家猪死后脑组织GC-MS检测和死亡时间推断的研究

GC-MS detection in the corpse brain tissue of swine for postmortem interval estimation

目的利用GC-MS检测死后家猪脑组织的代谢产物,推断死亡时间。方法成年家猪大脑,置于25℃、75%RH的人工气候箱中,于0 h-84 h内,每间隔6 h取材,GC-MS检测各时间点脑组织代谢物变化。结果PCA显示:平台期和窗口期的时间组彼此分开。建立PLS模型,通过VIP> 1且Kruskal-Wallis检验(P <0.05)筛选出18种重要的代谢物,线性回归模型和参数检验均有统计学意义。多元回归方程为:Y_(PMI)=6.610+16.29X_(十八烷酸)+14.56X_(5-氨基缬草酸)+5.517X_(丙氨酸)(R^2=0.909、SE=6.323)或Y_(PMI)=15.78+9.690 X_(5-氨基缬草酸)+86.45X_(亮氨酸)-82.35X_(甘氨酸)(R^2=0.952、SE=4.271)。结论 GC-MS检测出家猪死后脑组织的多种产物与PMI存在显著相关性,证实了其理论和技术推断PMI的可行性。综合多指标多元逐步回归分析和PLS-DA等多元模式分析方法建立PMI推断模型,可提高推断模型的准确性和精确度。

Objective To apply GC-MS to detect metabolites in brain of swines and to study the estimation of postmortem interval(PMI).Methods The adult swine brains were placed in a 25℃and 75%humidity artificial climate box,the brains were then collected every 6 h of the interval from 0 to 84 h and analyzed with GC-MS.Results PCA model showed that the groups of the platform periods and window periods are separated from each other.The PLS model was established,and 18 important metabolites were screened through Kruskal-Wallis test with VIP>1 and P<0.05.,and the linear regression model and parameter test were statistically significant.The multiple regression equation is YPMI=6.610+16.29 XSa+14.56 X5-Aminovaleric acid+5.517 XAla(R2=0.909、SE=6.323)or YPMI=15.78+9.690 X5-Aminovaleric acid+86.45 XLeu-82.35 XGly(R2=0.952、SE=4.271).Conclusion There is a significant correlation between products detected by GC-MS and PMI,confirming the feasibility of the GC-MS theory and technology in inferring the PMI.Integrated multi-indicator multiple stepwise regression analysis and multi-modal analysis methods such as PLS-DA to establish a PMI inference model,could improve the accuracy and veracity of the PMI inference.