Fayixue Zazhi (Aug 2022)
Application of Linear Regression Model of Gpnmb Gene in Rat Injury Time Estimation
Abstract
ObjectiveTo investigate the effects of injury time, postmortem interval （PMI） and postmortem storage temperature on mRNA expression of glycoprotein non-metastatic melanoma protein B （Gpnmb）, and to establish a linear regression model between Gpnmb mRNA expression and injury time, to provide aimed at providing potential indexes for injury time estimation.MethodsTest group SD rats were anesthetized and subjected to blunt contusion and randomly divided into 0 h, 4 h, 8 h, 12 h, 16 h, 20 h and 24 h groups after injury, with 18 rats in each group. After cervical dislocation, 6 rats in each group were collected and stored at 0 ℃, 16 ℃ and 26 ℃, respectively. The muscle tissue samples of quadriceps femoris injury were collected at 0 h, 12 h and 24 h postmortem at the same temperature. The grouping method and treatment method of the rats in the validation group were the same as above. The expression of Gpnmb mRNA in rat skeletal muscle was detected by RT-qPCR. The Pearson correlation coefficient was used to evaluate the correlation between Gpnmb mRNA expression and injury time, PMI, and postmortem storage temperature. SPSS 25.0 software was used to construct a linear regression model, and the validation group data was used for the back-substitution test.ResultsThe expression of Gpnmb mRNA continued to increase with the prolongation of injury time, and the expression level was highly correlated with injury time （P0.05）. The linear regression equation between injury time （y） and Gpnmb mRNA relative expression （x） was y=0.611 x+4.489. The back-substitution test proved that the prediction of the model was accurate.ConclusionThe expression of Gpnmb mRNA is almost not affected by the PMI and postmortem storage temperature, but is mainly related to the time of injury. Therefore, a linear regression model can be established to infer the time of injury.
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