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ShareScore release 0.9.0
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210 results for “Ebola”
Data from: Impact of the Ebola outbreak on Trypanosoma brucei gambiense infection medical activities in coastal Guinea, 2014-2015: a retrospective analysis from the Guinean national Human African Trypanosomiasis control program
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Data from: Ebola cases and health system demand in Liberia
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Data from: Impact of the Mass Drug Administration for malaria in response to the Ebola outbreak in Sierra Leone
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Data from: Investigating the zoonotic origin of the West African Ebola epidemic
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Data from: How Ebola impacts social dynamics in gorillas: a multistate modelling approach.
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Data from: Spatial spread of the West Africa Ebola epidemic
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Data from: Avoidable errors in the modeling of outbreaks of emerging pathogens, with special reference to Ebola
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The transcriptomic profiling of COVID-19 compared to SARS, MERS, Ebola, and H1N1
<p><strong>COVID-19 </strong>pandemic is a global crisis that threatens our way of life. As of April 29, 2020, COVID-19 has claimed more than 200,000 lives, with a global mortality rate of ~7% and recovery rate of ~30%. Understanding the interaction of cellular targets to the SARS-CoV2 infection is crucial for therapeutic development. Therefore, the aim of this study was to perform a comparative analysis of transcriptomic signatures of infection of COVID-19 compared to different respiratory viruses (Ebola, H1N1, MERS-CoV, and SARS-CoV), to determine unique anti-COVID1-19 gene signature. We identified for the first time molecular pathways for Heparin-binding, RAGE, miRNA, and PLA2 inhibitors, to be associated with SARS-CoV2 infection. The <em>NRCAM</em> and <em>SAA2</em> that are involved in severe inflammatory response, and <em>FGF1</em> and <em>FOXO1</em>genes, which are associated with immune regulation, were found to be associated with a cellular gene response to COVID-19 infection. Moreover, several cytokines, most significantly the <em>IL-8</em>, <em>IL-6</em>, demonstrated key associations with COVID-19 infection. Interestingly, the only response gene that was shared between the five viral infections was <em>SERPINB1</em>. The PPI study sheds light on genes with high interaction activity that COVID-19 shares with other viral infections. The findings showed that the genetic pathways associated with Rheumatoid arthritis, AGE-RAGE signaling system, Malaria, Hepatitis B, and Influenza A were of high significance. We found that the virogenomic transcriptome of infection, gene modulation of host antiviral responses, and GO terms of both COVID-19 and Ebola are more similar compared to SARS, H1N1, and MERS. This work compares the virogenomic signatures of highly pathogenic viruses and provides valid targets for potential therapy against COVID-19.</p> <p><strong>Supplementary tables and figures</strong></p> <p><strong>Figure 1</strong> : Significant DEGs across the five transcriptomic profiles , corresponding genes, chromosome locations, gene expression and significance scores. The DEGs related genes and chromosomal location (A). The DEGs information regarding host response to COVID-19 (B), Ebola (C), MERS-CoV (D) , H1N1 (E) and SARS-CoV (F) viral infections. The pvalues were scaled were scaled across gene profiles according to maximum and minimum values (ppvalue). The circles size and color is linked to DEGs significance and gene expression (LogFC) scores, respectively.</p> <p><strong>Figure 2 : </strong>Analysis of the gene enrichment of DEGs correlated with the host response to COVID-19. Categories of GO terms (A), significance scores (-10log-pvalue) (B), and number of associated DEGs (C). The COVID-19-associated DEGs (D), status across the studied infectious diseases (E), and selected linked GO terms (F).</p> <p><strong>Figure 3: </strong>The Venn diagram of viral associated genes. The number of uniquely shared genes associated with the host response to COVID-19, Ebola, H1N1, MERS-CoV, and SARS-CoV viral infections.</p> <p><strong>Figure 4: </strong>The Venn diagram of viral associated GO terms. The number of uniquely shared GO terms of DEGs associated with the host response across COVID-19, Ebola, H1N1, MERS-CoV, and SARS-CoV viral infections.</p> <p><strong>Figure 5: </strong>The PPIs network of DEGs associated with COVID-19. The PPI of host expressed DEGs under COVID-19 infection. DEGs shared between COVID-19 and Ebola, H1N1, MERS-CoV, and SARS-CoV are color-coded according to kind of infection. The gene node size is relative to its interaction activity. DEGs are collected in different groups according to their level of interaction activity.<br> </p> <p><strong>Figure 6: </strong>The PPIs network and gene enrichment analysis of highly interactive genes associated with COVID-19.</p> <p><strong>Figure S1 :</strong> The PPI network and gene enrichment analysis of the 173 genes that characterized the host response of COVID-19.</p> <p><strong>Figure S2: </strong>The PPI network and gene enrichment analysis of the 58 genes that are uniquely shared between COVID -19 and Ebola viral infections .</p> <p><strong>Figure S3 : </strong>The PPI network and gene enrichment analysis of the 51 genes that are uniquely shared between COVID-19 and MERS-CoV viral infections.</p> <p><strong>Figure S4 : </strong>The PPI network and gene enrichment analysis of the 31 genes that are uniquely shared between COVID-19, Ebola, and MERS-CoV viral infections.</p> <p><strong>Figure S5</strong> : The gene expression heatmap of genes COVID-19 shares with different viral infections.</p> <p><strong>Figure S6 : </strong>The PPI network and gene enrichment analysis of genes that are differentially expressed across studied viral infections and shared with COVID-19.</p> <p><strong>Table </strong><strong>S</strong><strong>1 : </strong>The data information used in this study.</p> <p><strong>Table S</strong><strong>2</strong>: The information of DEGs associated the host response of COVID-19, Ebola, H1N1, MERS-CoV, and SARS-CoV viral infections.</p> <p><strong>Table S</strong><strong>3</strong>: The Venn analysis results of DEGs and GO terms uniquely shared across of COVID-19, Ebola, H1N1, MERS-CoV, and SARS-CoV viral infections.</p> <p><strong>Table S</strong><strong>4</strong>: Selected gene enrichment analysis of uniquely shared group of genes across the host response of COVID-19, Ebola, H1N1, MERS-CoV, and SARS-CoV viral infections.</p> <p><strong>Table S</strong><strong>5</strong>: The gene expression information of DEGs that COVID-19 share with the studied infectious diseases.</p> <p><strong>Table S</strong><strong>6</strong>: Selected gene enrichment analysis of uniquely shared group of GO terms across the host response of COVID-19 and studied viral infections.</p>
Supporting transcriptomic data for: "Human transcriptomic response to the VSV-vectored Ebola vaccine"
<p>This is the complete dataset of transcriptomic data obtained from whole blood RNA of volunteers vaccinated with a high dose of the rVSV-ZEBOV vaccine against Ebola virus disease in the Geneva clinical trial.</p> <p>The Counts_Table.csv file contains gene expression data (counts) for genes in the Ion Ampliseq human Gene expression kit panel. </p> <p>The Descriptive_Table.csv contains descriptive data of the subjects for differential expression analysis.</p>
Data from: Scalable, semi-automated fluorescence reduction neutralization assay for qualitative assessment of Ebola virus-neutralizing antibodies in human clinical samples
Antibody titers against a viral pathogen are typically measured using an antigen binding assay, such as an enzyme-linked immunosorbent assay (ELISA), which only measures the ability of antibodies to identify a viral antigen of interest. Neutralization assays measure the presence of virus-neutralizing antibodies in a sample. Traditional neutralization assays, such as the plaque reduction neutralization test (PRNT), are often difficult to use on a large scale due to being both labor and resource intensive. Here we describe an Ebola virus fluorescence reduction neutralization assay (FRNA), which tests for neutralizing antibodies, that requires only a small volume of sample in a 96-well format and is easy to automate. The readout of the FRNA is the percentage of Ebola virus-infected cells measured with an optical reader or overall chemiluminescence that can be generated by multiple reading platforms and the readout is compatible with lytic and non-lytic viruses. Using blinded human clinical samples (EVD survivors or contacts) obtained in Liberia during the 2013–2016 Ebola virus disease outbreak, we demonstrate that FRNA-measured antibody titers are highly correlated with those measured by the Filovirus Animal Non-clinical Group (FANG) ELISA - the current standard for anti-EBOV antibody measurement with the important distinction of providing information on the neutralizing capabilities of the antibodies.
Community trust of government and non-governmental organizations during the 2014-16 Ebola epidemic in Liberia - survey responses
<p>The West African Ebola Virus Disease epidemic of 2014-16 cost more than 11,000 lives. Interventions targeting key behaviors to curb transmission, such as safe funeral practices and reporting and isolating the ill, were initially unsuccessful in a climate of fear, mistrust, and denial. Building trust was eventually recognized as essential to epidemic response and prioritized, and trust was seen to improve toward the end of the epidemic as incidence fell. However, little is understood about how and why trust changed during Ebola, what factors were most influential to community trust, and how different institutions might have been perceived under different levels of exposure to the outbreak. In this large-N household survey conducted in Liberia in 2018, we measured self-reported trust over time retrospectively in three different communities with different exposures to Ebola. We found trust was consistently higher for non-governmental organizations than for the government of Liberia across all time periods. Trust reportedly decreased significantly from the start to the peak of the epidemic in the study site of highest Ebola incidence. This finding, in combination with a negative association found between knowing someone infected and trust of both iNGOs and the government, indicates the experience of Ebola may have itself caused a decline of trust in the community. These results suggest that national governments should aim to establish trust when engaging communities to change behavior during epidemics. Further research on the relationship between trust and epidemics may serve to improve epidemic response efficacy and behavior uptake.</p>
Multiple Treatments for Ebola Virus Disease (EVD)
ClinicalTrials.gov study NCT02380625. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Phase I Trial to Assess the Safety, Tolerability and Immunogenicity of a Ebola Virus Vaccine
ClinicalTrials.gov study NCT02374385. IPD Sharing: Not stated. Countries: 0. Publications: 2.
African-Canadian Study of HIV-Infected Adults and a Vaccine for Ebola - ACHIV-Ebola
ClinicalTrials.gov study NCT03031912. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Scalable, semi-automated fluorescence reduction neutralization assay for qualitative assessment of Ebola virus-neutralizing antibodies in human clinical samples
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Community trust of government and non-governmental organizations during the 2014-16 Ebola epidemic in Liberia - survey responses
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A conserved transcriptional response to intranasal Ebola virus exposure in nonhuman primates before onset of fever
GEO Series GSE103825. Macaca fascicularis. 67 samples. Type: Expression profiling by high throughput sequencing.
Different Temporal Effects of Ebola Virus VP35 and VP24 Proteins on Global Gene Expression in Human Dendritic Cells
GEO Series GSE96590. Homo sapiens. 20 samples. Type: Expression profiling by high throughput sequencing.
Human liver Huh cell transcriptome (mRNA) response to a Wild-type ΔVP30 Ebola virus, Δmucin, and ssGP mutants
GEO Series GSE80058. Homo sapiens. 119 samples. Type: Expression profiling by array.
Human liver Huh cell transcriptome (miRNA) response to a Wild-type ΔVP30 Ebola virus, Δmucin, and ssGP mutants
GEO Series GSE80059. Homo sapiens. 78 samples. Type: Non-coding RNA profiling by array.
ScienceDex guides
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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.