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  • Data set for publication in Cell Host Microbe, Bruggisser et al: Cell-specific targeting by Clostridium perfringens β-toxin unraveled: the role of CD31 as the toxin receptor.
    Data Types:
    • Image
    • Tabular Data
    • Dataset
    • Document
    • Text
  • The dataset is constructed for a project that investigates the coverage and the role of Semantic Scholar (S2) search engine in condunting secondary studies in software engineering.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Text
  • 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.
    Data Types:
    • Dataset
    • Text
  • 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 (data_generation. Rmd): Datasets were generated with this R Notebook. It can be used to update datasets and customize the data generation process. Datasets: • 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.
    Data Types:
    • Software/Code
    • Dataset
    • Text
  • 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.
    Data Types:
    • Other
    • Sequencing Data
    • Tabular Data
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  • Enclosed TIF file contains a compilation of un-cropped immunoblots probed with three different antibodies: 1. Rabbit polyclonal anti-Gαi3 (C-10) (Santa Cruz Biotechnology, Cat# sc-262) 2. Rabbit polyclonal anti-Gαi1/2/3 (Cell Signaling Technology, Cat# 5290) 3. Rabbit polyclonal anti-Gαi3 (Aviva Systems Biology, Cat# OAAB19207) Lead Contact: Mikel Garcia-Marcos, Boston University (mgm1@bu.edu).
    Data Types:
    • Image
    • Dataset
  • Accurate regulation of innate immunity is necessary for the host to efficiently respond to invading pathogen and avoid excessive harmful immune pathology. Here we identified OTUD3 as an acetylation-dependent deubiquitinase that restricts innate antiviral immune signaling. OTUD3 deficiency in mice results in enhanced innate immunity, a diminished viral load, and morbidity. OTUD3 directly hydrolyzes K63-linked poly-ubiquitination of MAVS and thus shuts off innate antiviral immune response. Notably, the catalytic activity of OTUD3 relies on acetylation of its lysine129 residue. In response to virus infection, the acetylated lysine129 is removed by SIRT1, which promptly inactivates OTUD3 and thus allows timely induction of innate antiviral immunity. Importantly, acetyl-OTUD3 levels are inversely correlated with IFN-beta expression in influenza patients. These findings establish OTUD3 as a repressor of MAVS and uncover a previously unknown regulatory mechanism via which the catalytic activity of OTUD3 is tightly controlled to ensure timely activation of antiviral defense.
    Data Types:
    • Image
    • Dataset
  • The following files are associated with the manuscript "Antiradical Activity of Selected Phenolic Acids – FRAP Assay and QSAR Analysis of the Structural Features", MDPI Molecules, 2020. They include geometries of molecules used therein and allows to reproduce the obtained results.
    Data Types:
    • Dataset
    • Text
  • This dataset comprehends data and and associated R code used to run the analysis for the paper. We also include an R Markdown Dynamic document. We tested whether the amount of melanomacrophages and hepatic cellular catabolism substances are influenced by land use changes in the Brazilian Cerrado. Data contains the Environmental matrix (Q) composed of the land use classes for each samplimg site, species trait (R) matrix with content of each pigment in cells, averaged from all individuals, and species composition matrix (L) with the species incidence in all sampling sites.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Text
    • File Set
  • Raw data from single molecule experiments.
    Data Types:
    • Dataset
    • Document
    • Text
    • File Set