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<p>This study investigates mRNA degradation in human dental pulp to explore its utility for estimating the late postmortem interval (LPMI). Morphological changes in pulp tissue at 0, 7, 14, 21 and 28 days postmortem were observed via HE staining, showing progressive cellular degradation. High-throughput sequencing of samples at 0, 7, and 21 days identified candidate mRNAs. Five mRNA biomarkers were obtained, namely SRSF5, FGFR1, ACADVL, FOS, and LRP1. Their expression levels at 0, 3, 7, 10, 14, 21 and 28 days were quantified using RT–qPCR with 18&#xa0;S rRNA as the reference gene. Results demonstrated a consistent decrease in all five mRNAs over time. Mathematical models correlating mRNA levels with LPMI were established. Multi-index models exhibited superior fitting accuracy and predictive performance compared to single-index models, as validated using samples from 10, 18 and 25 days postmortem intervals, indicating greater practical applicability. This approach provides a new direction for forensic LPMI estimation research and contributes to the development of forensic pathology.</p>

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Experimental study of mRNA from human dental pulp tissue for late postmortem interval estimation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月13日

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  • Muxuan Yin,
  • Haibo Gao,
  • Juncai Chen,
  • Longqi Zou,
  • Xinru Wang,
  • Shuhan Lu,
  • Huan Li,
  • Fan He,
  • Qun Tang,
  • Hua Wu

摘要

This study investigates mRNA degradation in human dental pulp to explore its utility for estimating the late postmortem interval (LPMI). Morphological changes in pulp tissue at 0, 7, 14, 21 and 28 days postmortem were observed via HE staining, showing progressive cellular degradation. High-throughput sequencing of samples at 0, 7, and 21 days identified candidate mRNAs. Five mRNA biomarkers were obtained, namely SRSF5, FGFR1, ACADVL, FOS, and LRP1. Their expression levels at 0, 3, 7, 10, 14, 21 and 28 days were quantified using RT–qPCR with 18 S rRNA as the reference gene. Results demonstrated a consistent decrease in all five mRNAs over time. Mathematical models correlating mRNA levels with LPMI were established. Multi-index models exhibited superior fitting accuracy and predictive performance compared to single-index models, as validated using samples from 10, 18 and 25 days postmortem intervals, indicating greater practical applicability. This approach provides a new direction for forensic LPMI estimation research and contributes to the development of forensic pathology.