Evidence map›Paper›PMID 41897409›Full record

ArticleBiomolecules2026

Endogenous and Exogenous Small RNA Signatures as Novel Tools for Postmortem Interval Determination.

Yafei Wang, Botao Li, Yue Wang, Qinmin Chen, Zhonghua Wang, Guangping Fu, Shujin Li, Chenyu Zhang, Zhen Zhou, Bin Cong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomolecules, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Yafei WangHebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
Botao LiNanjing Drum Tower Hospital Center of Molecular Diagnostic and Therapy, State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, NJU Advanced Institute of Life Sciences (NAILS), School of Life Sciences, Nanjing University, Nanjing 210023, China.
Yue WangHebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
Qinmin ChenHebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
Zhonghua WangHebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
Guangping FuHebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
Shujin LiHebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.
Chenyu ZhangNanjing Drum Tower Hospital Center of Molecular Diagnostic and Therapy, State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, NJU Advanced Institute of Life Sciences (NAILS), School of Life Sciences, Nanjing University, Nanjing 210023, China.
Zhen ZhouNanjing Drum Tower Hospital Center of Molecular Diagnostic and Therapy, State Key Laboratory of Pharmaceutical Biotechnology, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, NJU Advanced Institute of Life Sciences (NAILS), School of Life Sciences, Nanjing University, Nanjing 210023, China.
Bin CongHebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China.

Funding

Fundamental Research Funds for the Central Universities 020814380152Fundamental Research Funds for the Central Universities 020814380190National Natural Science Foundation of China 32341007National Natural Science Foundation of China 82293651
6 · The paper itself

Abstract

backgroundAccurate estimation of the postmortem interval (PMI), the time elapsed between death and body discovery, is a critical challenge in forensic science due to the complex interplay of factors affecting decomposition. Traditional methods based on macroscopic changes often lack precision, especially in later postmortem stages.

methodsThis study aimed to develop a novel PMI estimation framework by integrating the dynamics of endogenous small non-coding RNAs (sncRNAs) and exogenous bacterial-derived small RNAs (sRNAs) using sRNA transcriptomics and machine learning.

resultsCardiac RNA degradation strongly correlated with PMI, with a random forest (RF) model achieving high accuracy (coefficient of determination (R

conclusionThese findings highlight the potential of integrated endogenous and exogenous sRNA analysis in PMI estimation, providing a high-precision, rapid diagnostic tool and revealing complex postmortem molecular processes.

Indexed as

Postmortem ChangesRNA, Small UntranslatedAnimalsBiomarkersGene Expression ProfilingMachine LearningMiceMicroRNAsMyocardiumPiwi-Interacting RNARNA, BacterialRNA StabilityTranscriptomeBiomarkersMicroRNAsPiwi-Interacting RNARNA, BacterialRNA, Small Untranslatedbiomarkersexogenous bacterial-derived small RNAs (sRNAs)machine learningPANDORA-seqPMI estimationRNA degradationsmall non-coding RNAs (sncRNAs)

Identifiers

PMID41897409
PMCPMC13023955

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