An investigation on annular cartilage samples for post-mortem interval estimation using Fourier transform infrared spectroscopy
An investigation on annular cartilage samples for post-mortem interval estimation using Fourier transform infrared spectroscopy
复制标题
使用傅里叶变换红外光谱法对环形软骨样本进行死后间隔估计的研究
DOI：
10.1007/s12024-019-00146-x
复制
发表时间：
2019-12-01
影响因子：
1.8
通讯作者：
Huang, Ping
中科院分区：
文献类型：
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作者：
Li, Zhouru;Huang, Jiao;Huang, Ping
已经进行了许多尝试，以估计死后间隔（PMI）使用生物分析方法的基础上，多个生物样品。软骨组织可用作此目的的替代品，因为它们的降解速率比其他软组织或生物流体样品的降解速率慢。在这项研究中，我们应用傅里叶变换红外光谱（FTIR），以获取生物信息的人环形软骨在30天内死后。主成分分析（PCA）表明，性别和死因几乎没有影响的总体光谱变化所造成的死后变化。通过预处理方法，使用传统的机器学习方法（称为偏最小二乘（PLS）回归）建立了几个预测模型。最好的模型实现了一个令人满意的预测与低误差为1.49天，使用三点平滑和扩展的乘法散射校正（EMSC）的二阶导数变换，并从蛋白质和碳水化合物的光谱区域的PMI预测贡献很大。本研究证明了基于软骨的FTIR分析用于PMI估计的可行性。进一步的工作将引入先进的算法，以实现更准确和精确的PMI预测。
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.