSQC NMR data in fid format for (NPA)<sub>6</sub>Zn<sub>3</sub>(H<sub>2</sub>O)<sub>2</sub> (NPA = 2-(phenylamino) benzoate) in DMSO-<em>d</em><sub>6.</sub></p>
Vitamin D deficiency and SARS‑CoV‑2 infection: D-COVID study
<p>D-COVID is a proyect to study the association between COVID-19 infection and vitamin D deficiency in patients of a terciary university hospital. To investigate the clinical evolution and prognosis of patients with COVID-19 and vitamin D deficiency, several queries qere launched into a Database containing plain text apparitions of certain terms in medical reports, as well as structured data. These apparitions were detected using NLP technology, and then saved individually in a database. The presented dataset is a bounded version of such database, containing only relevant data to the one extracted for the associated study. As for the strcture of the dataset, each row represents an apparition of a term in plain text, and the columns contain additional information.</p> <p><strong>- reportdate</strong>: date of the report where the term appears up.</p> <p><strong>- admission_days:</strong> strctured data days in hospitalization, if any.</p> <p><strong>- patient_id</strong>: anonymized patient identifier</p> <p><strong>- sex</strong>: patient sex (1=male, 2=female)</p> <p><strong>-birthdate</strong>: patient birthdate</p> <p><strong>- service</strong>: Service where the report was generated</p> <p><strong>- report_type:</strong> Type of report generated (either a discharge report, note, etc)</p> <p><strong>- record</strong>: unique identifier for the report itself</p> <p><strong>- term</strong>: term (that was read (NLP takes synonims and acronyms into account)</p> <p><strong>- exitus</strong>: medical exitus, if available in structured data, it could also be found in plan text in the previous column.</p>
Seroprevalence of IgG antibodies against SARS coronavirus 2 in Belgium – a serial prospective cross-sectional nationwide study of residual samples (March – October 2020)
<p>This dataset contains information on seven prospective cross-sectional nationwide residual sera collection rounds. The samples were analyzed for IgG antibodies against S1 proteins of SARS-CoV-2 with a semi-quantitative commercial ELISA (EuroImmun, Luebeck, Germany).</p> <p>We provide a CSV file containing the following variables:</p> <ul> <li><strong>code</strong>: unique sample code</li> <li><strong>age_cat</strong>: age categories by 10-year age bands (0-10, 10-20, ..., 80-90, 90-Inf), the lower limit is included, e.g. 0-10 = [0,10)</li> <li><strong>sex</strong>: sex (f = female, m = male)</li> <li><strong>province</strong>: province of residence (11 categories)</li> <li><strong>region</strong>: region of residence (3 categories: Brussels, Flanders, Walloon)</li> <li><strong>collection_round</strong>: collection round (values 1 to 7)</li> <li><strong>collection_start</strong>: start date of the collection round</li> <li><strong>collection_end</strong>: end date of the collection round</li> <li><strong>igg_orig</strong>: measured IgG OD value as character (note, a semi-quantitative ELISA was used, i.e. this should not be interpreted continiously)</li> <li><strong>igg_cat</strong>: categorized IgG OD values <ul> <li><em>LoD</em>: IgG OD < 0.15</li> <li><em>negative</em>: 0.15 ≤ IgG OD < 0.8</li> <li><em>borderline</em>: 0.8 ≤ IgG OD < 1.1</li> <li><em>positive</em>: 1.1 ≤ IgG OD</li> </ul> </li> </ul> <p>Please see publication mentioned underneath for more details (<a href="https://doi.org/10.1101/2020.06.08.20125179">https://doi.org/10.1101/2020.06.08.20125179</a>).</p> <p><strong>Funding:</strong> This work received funding from the European Union's Horizon 2020 research and innovation program - project EpiPose (No 101003688), the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement 682540 TransMID), the Flemish Research Fund (FWO 1150017N) and from The Antwerp University Fund; which is a community of donors who contribute to research and education with their personal commitment through a donation, gift, bequest or through academic chairs. The funders had no role in study design, data collection, data analysis, data interpretation, writing or submitting of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.</p>
The CHASING COVID Cohort Study: A national, community-based prospective cohort study of SARS-CoV-2 pandemic outcomes in the USA
<p>The Communities, Households and SARS-CoV-2 Epidemiology (CHASING) COVID Cohort Study is a community-based prospective cohort study launched during the upswing of the USA COVID-19 epidemic. The objectives of the cohort study are to: (1) estimate and evaluate determinants of the incidence of SARS-CoV-2 infection, disease and deaths; (2) assess the impact of the pandemic on psychosocial and economic outcomes and (3) assess the uptake of pandemic mitigation strategies. 6740 people are enrolled in the cohort, including participants from all 50 US states, the District of Columbia, Puerto Rico and Guam. Participants are contacted regularly to complete study assessments, including interviews and dried blood spot specimen collection for serologic testing.</p> <p>Datasets are provided in CSV and sas7bdat (with formatting script) file formats.</p>
Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study
<p>Data and code for publication on <em>Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study</em></p>
Dataset SeBluCo study: SARS-CoV-2-antibodies among German blood donors 2020 – 2022, a repetitive cross-sectional study
<p>The dataset is the result of a repetitive cross-sectional study in 28 regions in Germany on SARS-CoV-2 antibodies in residual samples of blood donors from April 2020 to April 2021, September 2021 and April/May 2022. These data were used to aide in monitoring the pandemic in Germany. Data were completely anonymised at the site of sample collection. Serological test results are accompanied by demographic data including sex, age and area of residence (assigned a level two Nomenclature des Unités Territoriales Statistiques (NUTS2)). </p><p>The file contains data (sheet "data") as well as the description of variable content and coding (sheet "variables").</p>
COVID-19 Study Assessing the Virologic Efficacy of REGN10933+REGN10987 Across Different Dose Regimens in Adult Outpatients With SARS-CoV-2 Infection
ClinicalTrials.gov study NCT04666441. IPD Sharing: YES. Countries: 1. Publications: 3.
Data from: Optimizing passive acoustic monitoring (PAM) for Biodiversity Studies: using species-area relationship (SAR) to predict species richness
Open the record for dataset details and reuse information.
SARS-CoV-2 detection dogs - a pilot study
<p>The outstanding olfactory acuity of canines led us to consider whether dogs are able to reliably detect the odour of respiratory diseases associated with a SARS-CoV-2 infection in saliva or tracheobronchial secretion of hospitalized COVID-19 patients. Furthermore, we examined if SARS-CoV-2 detection dogs could provide an appropriate screening method for the human virus.The aim of this data publication is to provide the data acquired in the controlled, randomized and double-blinded pilot study `Scent dog identification of SARS-CoV-2 infection’ (submitted to BMC Infectious Diseases).</p>
VTR case studies datasets: myoglobin against hemoglobin, RBDs of SARS-CoV-1 vs. SARS-CoV-2, and glucose-tolerant vs. non-tolerant β-glucosidases
<p>Description of the four files:</p> <ol> <li><strong>contacts.xlsx</strong> <ul> <li>List of detected contacts for the three case studies</li> </ul> </li> <li><strong>pymol_files_case_study_1.zip</strong> <ul> <li>Contains files in PDB format of the analyzed structures, and files in PML format used to display visualizations in the PyMOL tool for the case study 1: comparison between contacts of myoglobin against hemoglobin</li> </ul> </li> <li><strong>pymol_files_case_study_2.zip</strong> <ul> <li>Contains files in PDB format of the analyzed structures, and files in PML format used to display visualizations in the PyMOL tool for the case study 2: comparison between contacts of RBDs of SARS-CoV-1 vs. SARS-CoV-2 both complexed with the cell receptor ACE2</li> </ul> </li> <li><strong>pymol_files_case_study_3.zip</strong> <ul> <li>Contains files in PDB format of the analyzed structures, and files in PML format used to display visualizations in the PyMOL tool for the case study 3: comparison between contacts of glucose-tolerant vs. non-tolerant β-glucosidases </li> </ul> </li> </ol>
Pandemic-related Attitudes, Stressors and Work Outcomes among Medical Assistants during the SARS-CoV-2 ("Coronavirus") Pandemic in Germany: a cross-sectional Study
<p>File type: SPSS file (.sav)</p> <p>Study type: Cross-sectional study</p> <p>Population: Medical assistants in Germany</p> <p>Study period: April 7th-April 14th, 2020</p> <p>Number of participants: 2150</p> <p>Research question: Investigation of pandemic-related attitudes, stressors and work outcomes among medical assistants during the SARS-CoV-2 (“Coronavirus”) pandemic</p> <p>Missing values: None (due to online survey) </p> <p>Original variables: v_982, v_1, v_2, v_3, v_5, v_6, v_7, v_13, v_14, v_21, v_22, v_23, v_24, v_26, v_27, v_28, v_29, v_31, v_32, v_33, v_40, v_41, v_42, v_43, v_46, v_47, v_48 v_49, v_52, v_57, Beruf_MFA</p> <p>All other variables were calculated from the original variables either by rescaling or dichotomization. </p>
SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study
<p><strong>Background</strong>: Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions.</p> <p><strong>Methods</strong>: We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss.</p> <p><strong>Findings</strong>: The use of high efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% CrI: 73.1% - 85.7%) and 87% (CrI: 80.0% - 92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation.</p> <p><strong>Conclusions</strong>: Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.</p>
Attitudes and Stressors related to the SARS-CoV-2 Pandemic among Emergency Medical Services Workers in Germany: A cross-sectional Study
<p>This dataset stems from a cross-sectional study conducted in April and Mai 2020 among n=1537 emergency medical services workers (EMS) from entire Germany during the first peak of the SARS-CoV-2 pandemic. The study questionnaire was distributed online with help of the German Association of Emergency Medical Service on their social media channels. The collected data provides insights into major stressors among EMS workers at the first peak of the pandemic in Germany and allows for analysis of possible determinants of major stressors via logistic regression analysis. No funding was obtained for this study.</p> <p> </p> <p><strong>Research question:</strong></p> <p>Investigation of pandemic-related attitudes, stressors and work outcomes among emergency medical services workers during the SARS-CoV-2 pandemic</p> <p><strong>Study population: </strong></p> <p>Emergency medical services workers in Germany</p> <p><strong>Study type: </strong></p> <p>Cross-sectional study (two independent cross-sectional waves)</p> <p><strong>File type: </strong></p> <p>SPSS file (.sav)</p> <p><strong>Study periods: </strong></p> <p>First wave: April 9th-16th 2020<br> Second wave: Mai 14th-21st 2020</p> <p><strong>Number of participants: </strong></p> <p>1537</p> <p><strong>Missing values: </strong></p> <p>None (due to online survey) </p> <p><strong>Original variables: </strong></p> <p>v_982, v_1, v_2, v_31, v_4, v_5, v_7, dupl1_v_13, dupl1_v-14, v_57, v_13, v_37, v_38, v_39, v_40, v_41, v_42, v_43, v_44, v_45, v_46, v_47, v_48, v_49, v_50, dupl1_v_40, dupl1_v_41, dupl1_v_42, dupl1_v_43, v_55, Beruf_Rettungsdienst, Welle</p> <p>All other variables were calculated from the original variables either by rescaling or dichotomization. </p> <p>Dichotomization of attitudes, stressors and work outcomes: <br> Answer options "Strongly disagree" and "Disagree" were labelled as "no"<br> Answer options "Agree" and "Strongly Agree" were labelled as "yes"</p> <p>Dichotomization of self-rated health:<br> Answer options "Very bad", "Bad" and "Moderate" were labelled as "Bad".<br> Answer options "Good" and "Very good" were labelled as "Good".</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.