Abstract
Many attempts have been made to estimate the post-mortem interval (PMI) using bioanalytical methods based on multiple biological samples. Cartilage tissues could be used as an alternative for this purpose because their rate of degradation is slower than that of other soft tissue or biofluid samples. In this study, we applied Fourier transform infrared (FTIR) spectroscopy to acquire bioinformation from human annular cartilages within 30 days post-mortem. Principal component analysis (PCA) showed that sex and causes of death have almost no impact on the overall spectral variations caused by post-mortem changes. With pre-processing approaches, several predicted models were established using a conventional machine learning method, known as the partial least square (PLS) regression. The best model achieved a satisfactory prediction with a low error of 1.49 days using the second derivative transform of 3-point smoothing and extended multiplicative scatter correction (EMSC), and the spectral regions from proteins and carbohydrates contributed greatly to the PMI prediction. This study demonstrates the feasibility of cartilage-based FTIR analysis for PMI estimation. Further work will introduce advanced algorithms for more accurate and precise PMI prediction.
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Funding
This study is supported by grants from the National Natural Science Foundation of China (81801873, 81730056, 81722027, 81601645 and 81671869), the National Key R&D Program of China (2016YFC0800702), and the Science and Technolo gy Committee of Shanghai Municipality (17DZ2273200 and 19DZ2292700).
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This study was conducted with the approval of the ethics committee of the Institute of Forensic Sciences, Ministry of Justice, P.R. China.
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Li, Z., Huang, J., Wang, Z. et al. An investigation on annular cartilage samples for post-mortem interval estimation using Fourier transform infrared spectroscopy. Forensic Sci Med Pathol 15, 521–527 (2019). https://doi.org/10.1007/s12024-019-00146-x
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DOI: https://doi.org/10.1007/s12024-019-00146-x