8 research outputs found

    Additional file 1: of MutScan: fast detection and visualization of target mutations by scanning FASTQ data

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    A screenshot of false positive caused by bad alignment at chr22. We found some mutations near chr22:42,526,561 appeared in all the eight samples and surmised that they should be false positives. By manually looking into the alignment, we found about seven mismatches near that genome position, and confirmed that those mutations were false positives caused by bad alignment. (PNG 193 kb

    Tuning the First Hyperpolarizabilities of Boron Nitride Nanotubes

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    Various carbon-substituted boron nitride (8,0) and (4,4) nanotubes are designed for application as nonlinear optical materials. The structure and first (static and frequency-dependent) hyperpolarizabilities of these boron nitride nanotubes are predicted. The substitution of carbon in the boron nitride nanotube clip significantly enhances the first hyperpolarizabilities by up to several orders of magnitude. The doping pattern of the carbon circle and π electron conjugation are crucial in determining the large first hyperpolarizabilities of these nanotubes

    DataSheet_1_Prognostic value of receptor tyrosine kinases in malignant melanoma patients: A systematic review and meta-analysis of immunohistochemistry.doc

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    BackgroundSubstantial evidence suggests that receptor tyrosine kinases (RTKs) are overexpressed in tumors; however, few studies have focused on the prognostic value of RTKs in melanoma.ObjectivesThe objective of this study is to evaluate the association between overexpression of RTKs and survival in melanoma patients based on immunohistochemistry (IHC) analysis.MethodsOur review is registered on PROSPERO (http://www.crd.york.ac.uk/PROSPERO), registration number CRD42021261460. Seven databases were searched, and data were extracted. We used IHC to measure the association between overexpression of RTKs and overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and clinicopathology in melanoma patients. Pooled analysis was conducted to assess the differences between Hazard Ratios along with 95% confidence intervals.ResultsOf 5,508 publications examined following the database search, 23 publications were included in this study, which included data from a total of 2,072 patients. Vascular endothelial growth factor receptor 2 (VEGF-R2) overexpression was associated with worse OS and DFS in melanoma. Furthermore, there was an association between OS and the expression of several RTKs, including epidermal growth factor receptor (EGFR), mesenchymal-epithelial transition factor (MET), vascular endothelial growth factor receptor 1 (VEGF-R1), and insulin-like growth factor 1 receptor (IGF-1R). There were no significant correlations between EGFR overexpression and worse DFS or PFS. EGFR overexpression was associated with worse OS cutaneous and nasal melanoma, but not uveal melanoma. However, MET overexpression was related to worse OS in both cutaneous and uveal melanoma. Furthermore, EGFR overexpression was associated with a worse OS in Europe compared to other geographic areas. Moreover, EGFR and MET overexpression showed significant prognostic value in patients with the cut-off “≥10% staining”.ConclusionsOur findings build concrete evidence that overexpression of RTKs is associated with poor prognosis and clinicopathology in melanoma, highlighting RTK expression has the potential to inform individualized combination therapies and accurate prognostic evaluation.</p

    Image_2_Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis.tif

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    BackgroundIgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN.MethodsGSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN.ResultA total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN.ConclusionWe screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN.</p

    Table_1_Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis.docx

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    BackgroundIgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN.MethodsGSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN.ResultA total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN.ConclusionWe screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN.</p

    Image_1_Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis.tif

    No full text
    BackgroundIgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN.MethodsGSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN.ResultA total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN.ConclusionWe screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN.</p

    Image_3_Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis.tif

    No full text
    BackgroundIgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN.MethodsGSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN.ResultA total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN.ConclusionWe screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN.</p

    Mechanisms of dihydromyricetin against hepatocellular carcinoma elucidated by network pharmacology combined with experimental validation

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    Dihydromyricetin (DMY) is extracted from vine tea, a traditional Chinese herbal medicine with anti-cancer, liver protection, and cholesterol-lowering effects. This study investigated the mechanism of DMY against hepatocellular carcinoma (HCC). Potential DMY, HCC, and cholesterol targets were collected from relevant databases. PPI networks were created by STRING. Then, the hub genes of co-targets, screened using CytoHubba. GO and KEGG pathway enrichment, were performed by Metascape. Based on the above results, a series of in vitro experiments were conducted by using 40–160 μM DMY for 24 h, including transwell migration/invasion assay, western blotting, and Bodipy stain assay. Network pharmacology identified 98 common targets and 10 hub genes of DMY, HCC, and cholesterol, and revealed that the anti-HCC effect of DMY may be related to the positive regulation of lipid rafts. Further experiments confirmed that DMY inhibits the proliferation, migration, and invasion of HCC cells and reduces their cholesterol levels in vitro. The IC50 is 894.4, 814.4, 467.8, 1,878.8, 151.8, and 156.9 μM for 97H, Hep3B, Sk-Hep1, SMMC-7721, HepG2, and Huh7 cells, respectively. In addition, DMY downregulates the expression of lipid raft markers (CAV1, FLOT1), as well as EGFR, PI3K, Akt, STAT3, and Erk. The present study reveals that DMY suppresses EGFR and its downstream pathways by reducing cholesterol to disrupt lipid rafts, thereby inhibiting HCC, which provides a promising candidate drug with low toxicity for the treatment of HCC.</p
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