OBJECTIVE: To set up some objective and accurate criteria to evaluate wound healing. METHODS: Documents about wound healing were reviewed and summarized in detail. RESULTS: Wound healing rate, wound healing time, histopathology analysis, quantity assay of macrophage, determination of hydroxyproline, proliferation of cell, assay of DNA contents and circle of cells, level of transforming growth factor-alpha, levels of interleukin-1, interleukin-6 and tumor necrosis factor, assay of keratinocyte collagenase-1, level of fibroblast growth factor receptor-1, level of monocyte chemoattractant protein-1 and level of keratinocyte plasminogen activator inhabitor type 2 were selected as the evaluation criteria of wound healing. CONCLUSION: Wound healing rate, wound healing time and histopathology analysis are direct and efficient criteria of wound healing.
ObjectiveTo screen differential expression of genes in hepatocellular carcinoma (HCC) by bioinformatics method, and analyze its clinical significance and its possible molecular mechanism in HCC.MethodsThe HCC gene expression profile GSE101728 was picked out to analyze the differential expression genes. The hub genes were identified by STRING and Cytoscape. GO and KEGG analysis were carried out by using DAVID and PPI network were constructed by STRING. The relationship among the hub genes were analyzed by using GEPIA.ResultsA total of 1 082 DEGs were captured (354 up-regulated genes and 728 down-regulated genes). Meantime, 10 hub genes ［cyclin dependent kinase 1 (CDK1), cyclin B1 (CCNB1), cyclin A2 (CCNA2), polo-like kinase 1 (PLK1), laser kinase B (AURKB), cyclin of cell division 20 (CDC20), centromere protein A (CENPA), mitotic arrest defective protein 2 (MAD2L1), cyclin B2 (CCNB2), and kinesin family 2C (KIF2C)］ were identified, and its expression and clinical significance were verified by GEPIA. GO and KEGG analysis showed 10 hub genes were mainly enriched in cell division and cell cycle. Expressions of AURKB, CCNB1, and MAD2L1 were obviously positively correlated (P<0.05).ConclusionThis study analyzes the hub genes in the development of HCC by bioinformatics methods and provides valuable information for further research on the mechanism of HCC.