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利用动态表面增强拉曼光谱和支持向量机检测和直接读出人体尿液中的药物。

Detection and direct readout of drugs in human urine using dynamic surface-enhanced Raman spectroscopy and support vector machines.

机构信息

Institute of Intelligent Machines, Chinese Academy of Sciences , Hefei, 230031, China.

出版信息

Anal Chem. 2015 Mar 3;87(5):2937-44. doi: 10.1021/acs.analchem.5b00137. Epub 2015 Feb 10.

Abstract

A new, novel, rapid method to detect and direct readout of drugs in human urine has been developed using dynamic surface-enhanced Raman spectroscopy (D-SERS) with portable Raman spectrometer on gold nanorods (GNRs) and a classification algorithm called support vector machines (SVM). The high-performance GNRs can generate gigantic enhancement and the SERS signals obtained using D-SERS on it have high reproducibility. On the basis of this feature of D-SERS, we have obtained SERS spectra of urine and urine containing methamphetamine (MAMP). SVM model was built using these data for fast identified and visual results. This general method was successfully applied to the detection of 3, 4-methylenedioxy methamphetamine (MDMA) in human urine. To verify the accuracy of the model, drug addicts' urine containing MAMP were detected and identified correctly and rapidly with accuracy more than 90%. The detection results were displayed directly without analysis of their SERS spectra manually. Compared with the conventional method in lab, the method only needs a 2 μL sample volume and takes no more than 2 min on the portable Raman spectrometer. It is anticipated that this method will enable rapid, convenient detection of drugs on site for the police.

摘要

一种使用动态表面增强拉曼光谱(D-SERS)和便携式拉曼光谱仪在金纳米棒(GNRs)上检测和直接读出人类尿液中药物的新的、新颖的、快速的方法,并结合一种称为支持向量机(SVM)的分类算法。高性能的 GNRs 可以产生巨大的增强,使用 D-SERS 在其上获得的 SERS 信号具有很高的重现性。基于 D-SERS 的这一特性,我们已经获得了尿液和尿液中含有甲基苯丙胺(MAMP)的 SERS 光谱。使用这些数据建立了 SVM 模型,以实现快速识别和可视化结果。该通用方法已成功应用于人类尿液中 3,4-亚甲二氧基甲基苯丙胺(MDMA)的检测。为了验证模型的准确性,正确快速地检测并识别了含有 MAMP 的吸毒者尿液,准确率超过 90%。检测结果直接显示,无需手动分析其 SERS 光谱。与实验室中的常规方法相比,该方法仅需要 2μL 的样本量,在便携式拉曼光谱仪上耗时不超过 2 分钟。预计该方法将使警察能够快速、方便地在现场检测毒品。

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