Figure 1. Characteristic of carotid blood flow. The blood flow near the center of the vessel is laminar, the vessel wall is subjected to laminar shear stress or high shear stress (>15 dyn/cm2), while the lateral part of the vessel is turbulent, and the vessel wall is subjected to oscillatory shear stress or low shear stress (<4 dyn/cm2), which makes the lateral wall form atherosclerotic plaques easily--图1. 颈动脉血流的特征。靠近血管中心的血流是层流,血管壁受到层流剪切应力或高剪切应力(>15 dyn/cm2)的作用。而血管侧部的血流是湍流,血管壁受到振荡剪切应力或低剪切应力(<4 dyn/cm2),这使得侧壁易形成动脉粥样硬化斑块--2. 材料与方法2.1. 剪切应力数据集和预处理
Table 1. Summary of the shear stress datasets involved in our studyTable 1. Summary of the shear stress datasets involved in our study 表1. 研究中涉及的切应力数据集的总结
Figure 2. (A) Principal component analysis (PCA) results and box plot for the combined expression profile before Combat and after Combat. (B) Volcanic map of differential genes (DEGs) distribution, blue nodes represent down-regulated genes, red nodes represent up-regulated genes, gray nodes represent genes with no significant change. (C) Heat map of DEGs, horizontal axis represents each sample, vertical axis represents each gene, blue represents low gene expression. Red represents high gene expression. (D) Box plot shows the difference in the expression of each DEG in laminar shear stress (LS) and oscillatory shear stress (OS). *P < 0.05, **P < 0.01, ***P < 0.001--图2. (A) 主成分分析(PCA)结果和批次效应处理前后合并表达谱的箱线图。(B) 差异基因(DEGs)分布的火山图,蓝色节点代表下调基因,红色节点代表上调基因,灰色节点代表无显著变化的基因。(C) 差异基因的热图,横轴代表每个样本,纵轴代表每个基因,蓝色代表低基因表达,红色代表高基因表达。(D) 箱线图显示层流剪切应力(LS)和振荡剪切应力(OS)下每个DEG表达的差异。*P < 0.05,**P < 0.01,***P < 0.001--3.2. 功能和通路富集分析
Figure 3. Function enrichment analysis. (A) Gene ontology (GO) functional analysis of the differential genes (DEGs) between laminar shear stress (LS) and oscillatory shear stress (OS). (B) Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis of the DEGs between OS and LS--图3. 功能富集分析。(A) 层流剪切应力(LS)和振荡剪切应力(OS)之间差异基因(DEGs)的基因本体(GO)功能分析。(B) OS和LS之间差异基因的京都基因与基因组百科全书(KEGG)通路分析--3.3. PPI网络构建Figure 4. Protein-protein interaction (PPI) networks, according to Cytohubba analysis, color and figure size represent Degree value--图4. 蛋白质–蛋白质相互作用(PPI)网络,根据Cytohubba分析,颜色和图形大小代表度值--
Figure 5. Selection of signature genes regulated by shear stress in the combined GSE20739, GSE16706 and GSE1518 datasets. (A) Five-time cross-verification for tuning parameter selection in the least absolute shrinkage and selection operator (LASSO) model. Each curve corresponds to a single gene. (B) LASSO coefficient profiling. The solid vertical lines represent the partial likelihood deviance standard error (SE). The dotted vertical line is drawn at the optimal lambda. (C) Random forest shows the number of selected genes and accuracy. (D) Support vector machine-recursive feature elimination (SVM-RFE) algorithm for feature selection. (E) Venn diagram showing the characteristic genes shared by LASSO, Random Forest, and SVM-RFE algorithms. (F) The receiver operating characteristic (ROC) curves estimating the diagnostic performance of signature genes--图5. 在合并的GSE20739、GSE16706和GSE1518数据集中筛选剪切应力调控的特征基因。(A) 最小绝对收缩和选择算子(LASSO)模型中调节参数选择的五次交叉验证。每条曲线对应一个基因。(B) LASSO系数分析图。实线垂直线表示部分似然偏差标准误(SE)。虚线垂直线表示最佳lambda。(C) 随机森林显示所选基因的数量和准确性。(D) 支持向量机–递归特征消除(SVM-RFE)算法的特征选择。(E) 维恩图显示LASSO、随机森林和SVM-RFE算法共享的特征基因。(F) 受试者工作特征(ROC)曲线评估特征基因的诊断性能--3.5. 特征基因的功能富集分析
Figure 6. Function enrichment analysis. (A) Gene ontology (GO) functional analysis of the signature genes. (B) Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis of the signature genes--图6. 功能富集分析。(A) 特征基因的基因本体(GO)功能分析。(B) 特征基因的京都基因与基因组百科全书(KEGG)通路分析--3.6. 列线图模型构建Figure 7. (A) Nomogram shows the correlation between the signature genes and the oscillatory shear stress. (B), (C) Receiver operating characteristic (ROC) and calibration curves show that the prediction ability of the nomogram model is accurate--图7. (A) 列线图显示特征基因与振荡剪切应力之间的相关性。(B),(C) 受试者工作特征(ROC)曲线和校准曲线显示列线图模型的预测能力准确--图7. (A) 列线图显示特征基因与振荡剪切应力之间的相关性。(B),(C) 受试者工作特征(ROC)曲线和校准曲线显示列线图模型的预测能力准确Figure 7. (A) Nomogram shows the correlation between the signature genes and the oscillatory shear stress. (B), (C) Receiver operating characteristic (ROC) and calibration curves show that the prediction ability of the nomogram model is accurate--图7. (A) 列线图显示特征基因与振荡剪切应力之间的相关性。(B),(C) 受试者工作特征(ROC)曲线和校准曲线显示列线图模型的预测能力准确--图7. (A) 列线图显示特征基因与振荡剪切应力之间的相关性。(B),(C) 受试者工作特征(ROC)曲线和校准曲线显示列线图模型的预测能力准确
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