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High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
Published on: April 23, 2019
Hybrid multispectroscopic-chemometric strategy combined with DLLME for the detection of benzodiazepines in complex
Busra Emanetoglu1, Pelin Guzel2, Elif Koyuncu3
1Division of Forensic Sciences, Institute of Postgraduate Education, Istanbul Medeniyet University, Istanbul, 34700, Turkiye.
Abstract:
The detection of benzodiazepines in beverage residues is of crucial importance in forensic toxicology, particularly in investigations of drug-facilitated crimes. However, their determination in complex beverage matrices remains analytically challenging by severe matrix interferences and low analyte concentrations. In this study, a hybrid multispectroscopic-chemometric methodology was developed for determination of alprazolam (ALP) and lorazepam (LORA) following dispersive liquid-liquid microextraction (DLLME) pretreatment. The proposed approach integrates DLLME with UV-Vis, fluorescence and their derivative spectroscopies, combined with principal component analysis (PCA) and correlation-based data evaluation. Various beverage matrices, including wine, vodka, soft drinks, and sparkling water, were analyzed to assess the method's applicability under realistic forensic scenarios. DLLME significantly enhanced spectral quality and minimized matrix effects, improving the detection of both analytes in various beverages. UV-Vis derivative spectroscopy enhanced spectral resolution with analyte-dependent performance, while fluorescence spectroscopy provided complementary analytical information. Chemometric interpretation via principal component analysis (PCA) enabled effective differentiation between blank and spiked samples, confirming the robustness and reliability of the proposed analytical workflow. For both ALP and LORA cases, the first three principal components cumulatively captured over 80% of the total variance, indicating that they were statistically sufficient to adequately represent the dataset for further data analysis. Cluster validation using the elbow and silhouette methods consistently supported k = 2 as the optimal number of clusters for both cases. Overall, the combined DLLME-multispectroscopic-chemometric strategy offers a rapid, cost-effective, and accessible alternative to advanced instrumental techniques for the preliminary screening and differentiation of benzodiazepine residues in complex forensic beverage samples.
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