Risoluti Roberta, Gullifa Giuseppina, Fineschi Vittorio, Frati Paola, Materazzi Stefano
Department of Chemistry, "Sapienza" University of Rome, p.le A.Moro 5, 00185 Rome, Italy.
Department of Anatomical, Histological, Forensic Medicine and Orthopaedic Sciences, "Sapienza" University of Rome, p.le A.Moro 5, 00185 Rome, Italy.
Diagnostics (Basel). 2021 Jan 14;11(1):121. doi: 10.3390/diagnostics11010121.
Chronothanatology has always been a challenge in forensic sciences. Therefore, the importance of a multidisciplinary approach for the characterization of matrices (organs, tissues, or fluids) that respond linearly to the postmortem interval (PMI) is emerging increasingly. The vitreous humor is particularly suitable for studies aimed at assessing time-related modifications because it is topographically isolated and well-protected. In this work, a novel approach based on thermogravimetry and chemometrics was used to estimate the time since death in the vitreous humor and to collect a databank of samples derived from postmortem examinations after medico-legal evaluation. In this study, contaminated and uncontaminated specimens with tissue fragments were included in order to develop a classification model to predict time of death based on partial least squares discriminant analysis (PLS-DA) that was as robust as possible. Results demonstrate the possibility to correctly predict the PMI even in contaminated samples, with an accuracy not lower than 70%. In addition, the correlation coefficient of the measured versus predicted outcomes was found to be 0.9978, confirming the ability of the model to extend its feasibility even to such situations involving contaminated vitreous humor.
时间死亡学一直是法医学中的一项挑战。因此,采用多学科方法来表征对死后间隔时间(PMI)呈线性响应的基质(器官、组织或体液)的重要性日益凸显。玻璃体液特别适合用于旨在评估与时间相关变化的研究,因为它在解剖位置上相对孤立且受到良好保护。在这项工作中,一种基于热重分析法和化学计量学的新方法被用于估计玻璃体液中的死亡时间,并收集了经过法医学评估后的尸体检验样本数据库。在本研究中,包含了带有组织碎片的污染和未污染标本,以便基于偏最小二乘判别分析(PLS - DA)开发一个尽可能稳健的预测死亡时间的分类模型。结果表明,即使在污染样本中也有可能正确预测PMI,准确率不低于70%。此外,测量结果与预测结果的相关系数为0.9978,证实了该模型即使在涉及污染玻璃体液的情况下也能扩展其可行性的能力。