Nv Arathy, Thomas Mebin Wilson, Fathima Hana, Dinesh Drisya, Rawat Suchita
Forensic Science Department, Kristu Jayanti College (autonomous), Bangalore, India.
Forensic Science Department, JAIN (Deemed to be University), Bangalore, Karnataka, India.
Forensic Sci Int. 2025 Feb;367:112356. doi: 10.1016/j.forsciint.2024.112356. Epub 2025 Jan 1.
In forensic investigations, human keratinized tissues like skin and nails are commonly encountered as trace evidence, yet the use of vibrational spectroscopy for their identification and differentiation has been underexplored. This research utilized ATR-FTIR to distinguish between human nails and skin samples collected from a group of 50 participants, employing advanced chemometric analysis techniques. The spectral signatures of human keratinized tissues, such as nails and skin, exhibit similarities consistent with previous studies. Chemometric analysis aimed at distinguishing these tissues showed that the PLS-DA model achieved an overall accuracy of 67 % with an AUC score of 0.65, while the SVM model had an overall accuracy of 56 % with an AUC score of 0.71. For sex identification, the PLS-DA model demonstrated an overall accuracy of 83 % with an AUC value of 1, whereas the SVM model achieved an overall accuracy of 100 % with an AUC score of 1. The study underscores the potential of ATR-FTIR coupled with chemometrics in the precise identification and differentiation of human keratinized tissue, thereby enhancing the capabilities of forensic investigations.
在法医调查中,皮肤和指甲等人角化组织常作为微量证据出现,但振动光谱技术在其识别和区分方面的应用尚未得到充分探索。本研究利用衰减全反射傅里叶变换红外光谱(ATR-FTIR),结合先进的化学计量学分析技术,对从50名参与者中采集的人类指甲和皮肤样本进行区分。人类角化组织(如指甲和皮肤)的光谱特征与先前研究一致,呈现出相似性。旨在区分这些组织的化学计量学分析表明,偏最小二乘判别分析(PLS-DA)模型的总体准确率为67%,曲线下面积(AUC)得分为0.65,而支持向量机(SVM)模型的总体准确率为56%,AUC得分为0.71。在性别识别方面,PLS-DA模型的总体准确率为83%,AUC值为1,而SVM模型的总体准确率为100%,AUC得分为1。该研究强调了ATR-FTIR与化学计量学相结合在精确识别和区分人类角化组织方面的潜力,从而增强了法医调查的能力。