Metabolism of the benzodiazepines norflurazepam, flurazepam, fludiazepam and cinolazepam by human hepatocytes using high-resolution mass spectrometry and distinguishing their intake in authentic urine samples

Metabolic profiling of a new synthetic cannabinoid receptor agonist, ADMB-FUBIATA, with human liver microsomes, human primary hepatocytes and human recombinant CYP450 enzymes using LC-quadrupole-orbitrap MS

A novel synthetic cannabinoid receptor agonist (SCRA), ADMB-FUBIATA, featuring an acetamide-linked structure, has emerged on the illicit drug market. To provide dependable verification of its consumption and identify reliable biomarkers, we investigated an in vitro metabolism study of ADMB-FUBIATA incubated with human primary hepatocytes (HPHs) for the first time and correlated our findings with those from human liver microsomes (HLMs). In this work, ADMB-FUBIATA (10 μM) was incubated with HLM and HPH for 1 and 5 h, respectively, and then subjected to LC-quadrupole-orbitrap MS. A total of 25 metabolites across 8 metabolic pathways were identified after incubation with HLM and HPH, respectively. Monohydroxylation and N-dealkylation were the major metabolic pathways, and formation to ketone was first identified. In addition, the metabolism of ADMB-FUBIATA were found to be mediated by multiple CYP450 enzymes, predominantly CYP2C19, 2D6, and 3A4. This research also initially characterized the fragmentation patterns of the metabolites of ADMB-FUBIATA, elaborating on their structural relationship with ADMB-FUBIATA analogs. To effectively monitor ADMB-FUBIATA abuse, metabolites M4 and M1 were proposed as reliable biomarkers by cross-validating the HLM and HPH incubation results.

Metabolic Profile Analysis of Designer Benzodiazepine Etizolam in Zebrafish and Human Liver Microsomes

As one of the most widely abused designer benzodiazepines worldwide, Etizolam is characterized by its high addiction potential, low production cost, and difficulty in detection. Due to the rapid metabolism of Etizolam in the human body, the probability of detecting the Etizolam parent drug in actual case samples by forensic personnel is low. Therefore, without detecting the parent drug, analysis of Etizolam metabolites can help forensic personnel provide references and suggestions on whether the suspect has taken Etizolam. This study simulates the objective metabolic process of the human body. It establishes a zebrafish in vivo metabolism model and a human liver microsome in vitro metabolism model to analyze the metabolic characteristics of Etizolam. A total of 28 metabolites were detected in the experiment, including 13 produced in zebrafish, 28 produced in zebrafish urine and feces, and 17 produced in human liver microsomes. The UPLC-Q-Exactive-MS technology was used to analyze the structures and related metabolic pathways of Etizolam metabolites in zebrafish and human liver microsomes, and a total of 9 metabolic pathways were identified, including monohydroxylation, dihydroxylation, hydration, desaturation, methylation, oxidative deamination to alcohol, oxidation, reduction acetylation, and glucuronidation. Among them, metabolites involving hydroxylation reactions (including monohydroxylation and dihydroxylation) accounted for 57.1% of the total number of potential metabolites, indicating that hydroxylation may be the major metabolic pathway of Etizolam. Based on the response values of each metabolite, monohydroxylation (M1), desaturation (M19), and hydration (M16) were recommended as potential biomarkers for Etizolam metabolism. The experimental results provide reference and guidance for forensic personnel in identifying Etizolam use in suspects.

Investigating a broad range of emerging contaminants in a set of anthropogenically impacted environmental compartments

Environmental compartments are repositories of probably thousands of emerging contaminants (ECs) released along with treated/untreated wastewater. Despite extensive studies on the detection of ECs in surface water, other environmental compartments such as sediments and groundwater are yet to be thoroughly investigated. To assess the heavy anthropogenic impact on the environment, 24 environmental samples comprising of surface water, sediment and groundwater collected from the Yamuna River basin of India were analyzed via target and suspect screening. The surface water and sediment samples were collected from upstream and downstream of densely populated cities and towns situated along the heavily contaminated river Yamuna. The groundwater samples were collected from shallow drinking water wells of the catchment. Liquid chromatography tandem mass-spectroscopy was used to quantify 10 widely consumed pharmaceuticals in the samples. The study also analyzed the potential health hazards posed by the quantified contaminants. In order to evaluate further, the surface water and groundwater samples were subjected to high resolution mass spectrometry (HRMS) screening against a library resulting in a list of 450 ECs in the surface water and 309 ECs in the groundwater. Agricultural chemicals and pharmaceuticals found abundantly in the samples and half of whom were reported first time. The risk quotient was calculated to assess the potential hazard of the target analytes.

Spectral trends in GC-EI-MS data obtained from the SWGDRUG mass spectral library and literature: A resource for the identification of unknown compounds

Rapid identification of new or emerging psychoactive substances remains a critical challenge in forensic drug chemistry laboratories. Current analytical protocols are well-designed for confirmation of known substances yet struggle when new compounds are encountered. Many laboratories initially attempt to classify new compounds using gas chromatography-electron ionization-mass spectrometry (GC-EI-MS). Though there is a large body of research focused on the analysis of illicit substances with GC-EI-MS, there is little high-level discussion of mass spectral trends for different classes of drugs. This manuscript compiles literature information and performs simple exploratory analyses on evaluated GC-EI-MS data to investigate mass spectral trends for illicit substance classes. Additionally, this work offers other important aspects: brief discussions of how each class of drugs is used; illustrations of EI mass spectra with proposed structures of commonly observed ions; and summaries of mass spectral trends that can help an analyst classify new illicit compounds.