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非法毒品街头样本及其切割剂。基于 GC-MS 的分析结果为传感器的开发提供了指导方针。

Illicit drugs street samples and their cutting agents. The result of the GC-MS based profiling define the guidelines for sensors development.

机构信息

Laboratorium Badań Toksykologicznych Lab4Tox Sp. Z o.o., Skłodowskiej-Curie 55/61, 50-369, Wroclaw, Poland; Department of Inorganic and Analytical Chemistry, Faculty of Chemistry, University of Lodz, Tamka 12, 91-403, Lodz, Poland.

Laboratorium Badań Toksykologicznych Lab4Tox Sp. Z o.o., Skłodowskiej-Curie 55/61, 50-369, Wroclaw, Poland.

出版信息

Talanta. 2022 Jan 15;237:122904. doi: 10.1016/j.talanta.2021.122904. Epub 2021 Sep 28.

Abstract

In this work, we have focused on the profiling of 5647 street samples covering marijuana, common and new recreational illicit drugs. All samples were analyzed using gas chromatography-mass spectrometry (GC-MS) technique. In total we have identified 53 illicit drugs with Δ-9-tetrahydrocannabinol (THC), amphetamine, N-ethylhexedrone, 3,4-methylenedioxy methamphetamine (MDMA), 4-chloromethcathinone (4-CMC), α-pyrrolidinoisohexaphenone (α-PHiP), cocaine, and 4-chloroethcathinone (4-CEC) being most commonly found and making 38.5, 17.8, 15.5, 8.0, 3.5, 2.7, 2.1, and 2.0% of the total studied pool, respectively. Except for methadone, all analyzed street samples were spiked with at least one cutting agent. Caffeine was the most frequently found adulterating addition present in around 33% (excluding marijuana) of the analyzed samples. Other identified cutting agents make an impressive group of more than 160 compounds. Finally, we have tabulated, illustrated, and discussed presented data in a view of smart and portable sensors development.

摘要

在这项工作中,我们集中对 5647 个街头样本进行了分析,涵盖大麻、常见和新型娱乐性非法药物。所有样本均使用气相色谱-质谱联用技术(GC-MS)进行分析。我们总共鉴定出 53 种非法药物,其中包括Δ-9-四氢大麻酚(THC)、安非他命、N-乙基己基酮、3,4-亚甲二氧基甲基苯丙胺(MDMA)、4-氯甲卡西酮(4-CMC)、α-吡咯烷异己酮(α-PHiP)、可卡因和 4-氯乙基卡西酮(4-CEC),这些物质最为常见,分别占总研究样本的 38.5%、17.8%、15.5%、8.0%、3.5%、2.7%、2.1%和 2.0%。除美沙酮外,所有分析的街头样本均添加了至少一种切割剂。在大约 33%(不包括大麻)的分析样本中,咖啡因是最常见的掺杂物。其他已鉴定的切割剂是一组令人印象深刻的超过 160 种化合物。最后,我们根据智能和便携式传感器的发展,对呈现的数据进行了列表、说明和讨论。

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