Trace Detection of Tetrahydrocannabinol in Body Fluid via Surface-Enhanced Raman Scattering and Principal Component Analysis
Trace Detection of Tetrahydrocannabinol in Body Fluid via Surface-Enhanced Raman Scattering and Principal Component Analysis
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DOI：
10.1021/acssensors.9b00476
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发表时间：
2019-04-01
期刊：
影响因子：
8.9
通讯作者：
Wang, Alan X.
中科院分区：
文献类型：
--
作者：
Sivashanmugan, Kundan;Squire, Kenneth;Wang, Alan X.
四氢大麻酚（THC）是大麻中的主要活性成分，人体体液中THC的快速检测在法医分析和公共卫生中起着至关重要的作用。表面增强拉曼散射（Sers）传感已越来越多地用于检测非法药物;然而，仅报道了THC在甲醇溶液中的有限Sers传感结果，而其在体液（诸如唾液或血浆）中的存在尚未被研究。在这篇文章中，我们展示了痕量检测THC在人体血浆和唾液溶液中使用SERS活性基板形成的原位生长的银纳米粒子（银纳米粒子）硅藻硅藻壳。血浆和纯化唾液溶液中浓度极低（1 pM）的THC可充分区分，重现性良好。在1603 cm（-1）处的Sers峰具有3.4cm-1的标准偏差，用于评估甲醇溶液中的THC浓度。我们的Sers测量还表明，该特征峰在血浆和唾液溶液中经历了明显的波数偏移和稍宽的变化。此外，我们还观察到，由于O-C=O的伸缩模式，血浆或唾液样品中的THC在1621 cm（-1）处产生了较强的Sers峰，这与体液中THC结构的代谢变化有关。为了进行定量分析，应用主成分分析（PCA）来分析甲醇溶液、血浆和纯化的唾液样品中的1 pM THC的Sers光谱。前三个主成分的最大变异性达到71%，这清楚地表明了不同生物背景信号的影响。同样，在不同的代谢时间下的原始唾液溶液中的THC的Sers光谱进行了研究，使用PCA和98%的变异占前三个主成分。在不同THC驻留时间测量的样品的清晰分离可以提供关于体液中THC代谢过程的时间依赖性信息。使用线性回归模型来估计原始唾液中THC的代谢率，并且测试数据集中的预测代谢时间与训练数据集匹配良好。总之，混合等离子体-生物二氧化硅Sers基底可以实现对复杂体液中痕量THC的超灵敏、近定量检测，这可能会改变法医传感技术，以检测大麻滥用。
Tetrahydrocannabinol (THC) is the main active component in marijuana and the rapid detection of THC in human body fluid plays a critical role in forensic analysis and public health. Surface-enhanced Raman scattering (SERS) sensing has been increasingly used to detect illicit drugs; however, only limited SERS sensing results of THC in methanol solution have been reported, while its presence in body fluids, such as saliva or plasma, has yet to be investigated. In this article, we demonstrate the trace detection of THC in human plasma and saliva solution using a SERS-active substrate formed by in situ growth of silver nanoparticles (Ag NPs) on diatom frustules. THC at extremely low concentration of 1 pM in plasma and purified saliva solutions were adequately distinguished with good reproducibility. The SERS peak at 1603 cm(-1) with standard deviation of 3.4 cm-' was used for the evaluation of THC concentration in a methanol solution. Our SERS measurement also shows that this signature peak experiences a noticeable wavenumber shift and a slightly wider variation in the plasma and saliva solution. Additionally, we observed that THC in plasma or saliva samples produces a strong SERS peak at 1621 cm(-1) due to the stretching mode of O-C=O, which is related to the metabolic change of THC structures in body fluid. To conduct a quantitative analysis, principal component analysis (PCA) was applied to analyze the SERS spectra of 1 pM THC in methanol solution, plasma, and purified saliva samples. The maximum variability of the first three principal components was achieved at 71%, which clearly denotes the impact of different biological background signals. Similarly, the SERS spectra of THC in raw saliva solution under various metabolic times were studied using PCA and 98% of the variability is accounted for in the first three principal components. The clear separation of samples measured at different THC resident times can provide time dependent information on the THC metabolic process in body fluids. A linear regression model was used to estimate the metabolic rate of THC in raw saliva and the predicted metabolic time in the testing data set matched well with the training data set. In summary, the hybrid plasmonic-biosilica SERS substrate can achieve ultrasensitive, near-quantitative detection of trace levels of THC in complex body fluids, which can potentially transform forensic sensing techniques to detect marijuana abuse.