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Canon inc ipa library
Ipa Library, supplied by Canon inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
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IL-33 regulated inflammatory <t>signaling</t> <t>pathways</t> in SARS-CoV-2-infection WT B6 and IL-33 −/− mice were infected with SARS-CoV-2 as indicated in <xref ref-type=Figure 1 ( n = 3–5 mice/group). B6 mice in the mock group were i.n. treated with the same volume of cell culture medium. Lungs were perfused with cold PBS and harvested for RNA extraction and RNA-seq analysis. (A) Volcano plot describing the fold changes and false discovery rate (FDR)-adjusted p values between infected WT and IL-33 −/− lungs on D2. (B) Pathway enrichment analysis of top ten hallmark pathways in the lungs on D2. (C) Representative heatmaps of differently expressed genes of IFN-γ signaling pathway in the lungs of WT and IL-33 −/− mice on D2. Heatmaps were generated based on KEGG pathway using the Rosalind platform. (D) Network plot showing the genes correlating IL-33 to the COVID-19 disease database identified by ingenuity pathway analysis of the bulk RNA-seq. The orange and green labels indicate upregulation and downregulation, respectively, when compare IL-33 −/− to WT samples. (E) The network of differently expressed genes, pathways and cell functions analyzed by IPA network analyzer. The orange and blue legend on the right indicates the genes predicted to be activation or inhibition, respectively. " width="250" height="auto" />
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IL-33 regulated inflammatory <t>signaling</t> <t>pathways</t> in SARS-CoV-2-infection WT B6 and IL-33 −/− mice were infected with SARS-CoV-2 as indicated in <xref ref-type=Figure 1 ( n = 3–5 mice/group). B6 mice in the mock group were i.n. treated with the same volume of cell culture medium. Lungs were perfused with cold PBS and harvested for RNA extraction and RNA-seq analysis. (A) Volcano plot describing the fold changes and false discovery rate (FDR)-adjusted p values between infected WT and IL-33 −/− lungs on D2. (B) Pathway enrichment analysis of top ten hallmark pathways in the lungs on D2. (C) Representative heatmaps of differently expressed genes of IFN-γ signaling pathway in the lungs of WT and IL-33 −/− mice on D2. Heatmaps were generated based on KEGG pathway using the Rosalind platform. (D) Network plot showing the genes correlating IL-33 to the COVID-19 disease database identified by ingenuity pathway analysis of the bulk RNA-seq. The orange and green labels indicate upregulation and downregulation, respectively, when compare IL-33 −/− to WT samples. (E) The network of differently expressed genes, pathways and cell functions analyzed by IPA network analyzer. The orange and blue legend on the right indicates the genes predicted to be activation or inhibition, respectively. " width="250" height="auto" />
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IL-33 regulated inflammatory signaling pathways in SARS-CoV-2-infection WT B6 and IL-33 −/− mice were infected with SARS-CoV-2 as indicated in <xref ref-type=Figure 1 ( n = 3–5 mice/group). B6 mice in the mock group were i.n. treated with the same volume of cell culture medium. Lungs were perfused with cold PBS and harvested for RNA extraction and RNA-seq analysis. (A) Volcano plot describing the fold changes and false discovery rate (FDR)-adjusted p values between infected WT and IL-33 −/− lungs on D2. (B) Pathway enrichment analysis of top ten hallmark pathways in the lungs on D2. (C) Representative heatmaps of differently expressed genes of IFN-γ signaling pathway in the lungs of WT and IL-33 −/− mice on D2. Heatmaps were generated based on KEGG pathway using the Rosalind platform. (D) Network plot showing the genes correlating IL-33 to the COVID-19 disease database identified by ingenuity pathway analysis of the bulk RNA-seq. The orange and green labels indicate upregulation and downregulation, respectively, when compare IL-33 −/− to WT samples. (E) The network of differently expressed genes, pathways and cell functions analyzed by IPA network analyzer. The orange and blue legend on the right indicates the genes predicted to be activation or inhibition, respectively. " width="100%" height="100%">

Journal: iScience

Article Title: The alarmin IL-33 exacerbates pulmonary inflammation and immune dysfunction in SARS-CoV-2 infection

doi: 10.1016/j.isci.2024.110117

Figure Lengend Snippet: IL-33 regulated inflammatory signaling pathways in SARS-CoV-2-infection WT B6 and IL-33 −/− mice were infected with SARS-CoV-2 as indicated in Figure 1 ( n = 3–5 mice/group). B6 mice in the mock group were i.n. treated with the same volume of cell culture medium. Lungs were perfused with cold PBS and harvested for RNA extraction and RNA-seq analysis. (A) Volcano plot describing the fold changes and false discovery rate (FDR)-adjusted p values between infected WT and IL-33 −/− lungs on D2. (B) Pathway enrichment analysis of top ten hallmark pathways in the lungs on D2. (C) Representative heatmaps of differently expressed genes of IFN-γ signaling pathway in the lungs of WT and IL-33 −/− mice on D2. Heatmaps were generated based on KEGG pathway using the Rosalind platform. (D) Network plot showing the genes correlating IL-33 to the COVID-19 disease database identified by ingenuity pathway analysis of the bulk RNA-seq. The orange and green labels indicate upregulation and downregulation, respectively, when compare IL-33 −/− to WT samples. (E) The network of differently expressed genes, pathways and cell functions analyzed by IPA network analyzer. The orange and blue legend on the right indicates the genes predicted to be activation or inhibition, respectively.

Article Snippet: Canonical pathways analysis identified the most significant pathways from the Qiagen IPA library that were relevant to the dataset.

Techniques: Protein-Protein interactions, Infection, Cell Culture, RNA Extraction, RNA Sequencing, Generated, Activation Assay, Inhibition