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Integrating dual-transcriptomic and machine learning to establish a miRNA-mRNA-protein triad system for skin wound age estimation

Figure 1. High-throughput sequencing profiles of miRNAs and mRNAs during skin wound healing. (A and B) PCA scatter plot of (A)miRNA and (B)mRNA sequencing data from normal control and wounded skin at indicated post-injury time points, n = 3; (C and D) Differential expression analysis of miRNAs; (C) Bar chart showing the number of differentially expressed miRNAs in wounded skin compared to normal controls at each post-injury time point, |log2FC| > 1, adjusted P < 0.05. (D) Petal plot illustrating the overlap of differentially expressed miRNAs across different post-injury time points; (E and F) Differential expression analysis of mRNAs; (E) Bar chart showing the number of differentially expressed mRNAs in wounded skin compared to normal controls at each post-injury time point, |log2FC| > 1, adjusted P < 0.05; (F) Petal plot illustrating the overlap of differentially expressed mRNAs across different post-injury time points. PCA: Principal component analysis; FC: fold change.

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