Development and validation of the UHPLC-MS/MS method for the quantitative determination of 25 PFAS in dried blood spots.

Per- and polyfluoroalkyl substances (PFAS) are anthropogenic fluorine-containing compounds largely used in industrial and consumer applications. They tend to bioaccumulate in the human body after intake from various sources in daily life. Following repeated exposure to PFAS, a broad range of adverse health outcomes has been reported. Consequently, monitoring PFAS levels in human blood is of paramount importance for public health policies. In contrast with traditional venipuncture, dried blood spots (DBS) constitute a reliable, cheap, and less invasive technique to allow microsampling by capillary blood collected on a specific device. This work aimed to develop and validate an innovative analytical method, combining quantitative DBS with UHPLC-MS/MS instrumentation to identify and quantify 25 PFAS. The extraction procedure was developed and optimized within the range 2-100 ng/mL. Specifically, fortified blood was applied on Capitainer®B devices providing 10 µL of blood volume through a microfluidic channel. After 3 h of drying, the extraction was performed by methanol under sonication, followed by centrifugation. Then, the extraction solvent was evaporated; the residue was reconstituted with the mobile phase solution. The validated method evidenced good sensitivity, with limits of detection ranging from 0.4 ng/mL (PFODA, PFOS) to 1.0 ng/mL (PFOA, 3,6-OPFHpA). The ± 20% acceptability criteria established for intra- and inter-day precision and accuracy were fulfilled for all analytes. High recovery-above 80%-was recorded, whereas significant matrix effect resulted in ion enhancement (> 50%) for 13 analytes. In conclusion, the proposed workflow proved to be reliable, fit for purpose, and easily adaptable in the laboratory routine.

An initial exploration of machine learning for establishing associations between genetic markers and THC levels in Cannabis sativa samples.

Cannabis sativa, a globally commercialized plant used for medicinal, food, fiber production, and recreation, necessitates effective identification to distinguish legal and illegal varieties in forensic contexts. This research utilizes multivariate statistical models and Machine Learning approaches to establish correlations between specific genotypes and tetrahydrocannabinol (Δ9-THC) content (%) in C. sativa samples. 132 cannabis leaves samples were obtained from legal growers in Piedmont, Italy, and illegal drug seizures in Turin. Samples were genetically profiled using a 13-loci STR multiplex and their Δ9-THC content was detected through quantitative GC-MS analysis. This study aims to assess the use of supervised classification modelling on genetic data to distinguish cannabis samples into legal and illegal categories, revealing distinct clusters characterized by unique allele profiles and THC content. t-distributed Stochastic Neighbor Embedding (t-SNE), Random Forest (RF) and Partial Least Squares Regression (PLS-R) were executed for the machine learning modelling. All the tested models resulted effective discriminating between legal samples and illegal. Although further validation is necessary, this study presents a novel forensic investigative approach, potentially aiding law enforcement in significant marijuana seizures or tracking illicit drug trafficking routes.

Method development for the quantification of nine nitazene analogs and brorphine in Dried Blood Spots utilizing liquid chromatography - tandem mass spectrometry.

The detection of nitazenes in biological fluids is increasingly needed as they are repeatedly reported in intoxication and overdose cases. A simple method for the quantification of low levels of nine nitazene analogs and brorphine in Dried Blood Spots (DBS) was developed and validated. 10 µL of spiked whole blood is deposited on a Capitainer®B card and allowed to dry. The spot is punched out, and extracted with 500 µL methanol:acetonitrile (3:1 v/v) added with 1.5 µL of fentanyl-D5 as the internal standard. After stirring, sonication, and centrifugation of the vial, the solvent is dried under nitrogen, the extract is reconstituted in 30 µL methanol, and 1 µL is injected into a UHPLC-MS/MS instrument. The method validation showed linear calibration in the 1-50 ng/mL range, LOD values ranging between 0.3 ng/mL (isotonitazene) and 0.5 ng/mL (brorphine), average CV% and bias% within 15 % and 10 % for all compounds, respectively. The matrix effect due to blood and filter paper components was within 85-115 % while recovery was between 15-20 %. Stability tests against time and temperature showed no significant variations for storage periods up to 28 days. Room temperature proved to represent the best samples storage conditions. UHPLC-MS/MS proved capable to reliably identify all target analytes at low concentration even in small specimen volumes, as those obtained from DBS cards, which in turn confirmed to be effective and sustainable micro-sampling devices. This procedure improves the efficiency of toxicological testing and provides an innovative approach for the identification of the nitazene class of illicit compounds.

Metabolic study of new psychoactive substance methoxpropamine in mice by UHPLC-QTOF-HRMS.

Methoxpropamine (MXPr) is an arylcyclohexylamine dissociative drug structurally similar to 3-methoxyeticyclidine, ketamine, and deschloroketamine, recently appeared in the European illegal market, and was classified within the new psychoactive substances (NPS). Our study investigated the metabolism of MXPr to elucidate the distribution of the parent drug and its metabolites in body fluids and fur of 16 mice. After the intraperitoneal administration of MXPr (1, 3, and 10 mg/kg), urine samples from eight male and eight female mice were collected every hour for six consecutive hours and then at 12- to 24-h intervals. Additionally, plasma samples were collected 24 h after MXPr (1 and 3 mg/kg) administration. Urine and plasma were diluted 1:3 with acetonitrile/methanol (95:5) and directly injected into the UHPLC-QTOF-HRMS system. The phase-I and phase-II metabolites were preliminarily identified by means of the fragmentation patterns and the exact masses of both their precursor and fragment ions. Lastly, the mice fur was analyzed following an extraction procedure specific for the keratin matrix. Desmethyl-MXPr-glucoronide was identified in urine as the main metabolite, detected up to 24 h after administration. The presence of norMXPr in urine, plasma, and fur was also relevant, following a N-dealkylation process of the parent drug. Other metabolites that were identified in fur and plasma included desmethyl-MXPr and dihydro-MXPr. Knowledge of the MXPr metabolites evolution is likely to support their introduction as target compounds in NPS toxicological screening analysis on real samples, both to confirm intake and extend the detection window of the dissociative drug MXPr in the biological matrices.

Recent advances in the detection of drugs of abuse by dried blood spots.

The purpose of this review study was to sum up the main recent advances reported in the scientific literature about the detection of common drugs of abuse in biological samples upon their collection by dried blood spot devices. The most recent, innovative and fully validated methods for the qualitative and/or quantitative detection of common drugs of abuse are reported, including alprazolam, clonazepam, diazepam, 3,4-methylenedioxymethamphetamine, 3,4-methylenedioxyamphetamine, 3,4-methyl-enedioxyethylamphetamine, amphetamine, methamphetamine, cocaine, tetrahydrocannabinol, 6-monoacetylmorphine, morphine, codeine, hydromorphone, hydrocodone, oxycodone, noroxycodone, tramadol, methadone, buprenorphine, fentanyl, ketamine and their respective metabolites and γ-hydroxybutyric acid. Dried blood spot proved to be extremely promising for routine analysis of forensic cases, although large-scale experiments on real samples need to be performed to confirm the emerging advantages of the technique and remove the potential limitations still affecting its widespread application.