Bar adsorptive microextraction and liquid chromatography-diode array detection of synthetic cannabinoids in oral fluid.
Samir M AhmadNuno R NengCláudio R QueirósHelena GasparJosé Manuel F NogueiraPublished in: Analytical and bioanalytical chemistry (2024)
In recent years, synthetic cannabinoids (SCs) have become a major public health issue. For this reason, there is a need for innovative analytical methods that allow its monitoring in biological matrices. In this work, we propose a novel methodology to screen eight SCs (AM-694, cumyl-5F-PINACA, MAM-2201, 5F-UR-144, JWH-018, JWH-122, UR-144 and APINACA) in oral fluids. A bar adsorptive microextraction method followed by microliquid desorption combined with high-performance liquid chromatography with diode array detection (BAµE-µLD/HPLC-DAD) was developed to monitor the target SCs. The main factors affecting the BAµE technology were fully optimized for oral fluid analysis. Under optimized experimental conditions, the proposed methodology showed good linear dynamic ranges from 20.0 to 2000.0 µg L -1 (r 2 > 0.99, relative residuals < 15%), limits of detection between 2.0 and 5.0 µg L -1 and suitable average recovery yields (87.9-100.5%) for the eight studied SCs. The intra- and interday accuracies (bias ≤ ± 14.7%) and precisions (RSD ≤ 14.9%) were also evaluated at three spiking levels. The validated methodology was then assayed to oral fluid samples collected from several volunteers. The proposed analytical approach showed remarkable performance and could be an effective alternative for routine monitoring of the target compounds in oral fluid.
Keyphrases
- high performance liquid chromatography
- liquid chromatography
- simultaneous determination
- tandem mass spectrometry
- mass spectrometry
- solid phase extraction
- public health
- liquid chromatography tandem mass spectrometry
- ms ms
- high resolution mass spectrometry
- loop mediated isothermal amplification
- high throughput
- ionic liquid
- high resolution
- real time pcr
- label free
- molecularly imprinted
- data analysis