Abstract：
In forensic practice, determining the postmortem submersion interval (PMSI) and cause-of-death of cadavers in aquatic ecosystems has always been challenging task. Traditional approaches are not yet able to address these issues effectively and adequately. Our previous study proposed novel models to predict the PMSI and cause-of-death based on metabolites of blood from rats immersed in freshwater. However, with the advance of putrefaction, it is hardly to obtain blood samples beyond 3 days postmortem. To further assess the feasibility of PMSI estimation and drowning diagnosis in the later postmortem phase, gastrocnemius, the more degradation-resistant tissue, was collected from drowned rats and postmortem submersion model in freshwater immediately after death, and at 1 day, 3 days, 5 days, 7 days, and 10 days postmortem respectively. Then the samples were analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the dynamic changes of the metabolites. A total of 924 metabolites were identified. Similar chronological changes of gastrocnemius metabolites were observed in the drowning and postmortem submersion groups. The difference in metabolic profiles between drowning and postmortem submersion groups was only evident in the initial 1 day postmortem, which was faded as the PMSI extension. Nineteen metabolites representing temporally-dynamic patterns were selected as biomarkers for PMSI estimation. A regression model was built based on these biomarkers with random forest algorithm, which yielded a mean absolute error (± SE) of 5.856 (± 1.296) h on validation samples from an independent experiment. These findings added to our knowledge of chronological changes in muscle metabolites from submerged vertebrate remains during decomposition, which provided a new perspective for PMSI estimation.
摘要：
在法医实践中，确定尸体在水生生态系统中的死后淹没间隔（PMSI）和死亡原因一直是具有挑战性的任务。传统方法还不能有效和充分地解决这些问题。我们先前的研究提出了新的模型来预测PMSI和死亡原因，该模型基于浸入淡水中的大鼠血液的代谢产物。然而,随着腐败的推进，死后三天后几乎无法获得血液样本。为了进一步评估死后后期PMSI估计和溺水诊断的可行性，腓肠肌,抗降解的组织越多，从溺水大鼠和死后立即浸入淡水模型中收集，在1天，3天,5天,7天,和死后10天。然后用液相色谱-串联质谱(LC-MS/MS)分析样品中代谢物的动态变化。总共鉴定了924种代谢物。在溺水和死后浸没组中观察到腓肠肌代谢物的类似时间变化。溺水和死后浸没组之间的代谢谱差异仅在死后的最初1天才明显。作为PMSI扩展而褪色。选择代表时间动态模式的19种代谢物作为用于PMSI估计的生物标志物。基于这些生物标志物,采用随机森林算法建立回归模型,在独立实验的验证样本上，其平均绝对误差（±SE）为5.856（±1.296）h。这些发现增加了我们对分解过程中淹没的脊椎动物残骸肌肉代谢物的时间变化的认识，这为PMSI估算提供了新的视角。
