Fig. 5.

Proteomic characterization of treated BMSCs compared to untreated BMSCs. a Box plots to visualize the distributions of a dataset. The box plots in the same figure indicated that the distribution of the intensities among all samples was nearly the same. b 3D score plot for all samples. The explained variances were shown in brackets. c Hierarchical clustering was performed with the h.clust function in a statistical package, and the clustering result was shown in the form of a heatmap. d Correlation analysis could be used to visualize the overall correlations between different samples. e Volcano plots were used to demonstrate differential abundance between two groups. The vertical lines corresponded to 1.5-fold up and down and the horizontal line represented a p value of 0.05. The colored dots in the plot represented the differentially abundant proteins with statistical significance. f Heatmap showed 21 differentially abundant proteins among samples (high relative abundance in red, and low relative abundance in green or black). g Gene ontology (GO) analysis of differentially abundant proteins. The vertical axis represented the gene ratio (the ratio of the gene count in GO terms to the total differentially expressed genes count) and the horizontal axis described the enrichment components. BP biological process, CC cellular component, MF molecular function. h KEGG significant enrichment analysis for the differentially abundant proteins. The horizontal axis indicated p value and vertical ordinates were the terms of the pathways. The size of the node indicated the number of genes matched in the pathways. The degree of color represented −log₁₀ (p value): Logarithmic conversion of Fisher’s exact test p value, indicating the significance of pathway correlations