BACKGROUND:Liver regeneration is the key factor influencing the prognosis of living donor liver transplantation. There has not been the research on special miRNA of liver regeneration after living donor liver transplantation. OBJECTIVE:To analyze the variation of miRNAs expression profile after rat reduced-size liver transplantation at certain time point, select and verify target miRNA which can provide targeting intervention strategies in liver regeneration after rat reduced-size liver transplantation and provide theoretical evidence for liver regeneration after living donor liver transplantation.METHODS:The reduced-size liver transplantation models were established. miRNAs microarray was used to detect miRNA expression. In differentialy expressed microRNAs, real-time quantitative PCR was utilized to detect target miRNAs. The credibility of miRNAs microarray results was verified. RESULTS AND CONCLUSION:Compared with rat liver tissue in the sham operation group, 11 miRNAs up-regulated in reduced-size liver transplantation, including let-7b-5p, let-7c-5p, miR-101a-3p, miR-103-3p, miR-130a-3p, miR-142-5p, miR-186-5p, miR-199a-3p, miR-21-5p, 221-3p and miR-34a-5p. Four miRNAs were down-regulated, including miR-26b-5p, miR-150-5p, miR-19a-3p and rno-miR-146-5p. PCR test further verified that miR-221-3p and miR-199a-3p expression changes approximated the chip results at 24, 48 hours and 1 week, indicating that results of miRNA microarray were believable. These results verified that it exists variation of miRNAs expression profile after rat reduced-size liver transplantation, which picked out and verified the target miRNAs.

Objective To develop a subgroup analysis method that can simultaneously deal with longitudinal data containing measurement errors and dropouts.Methods Subgroup analysis was carried out based on a threshold regression model.A new generalized unbiased estimation equation is constructed by using the independence between repeated measurements to deal with measurement errors and introducing an inverse probability weighting matrix to deal with missing response.Results The computer stochastic simulation shows that the proposed estimation method is effective in dealing with measurement errors and dropouts,and has smaller bias and mean square error than the generalized estimation equation method without correcting measurement errors or dropouts.Conclusion In subgroup analysis,when there are measurement errors in covariables and missing values in response variables,it is usually necessary to deal with the measurement errors and missing values in order to obtain reliable parameter estimation.