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大鼠心肌组织中microRNA和18S rRNA的降解与死亡时间的相关性 被引量:18

Estimation of Postmortem Interval Using microRNA and 18S rRNA Degradation in Rat Cardiac Muscle
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摘要 目的探讨大鼠死后心肌组织中microRNA和18S rRNA的含量变化与死亡时间的关系。方法将SD大鼠断颈处死后置于25℃室温、50%湿度的环境中,于死后不同时间提取心肌组织中总RNA。利用实时荧光定量PCR检测大鼠心肌组织中miR-1-2和18S rRNA的含量变化,结果用循环阈值(Ct值)表示,分析死亡时间与Ct值的关系,最终建立死亡时间推断的回归分析方程。结果大鼠死后120h内心肌组织中miR-1-2含量无明显变化,此后开始下降;而18S rRNA含量在96 h内逐渐增多,随后开始缓慢下降。大鼠死后不同时间18S rRNA的Ct值以及18S rRNA和miR-1-2的ΔCt值与PMI呈非线性相关,二次曲线拟合的R2值分别为0.9487、0.8072。结论 18S rRNA的Ct值和18S rRNA与miR-1-2的ΔCt值与PMI之间存在明显非线性关系,可以作为早期死亡时间推断的指标。 Objective To explore the relationship between the time-dependent level changes of microRNA and 18S rRNA and the different postmortem interval(PMI) in rat cardiac muscle.Methods SD rats were sacrificed by cervical dislocation and placed at ambient temperature 25 ℃ with a humidity of 50%.Total RNA was extracted from the rat cardiac muscle at different time points after death.The levels of miR-1-2 and 18S rRNA were examined using real-time PCR in rat cardiac muscle.The results were expressed by cycle threshold(Ct) value to explore relationship between PMI and Ct value,and the regression functions were established to estimate PMI.Results The miR-1-2 level in rat myocardial tissue showed no significant changes within 120 h after death,and then began to decline.The 18S rRNA level increased gradually within 96 h after death,and then declined slowly.The nonlinear relationships were established between Ct value(18S rRNA),ΔCt value(difference between 18S rRNA and miR-1-2) and PMI.The R2 of conics fitting were 0.948 7 and 0.807 2,respectively.Conclusion Ct value of 18S rRNA and ΔCt value present a good correlation with PMI,and can be markers for estimating early PMI.
出处 《法医学杂志》 CAS CSCD 2010年第6期413-417,共5页 Journal of Forensic Medicine
关键词 法医病理学 微RNAS RNA 核糖体 18S 死亡时间 聚合酶链反应 大鼠 forensic pathology microRNAs RNA ribosomal 18S postmortem interval polymerase chain reaction rats
作者简介 李文灿(1984-),男,河南新郑人,硕士研究生,主要从事法医学研究:E—mail:082101058@fudan.edu.cn 通信作者:陈龙,男,副教授,主任法医师,主要从事法医病理学及法医临床学研究:E-mail:chenlong@shmu.edu.cn
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