The dataset in the file "combined1.csv" included 383 patient's clinical data, including 7 variables: age, sex, location, aneurysm, nidus size, draining type, the number of draining veins, and hemorrhage. Female was defined as 0, male as 1. Superficial AVM was defined as 0, deep AVM as 1, infratentorial AVM as 2. Only superficial draining vein was defined as 0, mixed superficial and deep draining vein as 1. A single draining vein was defined as 1, multiple draining veins as 2. Ruptured AVM was defined as 1, unruptured AVM as 0.
The file "randomtestpredict.R" was the source file in RStudio, which was used to build and test prediction models based on the above data file.
Contributors:Veerle Van Oeckel, Maïté Verloigne, Benedicte Deforche, Nicola D. Ridgers, Elling Bere
Background: Sedentary behaviour guidelines recommend that individuals should regularly break up sitting time. Accurately monitoring such breaks is needed to inform guidelines concerning how regularly to break up sitting time and to evaluate intervention effects. We investigated the concurrent validity of questionnaire items assessing number of breaks in sitting time among children and adolescents.
Methods: Fifty-seven children and adolescents self-reported number of breaks from sitting taken at school, while watching TV and during other screen time activities. Participants also wore an activPAL monitor to objectively assess the number of sitting time breaks (frequency/hour). Concurrent validity was assessed using Spearman rank correlations.
Results: Self-reported number of breaks/hour at school showed good concurrent validity (ρ=0.676). Results were moderate to good for self-reported number of breaks/hour while watching TV (ρ range: 0.482 to 0.536) and moderate for self-reported number of breaks/hour in total screen time (ρ range: 0.377 to 0.468). Poor concurrent validity was found for self-reported number of breaks/hour during other screen time activities (ρ range: 0.157 to 0.274).
Conclusions: Only the questionnaire items about number of breaks at school and while watching TV appear to be appropriate for further use in research focussing on breaks in prolonged sitting among children and adolescents.
Contributors:Maciej Spiegel, Tadeusz Andruniów, Zbigniew Sroka
The following files are associated with the manuscript "Flavones’ and Flavonols’ Antiradical Structure–Activity Relationship—A Quantum Chemical Study", MDPI Antioxidants, 2020 (https://doi.org/10.3390/antiox9060461).
They include geometries of molecules used therein and allows to reproduce the obtained results.
The presented cross-sectional dataset can be employed to analyze the governmental, trade, and competitiveness relationships of official COVID-19 reports. It contains 18 COVID-19 variables generated based on the official reports of 138 countries, as well as an additional 2203 governance, trade, and competitiveness indicators from the World Bank Group GovData360 and TCdata360 platforms in a preprocessed form. The current version was compiled on May 25, 2020.
Please cite as:
• (Data in Brief article)
• Data generation (data_generation. Rmd): Datasets were generated with this R Notebook. It can be used to update datasets and customize the data generation process.
• Country data (country_data.txt): country data.
• Metadata (metadata.txt): the metadata of selected GovData360 and TCdata360 indicators.
• Joint dataset (joint_dataset.txt): the joint dataset of COVID-19 variables and preprocessed GovData360 and TCdata360 indicators.
• Correlation matrix (correlation_matrix.txt): the Kendall rank correlation matrix of the joint dataset.
The COVID-19 pandemic is a worldwide public health crisis. A vaccine with efficacy against SARS-CoV-2, the pathogen that causes COVID-19, is needed. While most vaccines under investigation are optimized to generate an antibody response, we hypothesize that peptide vaccines containing optimized epitope regions with concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation would drive both humoral and cellular immunity with high specificity, potentially avoiding undesired effects such as antibody-dependent enhancement (ADE), all the while providing a platform with fast manufacturing potential and with high shelf-life stability. Here we combine computational prediction of T cell epitopes with recently published B cell epitope mapping studies to propose optimized peptide vaccines for SARS-CoV-2. We begin with an exploration of the predicted T cell epitope space in SARS-CoV-2, with interrogation of HLA-I and -II epitope overlap, protein source, concurrent human/murine coverage, and allelic space. The T cell vaccine candidates were selected by further considering their predicted affinities for MHC-I and MHC-II alleles across the human population (as well as H2-b/H2-d murine coverage to support preclinical studies), predicted immunogenicity, viral protein abundance, sequence conservation, and co-localization of MHC-I and -II epitopes. The predicted B cell epitope regions were selected by starting from responses identified in linear epitope mapping studies of patient serum and filtering to select those with high molecular dynamics-derived surface accessibility, high sequence conservation, spatial localization within functional domains of the spike glycoprotein (RBD, FP, and HR regions), and avoidance of glycosylation sites. From 58 initial candidates, three B cell epitope regions were identified using these criteria. By combining these B cell and T cell analyses, we propose a set of human and murine-compatible SARS-CoV-2 vaccine peptide candidates.
Contributors:Max van Riel, Zidan Yu, Shota Hodono, Ding Xia, Hersh Chandarana, koji fujimoto, Martijn Cloos
Free-breathing MR Fingerprinting acquisitions of the abdomen. One dataset is acquired with the normal ordering, the other with the motion-robust ordering, as described in the article "Optimization of MR Fingerprinting for Free-Breathing Quantitative Abdominal Imaging". The data acquired with the normal ordering shows artefacts caused by respiratory motion, while these artefacts are reduced by using the proposed motion-robust ordering of the acquired k-space.