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1.
Chinese Journal of Digestion ; (12): 546-553, 2021.
Article in Chinese | WPRIM | ID: wpr-912210

ABSTRACT

Objective:To investigate the expression, regulation, potential mechanism and clinical significance of microRNA(miRNA)-129-1 in colon cancer.Methods:The changes of expression and methylation of miRNA-129-1 were analyzed from the methylation, mRNA expression and miRNA expression data of colon cancer in the cancer genome atlas (TCGA) database. The target genes of miRNA-129-1 were predicted from miRwalk 2.0 and TargetScan database. DAVID 6.7 online software was used for gene oncology and Kyoto encyclopedia of genes and genomes enrichment analysis. STRING database was used for protein-protein interaction analysis. TCGA data were applied again to analyze the differential expression and prognosis of key target genes of miRNA-129-1. Paired t test and independent sample t test were used for statistical analysis. The receiver operating characteristic curve (ROC) was used to evaluate the diagnostic value of miRNA-129-1 gene methylation in colon cancer. Kaplan-Meier method and log-rank test were used to analyze the effects of miRNA-129-1 expression on survival. Results:The sequence of miRNA-129-1 among different species was conserved. After all colon cancer samples, and control samples of TCGA database were analyzed, the results showed that compared with those of control samples, the expression of miRNA-129-1 decreased in cancer samples (0.98±0.81 vs. 5.74±0.59), and the methylation levels of cg04524088, cg04840800, cg11364290, cg20734982 and cg24044186 locus of miRNA-129-1 significantly decreased (0.321±0.130 vs. 0.563±0.051, 0.432±0.123 vs. 0.624±0.064, 0.475±0.153 vs. 0.768±0.033, 0.659±0.180 vs. 0.816±0.037 and 0.862±0.096 vs. 0.916±0.019, respectively) in colon cancer tissues, and the differences were all statistically significant ( t=14.95, 11.36, 9.39, 11.74, 5.32 and 3.47, all P<0.01). The results of ROC analysis showed that the methylation levels of the above five locus of miRNA-129-1 gene had high diagnostic efficiency in colon cancer (area under curve=0.946, 0.915, 0.950, 0.758 and 0.667, all P<0.01). The results of survival analysis indicated that low expression of miRNA-129-1 was associated with poor prognosis (hazard ratio ( HR)=0.55, P=0.018). The results of bioinformatics analysis demonstrated that the target genes of miRNA-129-1 were enriched in serine / threonine kinase receptor, mitogen-activated protein kinase and other functional gene clusters closely related to tumor, and there was a complex interaction network among the target genes proteins. The high expression of ephrin type-B receptor2 ( EPHB2) gene, a potential key target gene of miRNA-129-1, was associated with the short overall survival and disease-free survival time ( HR=1.9 and 1.6, both P<0.01). Conclusions:The expression and methylation of miRNA-129-1 play an important regulatory role in the development and development of colon cancer. The methylation of miRNA-129-1 has potential value in the diagnosis of colon cancer, and miRNA-129-1 is an influencing factor for the prognosis of patients with colon cancer. EPHB2 may be a potential key target gene of miRNA-129-1.

2.
Journal of Zhejiang University. Science. B ; (12): 504-511, 2021.
Article in English | WPRIM | ID: wpr-880754

ABSTRACT

The prompt detection and proper evaluation of necrotic retinal region are especially important for the diagnosis and treatment of acute retinal necrosis (ARN). The potential application of artificial intelligence (AI) algorithms in these areas of clinical research has not been reported previously. The present study aims to create a computational algorithm for the automated detection and evaluation of retinal necrosis from retinal fundus photographs. A total of 149 wide-angle fundus photographs from 40 eyes of 32 ARN patients were collected, and the U-Net method was used to construct the AI algorithm. Thereby, a novel algorithm based on deep machine learning in detection and evaluation of retinal necrosis was constructed for the first time. This algorithm had an area under the receiver operating curve of 0.92, with 86% sensitivity and 88% specificity in the detection of retinal necrosis. For the purpose of retinal necrosis evaluation, necrotic areas calculated by the AI algorithm were significantly positively correlated with viral load in aqueous humor samples (

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