Post-mortem interval estimation in rat liver tissues using attenuated total reflection Fourier transform infrared spectroscopy combined with chemometrics. Issue 5 (3rd September 2019)

• Record Type: Journal Article
• Authors: Wang, Lei; Lin, Hancheng; Luo, Yiwen; Sun, Qiran; Li, Zhengdong; Chen, Yijiu; Huang, Ping; Wang, Zhenyuan; Sun, Junhong; Tuo, Ya
• Is Part Of: Australian journal of forensic sciences. Volume 51:Issue 5(2019)
• Page Start: 527
• Page End: 537
• Publication Date: 2019-09-03
• Subjects: Forensic pathology; -- post-mortem interval; -- Fourier transform infrared spectroscopy; -- chemometrics; Law -- Australia -- Periodicals; Forensic sciences -- Periodicals; Forensic Medicine -- Periodicals; 363.2505
• DOI: 10.1080/00450618.2018.1429016
• Languages: English
• ISSNs: 0045-0618

Abstract

Abstract: Post-mortem interval (PMI) estimation is one of the most challenging tasks in forensic practice. Therefore, for PMI estimation, attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy coupled with chemometrics was utilized to monitor the biochemical changes in rat liver tissues with increasing PMI at 4°C, 20°C and 30°C. First, principal component analysis (PCA) revealed that the spectral points were distributed from right to left with increasing PMI along PC–1, and this trend was more obvious at the higher temperature (20°C and 30°C) groups. Second, a partial least squares (PLS) regression model was successfully constructed with the 30°C group, with a root mean square error of cross-validation (RMSECV) of 6.9 h ( R 2 = 0.92) and a root mean square error of prediction (RMSEP) of 4.6 h ( R 2 = 0.96). Lastly, a partial least squares-discriminant analysis (PLS-DA) classification model was established in the 20°C group and demonstrated a complete separation of the spectra among the three classes (0–24 h, 48–96 h and 120–168 h) with 90% accuracy (not-assigned rate: 11%). In conclusion, these results demonstrated that ATR-FTIR spectroscopy combined with chemometrics could serve as a convenient and reliable tool for studying PMI estimation.