Identification and Quantification of the Main Psychoactive Ingredients of Cannabis in Urine Using Excitation-Eemission Matrix Fluorescence Coupled with Parallel Factor Analysis.

Cannabis is the most prevalent abused substance after alcohol, and its consumption severely harms human health and thus adversely impacts society. The identification and quantification of cannabis in urine play important roles in practical forensics. Excitation-emission matrix (EEM) fluorescence spectroscopy coupled with parallel factor (PARAFAC) analysis was developed to identify and quantify the four main ingredients of cannabis in urine samples. The main ingredients of cannabis including Δ-9-tetrahydrocannabinol (THC), cannabidiol, cannabinol, and tetrahydrocannabinolic acid (THC-COOH) exhibited diverse fluorescence characteristics, and the concentrations of these compounds depicted a positive linear relationship with the fluorescence intensity at the ng/mL level. The EEM/PARAFAC method adequately characterized and discriminated the four ingredients in calibration and prediction samples with a low root-mean-square error of prediction (RMSEP; 0.03-0.07 µg/mL) and limit of quantitation (LOQ; 0.26-0.71 µg/mL). The prediction results of the EEM/PARAFAC method well correlated with that of GC-MS with a low RMSEP range (0.01-0.05 µg/mL) and LOQ range (0.07-0.44 µg/mL) in urine samples. The EEM spectroscopic investigation coupled with the PARAFAC algorithm results in an organic, solvent-less, fast, reliable tool to perform accurate and rapid screening of cannabis abusers.

Identification and classification of ATS in oral fluid based on Ag nanoassemblies on Si surface doped with Au nanobipyramids.

Herein, a novel Ag NP substrate doped with Au nanobipyramids was designed and fabricated via a convenient procedure of galvanic reaction for the identification and classification of amphetamine-type stimulants (ATS) in oral fluids in combination with surface enhanced Raman scattering (SERS). The substrate was shown to have a three-dimensional nanostructure, high SERS activity, and good stability. In combination with SERS, the Ag NP substrate doped with Au nanobipyramids was able to detect ultra-low traces of ATS, including amphetamine, methylamphetamine (MA), 3,4-methylenedioxyamphetamine (MDA), and 3,4-methylenedioxymethylamphetamine (MDMA) in oral fluid with limit of detection (LOD) and limit of determination quantitation (LOQ) as low as 10-9 mg/mL, which is much better than the current spectroscopic techniques. The equations between concentration and peaks intensity for quantitative analysis displied good doublelogarithmic linear relations and reliability figures of merit at nanogram concentration level in compartion with GC-MS method. The approach can be broadly applied to the ultra-low trace detection of ATS in oral fluid and would be particularly useful for the analyses of nitrogenous organic compounds.