Forensic identification of urine on cotton and polyester fabric with a hand-held Raman spectrometer
Forensic identification of urine on cotton and polyester fabric with a hand-held Raman spectrometer
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DOI：
10.1016/j.forc.2018.05.001
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发表时间：
2018-06-01
影响因子：
2.7
通讯作者：
Kurouski, Dmitry
中科院分区：
文献类型：
--
作者：
Hager, Elizabeth;Farber, Charles;Kurouski, Dmitry
犯罪现场和监狱体液样本的现场检测和识别对于执法至关重要。目前的法医体液检测具有高度特异性，会破坏潜在的 DNA 证据，而且非常耗时。拉曼光谱 (RS) 是一种无标记、非侵入性和非破坏性分析技术，可提供有关分子振动以及分析样品化学结构的信息。这些优点使得 RS 对法医应用极具吸引力。这项研究展示了如何使用 RS 对织物上的尿液进行验证性、非侵入性和非破坏性的直接检测和识别。这一点非常重要，因为曾有惩教人员遭受囚犯尿液的案例。人们可以想象，除了目击者证词之外的确凿证据将有助于对此类案件进行潜在的起诉，特别是如果可以同时检测尿液和 DNA 的话。在这项研究中，我们表明，使用手持式拉曼光谱仪，我们可以检测和识别棉质和合成纤维以及被汗水污染的衣服上的液体样本中的尿液。我们还证明 RS 能够直接检测和识别警服上的尿液。最后，我们表明，将偏最小二乘判别分析与 RS 相结合，可以对所有研究类型的织物进行高精度的尿液预测。 (C) 2018 Elsevier B.V. 保留所有权利。
On-site detection and identification of body fluid samples at crime scenes and in prisons is critical for law enforcement. Current forensic tests for body fluids are highly specific, destructive to potential DNA evidence and time-consuming. Raman spectroscopy (RS) is a label-free, non-invasive and non-destructive analytical technique that provides information about molecular vibrations and consequently chemical structure of the analyzed specimen. These advantages make RS highly attractive for forensic applications. This study demonstrates how RS can be used for confirmatory, non-invasive and non-destructive detection and identification of urine directly on fabrics. This is very important because there have been cases of correctional officers subjected to urine from prisoners. One would envision that conclusive evidence other than eyewitness testimonies will help in potential prosecution of such cases, especially if both urine and DNA can be simultaneously detected. In this study, we show that using a handheld Raman spectrometer we can detect and identify urine in liquid samples, both on cotton and synthetic fabric, as well as on sweat-contaminated clothes. We also demonstrate that RS is capable of detection and identification of urine directly on police uniform. Finally, we show that coupling of partial least squares discriminant analysis with RS allows for high accuracy prediction of urine on all studied types of fabric. (C) 2018 Elsevier B.V. All rights reserved.