First Department of Forensic Science, National Research Institute of Police Science , 6-3-1, Kashiwanoha, Kashiwa, Chiba 277-0882, Japan.
Department of Chemistry, Graduate School of Science, The University of Tokyo , 7-3-1, Hongo, Bunkyo, Tokyo 113-0033, Japan.
Anal Chem. 2017 Sep 19;89(18):9797-9804. doi: 10.1021/acs.analchem.7b01756. Epub 2017 Aug 28.
Often in criminal investigations, discrimination of types of body fluid evidence is crucially important to ascertain how a crime was committed. Compared to current methods using biochemical techniques, vibrational spectroscopic approaches can provide versatile applicability to identify various body fluid types without sample invasion. However, their applicability is limited to pure body fluid samples because important signals from body fluids incorporated in a substrate are affected strongly by interference from substrate signals. Herein, we describe a novel approach to recover body fluid signals that are embedded in strong substrate interferences using attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy and an innovative multivariate spectral processing. This technique supported detection of covert features of body fluid signals, and then identified origins of body fluid stains on substrates. We discriminated between ATR FT-IR spectra of postmortem blood (PB) and those of antemortem blood (AB) by creating a multivariate statistics model. From ATR FT-IR spectra of PB and AB stains on interfering substrates (polyester, cotton, and denim), blood-originated signals were extracted by a weighted linear regression approach we developed originally using principal components of both blood and substrate spectra. The blood-originated signals were finally classified by the discriminant model, demonstrating high discriminant accuracy. The present method can identify body fluid evidence independently of the substrate type, which is expected to promote the application of vibrational spectroscopic techniques in forensic body fluid analysis.
在刑事侦查中，区分体液证据的类型对于确定犯罪是如何发生的至关重要。与当前使用生化技术的方法相比，振动光谱方法可以提供广泛的适用性，无需样本入侵即可识别各种体液类型。然而，它们的适用性仅限于纯体液样本，因为嵌入在基质中的体液的重要信号受到基质信号干扰的强烈影响。在这里，我们描述了一种使用衰减全反射傅里叶变换红外（ATR FT-IR）光谱和创新的多变量光谱处理来恢复嵌入在强基质干扰中的体液信号的新方法。该技术支持检测体液信号的隐藏特征，然后识别基质上体液污渍的来源。我们通过创建多元统计模型来区分死后血液（PB）和生前血液（AB）的 ATR FT-IR 光谱。通过我们最初使用血液和基质光谱的主成分开发的加权线性回归方法，从干扰基质（聚酯、棉和牛仔布）上的 PB 和 AB 污渍的 ATR FT-IR 光谱中提取出血液来源的信号。最后，通过判别模型对血液来源的信号进行分类，表现出很高的判别准确性。本方法可以独立于基质类型识别体液证据，有望促进振动光谱技术在法医体液分析中的应用。
