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肺部微生物群特征有望成为溺水诊断及死后浸泡时间估计的生物指标。

Microbiota signature of the lung as the promising bioindicator for drowning diagnosis and postmortem submersion interval estimation.

作者信息

Zeng Kuo, Zhang Fu-Yuan, Wu Ming-Zhe, Yuan Hao-Miao, Du Shu-Kui, Ying Jin-Cheng, Zhang Yan, Wang Lin-Lin, Zhao Rui, Guan Da-Wei

机构信息

Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China.

Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Beijing, China.

出版信息

Int J Legal Med. 2025 Jul;139(4):1863-1877. doi: 10.1007/s00414-025-03458-6. Epub 2025 Mar 11.

Abstract

Drowning diagnosis and postmortem submersion interval (PMSI) estimation are still major challenges in forensic practice. Our recent studies provided evidence that microbiota successions in multiple organs, including intestine, liver, and brain, were valuable indicators for PMSI estimation. Meanwhile, microbiota in the lung from corpses submerged for 3 days presented obvious difference between drowning and postmortem submersion. However, gaps exist in our understanding of how long this difference lasts and how the decomposer microbial community in the lung changes with progression of decomposition. Here, we characterized the postmortem microbiota in the lung of mice submerged for 0 to 14 days, which were drowned or sacrificed by CO asphyxia. Our study revealed that most samples collected before 3 days postmortem were not qualified enough for sequencing. The microbiota in the lung was largely influenced by the microbes colonized in the aquatic environment. Differences in microbiota between drowning and postmortem submersion faded over decomposition and could be used for drowning diagnosis within 10 days postmortem. Meanwhile, 22 taxa with good discriminative ability were identified to establish the classification model for discriminating drowning and postmortem submersion (AUC = 0.92, accuracy = 81.25%) by random forest algorithm. Twenty other candidates exhibiting obviously temporal changes were selected for PMSI estimation, which yield satisfactory performance (mean absolute errors ± the standard error = 0.976 ± 0.189 d). Altogether, we provide further evidence that microbiota signature of the lung is a promising bioindicator for the forensic death investigations of decomposed bodies recovered from water.

摘要

溺水诊断和死后浸泡时间(PMSI)估计仍是法医实践中的重大挑战。我们最近的研究表明,包括肠道、肝脏和大脑在内的多个器官中的微生物群落演替是估计PMSI的重要指标。同时,浸泡3天尸体的肺部微生物群在溺水和死后浸泡之间存在明显差异。然而,我们对于这种差异持续的时间以及肺部分解微生物群落如何随分解进程变化的理解仍存在空白。在此,我们对溺水或一氧化碳窒息处死并浸泡0至14天的小鼠肺部的死后微生物群进行了特征分析。我们的研究表明,死后3天内采集的大多数样本测序质量不足。肺部微生物群在很大程度上受水生环境中定殖微生物的影响。溺水和死后浸泡之间的微生物群差异在分解过程中逐渐消失,可用于死后10天内的溺水诊断。同时,通过随机森林算法鉴定出22个具有良好判别能力的分类单元,以建立区分溺水和死后浸泡的分类模型(AUC = 0.92,准确率 = 81.25%)。另外选择了20个表现出明显时间变化的候选分类单元用于PMSI估计,其表现令人满意(平均绝对误差±标准误差 = 0.976 ± 0.189天)。总之,我们进一步证明肺部微生物群特征是从水中打捞的腐败尸体法医死亡调查中有前景的生物指标。

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