Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China.
Department of Forensic Pathology, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
Anal Bioanal Chem. 2018 Nov;410(29):7611-7620. doi: 10.1007/s00216-018-1367-1. Epub 2018 Oct 23.
Evaluation of postmortem interval (PMI) is of paramount importance to guide criminal investigations, especially when witnesses are not found. However, accurate PMI estimation is a challenging task in the forensic community due to the limitations of existing methods. The study aims to investigate the potential of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy for predicting PMI based on vitreous humor (VH). VH samples were collected from 72 rabbits in the range of 0-48 h postmortem at a 6-h interval. Their FTIR spectra were normalized by the extended multiplicative signal correction (RMSC) and divided into calibration and validation sets. After analysis of the absorption bands, the Bayesian ridge regression (BRR), support vector regression (SVR), and artificial neural network (ANN) methods were established by the calibration set using a 10-fold cross-validation that was further used to predict the PMI in the validation set. The validity of the models was assessed by a permutation test. The current study demonstrated that multiple macromolecules in the VH samples were reflected in a FTIR spectrum, and the spectral absorption bands at 1313 and 925 cm were highly correlated with PMI. The three models allowed generalization to the validation set due to similar R and errors between the calibration and validation tests. The highest accuracy with R = 0.983 and error = 2.018 h was achieved by the ANN model in the validation test. The results suggest that ATR-FTIR spectroscopy may be useful for VH analysis in order to predict PMI in the future. Graphical abstract ᅟ.
死后间隔时间（PMI）的评估对指导刑事调查至关重要，尤其是当找不到证人时。然而，由于现有方法的局限性，准确估计 PMI 是法医学领域的一项具有挑战性的任务。本研究旨在探讨衰减全反射傅里叶变换红外（ATR-FTIR）光谱法在基于玻璃体（VH）预测 PMI 方面的潜力。从 72 只死后 0-48 小时的兔子中每隔 6 小时收集 VH 样本。通过扩展乘性信号校正（RMSC）对其 FTIR 光谱进行归一化，并将其分为校准集和验证集。在分析吸收带后，使用 10 倍交叉验证通过校准集建立贝叶斯脊回归（BRR）、支持向量回归（SVR）和人工神经网络（ANN）方法，进一步用于预测验证集中的 PMI。通过置换检验评估模型的有效性。本研究表明，VH 样本中的多种大分子在 FTIR 光谱中得到反映，光谱在 1313 和 925cm 处的吸收带与 PMI 高度相关。由于校准和验证测试之间的 R 和误差相似，这三个模型允许推广到验证集。在验证测试中，ANN 模型的准确率最高，R=0.983，误差=2.018 小时。结果表明，ATR-FTIR 光谱法可能有助于 VH 分析，以便在未来预测 PMI。
