城市生活污水中阿片类、苯丙胺类以及苯二氮卓类滥用物质的高分辨质谱筛选及确证

本研究采用固相萃取对城市生活污水样品进行前处理,超高效液相色谱-串联高分辨质谱法筛选及确证污水中阿片类、苯丙胺类和苯二氮卓类等36种滥用物质,并将其应用于实际污水样品。结果表明,该方法的专属性强,36种滥用物质的检出限范围为5~20 ng/L。在12个污水样品中共检出吗啡、可待因、哌替啶、曲马多4种阿片类滥用物质,甲基苯丙胺1种苯丙胺类滥用物质以及地西泮、去甲西泮、艾司唑仑、阿普唑仑4种苯二氮卓类滥用物质。城市生活污水中存在多种滥用物质,区域流行性不同,利用本方法可进行快速、准确地筛选与确认。     

Principal component analysis coupled with artificial neural networks-a combined technique classifying small molecular structures using a concatenated spectral database

In this paper we present several expert systems that predict the class identity of the modeled compounds, based on a preprocessed spectral database. The expert systems were built using Artificial Neural Networks (ANN) and are designed to predict if an unknown compound has the toxicological activity of amphetamines (stimulant and hallucinogen), or whether it is a nonamphetamine. In attempts to circumvent the laws controlling drugs of abuse, new chemical structures are very frequently introduced on the black market. They are obtained by slightly modifying the controlled molecular structures by adding or changing substituents at various positions on the banned molecules. As a result, no substance similar to those forming a prohibited class may be used nowadays, even if it has not been specifically listed. Therefore, reliable, fast and accessible systems capable of modeling and then identifying similarities at molecular level, are highly needed for epidemiological, clinical, and forensic purposes. In order to obtain the expert systems, we have preprocessed a concatenated spectral database, representing the GC-FTIR (gas chromatography-Fourier transform infrared spectrometry) and GC-MS (gas chromatography-mass spectrometry) spectra of 103 forensic compounds. The database was used as input for a Principal Component Analysis (PCA). The scores of the forensic compounds on the main principal components (PCs) were then used as inputs for the ANN systems. We have built eight PC-ANN systems (principal component analysis coupled with artificial neural network) with a different number of input variables: 15 PCs, 16 PCs, 17 PCs, 18 PCs, 19 PCs, 20 PCs, 21 PCs and 22 PCs. The best expert system was found to be the ANN network built with 18 PCs, which accounts for an explained variance of 77%. This expert system has the best sensitivity (a rate of classification C = 100% and a rate of true positives TP = 100%), as well as a good selectivity (a rate of true negatives TN = 92.77%). A comparative analysis of the validation results of all expert systems is presented, and the input variables with the highest discrimination power are discussed.     

Characterizing the psychological state produced by LSD.

Two studies, involving 69 male inmates of an experimental penal institution, investigated the psychological states produced by LSD as compared with amphetamine and placebo controls. A number of scales on a newly developed subjective drug-effects questionnaire significantly differentiated the groups. This instrument was further used to identify 3 qualitatively different subjective states produced by LSD (moderately euphoric, dysphoric, and ambivalent). New techniques for exploring the perceptual and vocal components of emotional change were also applied. These techniques further elucidated the quality and possible origin of the psychological states produced by LSD. The results (which indicate the presence of highly intense but contradictory emotions) were interpreted in the light of a current theory of emotion and Bartlett's concept of "effort after meaning." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

“毒驾”案件中质谱证据的采集及应用

吸毒后驾驶(简称"毒驾")案件中,科学证据的检验方法对相关法律法规的制订以及案件公平公正的处理具有重要意义。本研究以微量陈旧血样中安非他明类毒品为分析目标,建立了一种气相色谱-正离子化学电离-串联质谱(GC/PCI-MS/MS)检测方法,并将其应用于370份交通事故案件中"酒驾"检测后剩余的微量陈旧血样。结果表明,该方法的灵敏度高、回收率好,测试样品中安非他明类毒品的检出率约为0.27%。上述研究结果不仅为我国"毒驾"案件的处理提供了一种高效的检测方法,而且为相关法律措施的制订提供了重要的参考数据和研究思路。