Department of Chemistry and Chemical Biology, Indiana University Purdue University Indianapolis, 402 North Blackford St., LD326, Indianapolis, IN, 46202, USA.
Forensic and Investigative Sciences Program, Indiana University Purdue University Indianapolis, 402 North Blackford St., LD326, Indianapolis, IN, 46202, USA.
Anal Bioanal Chem. 2020 Feb;412(5):1123-1128. doi: 10.1007/s00216-019-02337-5. Epub 2020 Jan 3.
Since its introduction, gas chromatography (GC) coupled to vacuum ultraviolet spectrophotometry (VUV) has been shown to complement mass spectrometry (MS) for materials such as petrochemicals, explosives, pesticides, and drugs. In forensic chemistry, opioids are commonly encountered but rarely are the samples pure. This work focuses on GC-VUV analysis applied to naturally occurring (e.g., morphine), semi-synthetic (e.g., heroin), and synthetic (fentanyl) opioids as well as common adulterants and diluents (e.g., lidocaine and quinine). The specificity of the VUV spectra were examined visually as well as via descriptive statistical methods (e.g., correlation coefficients and sums of square residuals). Multivariate pattern recognition techniques (principal component analysis and discriminant analysis (DA)) were used to prove the opioid spectra can be reliably differentiated. The accuracy of the DA model was 100% for a test set of VUV spectra. Finally, three "street" heroin samples were analyzed to show "real-world" performance for forensic analyses. These samples contained adulterants such as caffeine, as well as by-products of heroin manufacture.
自问世以来，气相色谱（GC）与真空紫外分光光度法（VUV）的联用已被证明可与质谱（MS）相辅相成，适用于石化产品、爆炸物、农药和药物等材料。在法化学中，阿片类药物很常见，但样品很少是纯净的。本工作重点研究了 GC-VUV 分析技术在天然存在的（如吗啡）、半合成的（如海洛因）和合成的（如芬太尼）阿片类药物以及常见的掺杂物和稀释剂（如利多卡因和奎宁）中的应用。通过视觉和描述性统计方法（如相关系数和平方残差之和）检查了 VUV 光谱的特异性。采用多元模式识别技术（主成分分析和判别分析（DA））证明了阿片类药物光谱可以可靠地区分。DA 模型对一组 VUV 光谱测试集的准确率达到 100%。最后，分析了三个“街头”海洛因样品，以展示法化学分析的“实际”性能。这些样品中含有咖啡因等掺杂物，以及海洛因制造的副产品。
