Stride Nielsen Louise, Lindholst Christian, Villesen Palle
Department of Forensic Medicine, Section for Forensic Chemistry, Aarhus University, Palle Juul-Jensens Boulevard 99, 8200 Aarhus N, Denmark; Bioinformatics Research Centre, Aarhus University, C. F. Møllers Allé 8, 8000 Aarhus C, Denmark.
Department of Forensic Medicine, Section for Forensic Chemistry, Aarhus University, Palle Juul-Jensens Boulevard 99, 8200 Aarhus N, Denmark.
Forensic Sci Int. 2016 Dec;269:42-49. doi: 10.1016/j.forsciint.2016.11.007. Epub 2016 Nov 11.
Many different groups of chemical compounds can be used in statistical impurity-profile comparison in order to establish links between different seizures of illicit drugs. For cocaine, some of these compounds descent directly from the coca leaf while others are remnants from the manufacturing process; and each of the compound groups exhibit different degrees of stability and discrimination power. Information obtained from the different groups can be handled in numerous ways and selecting the right method using a balanced combination of the compound groups is highly important in order to provide investigators and courtrooms with accurate conclusions. By using logistic regression or discriminant analysis (linear and quadratic), cocaine alkaloid and residual solvent distances can be combined in order to obtain probabilities for the two possibilities: linked or unlinked. We examined different data transformations and distance methods and ranked the different models using cross validation. Validation in an unrelated data set proved the consistency of the results. Data consisted of five large groups of linked samples exposed to different storage conditions during 12 months, 124 different cocaine sample seizures and 15 smaller groups of linked samples stored at room temperature for up to 15 months. The alkaloid and residual solvent impurity profiles of the samples were analysed using gas chromatography-mass spectrometry (GC-MS) and headspace GC-MS, respectively. Residual solvent profiles exhibited considerable higher discrimination power than cocaine alkaloid profiles. Thus, a residual-solvent-weighted model (log10 transformation and cosine distance) was found superior at distinguishing correctly between linked and unlinked seizures compared to models using alkaloid distance alone. The model only gives weight to the residual solvents when the alkaloid profiles are very similar. This finding demonstrates the possibility to combine information from the highly stable, non-coca leaf-descent residual solvent profiles and the less stable cocaine alkaloid profiles for statistical comparative analysis of cocaine seizures in a simple and easy-to-implement way.
为了建立不同批次非法药物之间的联系，许多不同种类的化合物可用于统计杂质谱比较。对于可卡因来说，其中一些化合物直接来源于古柯叶，而其他一些则是制造过程中的残余物；并且每一组化合物都表现出不同程度的稳定性和鉴别能力。从不同组获得的信息可以通过多种方式处理，为了向调查人员和法庭提供准确的结论，使用化合物组的平衡组合选择正确的方法非常重要。通过使用逻辑回归或判别分析（线性和二次），可以将可卡因生物碱和残留溶剂距离相结合，以获得两种可能性的概率：相关或不相关。我们研究了不同的数据转换和距离方法，并使用交叉验证对不同模型进行了排名。在不相关数据集中的验证证明了结果的一致性。数据包括五组在12个月内暴露于不同储存条件的大量相关样本、124个不同的可卡因样本缉获量以及15组在室温下储存长达15个月的较小相关样本组。分别使用气相色谱 - 质谱联用仪（GC-MS）和顶空气相色谱 - 质谱联用仪分析了样本的生物碱和残留溶剂杂质谱。残留溶剂谱表现出比可卡因生物碱谱更高的鉴别能力。因此，与仅使用生物碱距离的模型相比，发现一种残留溶剂加权模型（log10转换和余弦距离）在正确区分相关和不相关缉获量方面更具优势。当生物碱谱非常相似时，该模型仅对残留溶剂赋予权重。这一发现表明，有可能以简单且易于实施的方式将来自高度稳定的、非古柯叶来源的残留溶剂谱和稳定性较低的可卡因生物碱谱的信息结合起来，用于可卡因缉获量的统计比较分析。
