UV-Vis and ATR-FTIR spectroscopic investigations of postmortem interval based on the changes in rabbit plasma.
UV-Vis and ATR-FTIR spectroscopic investigations of postmortem interval based on the changes in rabbit plasma.
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基于家兔血浆变化的尸检间隔的紫外-可见光和 ATR-FTIR 光谱研究
DOI：
10.1371/journal.pone.0182161
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Wang Z
中科院分区：
文献类型：
--
作者：
Wang Q;He H;Li B;Lin H;Zhang Y;Zhang J;Wang Z
估计 PMI 在法医调查中非常重要。尽管有许多方法用于估计 PMI，但一些研究重点关注事后重新分布。在这项研究中，紫外可见光 (UV-Vis) 测量与目视检查相结合表明，死后血红蛋白有规律地扩散到血浆中，这表明死后血液中成分的重新分布。此后，使用衰减全反射-傅里叶变换红外（ATR-FTIR）光谱来确认这种现象引起的变化。首先，构建全谱偏最小二乘（PLS）和遗传算法结合PLS（GA-PLS）模型来预测PMI。 GA-PLS模型的性能优于全谱PLS模型，其交叉验证的均方根误差（RMSE）为3.46 h（R2 = 0.95），预测的RMSE为3.46 h（R2 = 0.94）。对血浆和有形成分之间光谱相似性的研究也支持了成分重新分布在死后血浆光谱变化中的作用。这些结果表明，ATR-FTIR 光谱与先进的数学方法相结合可以作为研究死后成分的重新分布和估计 PMI 的便捷可靠的工具。
Estimating PMI is of great importance in forensic investigations. Although many methods are used to estimate the PMI, a few investigations focus on the postmortem redistribution. In this study, ultraviolet–visible (UV–Vis) measurement combined with visual inspection indicated a regular diffusion of hemoglobin into plasma after death showing the redistribution of postmortem components in blood. Thereafter, attenuated total reflection–Fourier transform infrared (ATR–FTIR) spectroscopy was used to confirm the variations caused by this phenomenon. First, full-spectrum partial least-squares (PLS) and genetic algorithm combined with PLS (GA-PLS) models were constructed to predict the PMI. The performance of GA-PLS model was better than that of full-spectrum PLS model based on its root mean square error (RMSE) of cross-validation of 3.46 h (R2 = 0.95) and the RMSE of prediction of 3.46 h (R2 = 0.94). The investigation on the similarity of spectra between blood plasma and formed elements also supported the role of redistribution of components in spectral changes in postmortem plasma. These results demonstrated that ATR-FTIR spectroscopy coupled with the advanced mathematical methods could serve as a convenient and reliable tool to study the redistribution of postmortem components and estimate the PMI.
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影响因子：
2.1
作者：
Hyde, Embriette R.;Haarmann, Daniel P.;Bucheli, Sibyl R.
通讯作者：
Bucheli, Sibyl R.
影响因子：
2.2
作者：
Henssge, C;Madea, B
通讯作者：
Madea, B
影响因子：
2.2
作者：
Henssge, Claus;Madea, Burkhard
通讯作者：
Madea, Burkhard
影响因子：
3.4
作者：
Alves, Ana;Santos, Antonio;Rodrigues, Jose
通讯作者：
Rodrigues, Jose
影响因子：
1
作者：
Donaldson, Andrea Evelyn;Lamont, Iain L.
通讯作者：
Lamont, Iain L.