Wastewater surveillance of 105 pharmaceutical drugs and metabolites by means of ultra-high-performance liquid-chromatography-tandem high resolution mass spectrometry.

Water pollution from pharmaceutical drugs is becoming an environmental issue of increasing concern, making water quality monitoring a crucial priority to safeguard public health. In particular, the presence of antidepressants, benzodiazepines, antiepileptics, and antipsychotics require specific attention as they are known to be harmful to aquatic biota. In this study, a multi-class comprehensive method for the detection of 105 pharmaceutical residues in small (30 mL) water samples was developed according to fit-for-purpose criteria and then applied to provide wide screening of samples obtained from four Wastewater Treatment Plants (WWTPs) in northern Italy. The filtered samples (0.22 µm filters) were extracted by SPE, and then eluted. 5 µL of the concentrated samples were analyzed by a UHPLC-QTOF-HRMS method validated for screening purposes. Adequate sensitivity was recorded for all target analytes, with limits of detection below 5 ng/L for 76 out of 105 analytes. A total of 23 out of the 105 targeted pharmaceutical drugs was detected in all samples. Several further compounds were detected over wide concentration intervals, ranging from ng/L to µg/L. In addition, the retrospective analysis of full-scan QTOF-HRMS data was exploited to carry out an untargeted screening of some drugs' metabolites. As a proof of concept, it was investigated the presence of the carbamazepine metabolites, which is among the most frequently detected contaminants of emerging concern in wastewater. Thanks to this approach, 10,11-dihydro-10-hydroxycarbamazepine, 10,11-dihydro-10,11-dihydroxycarbamazepine and carbamazepine-10,11-epoxide were identified, the latter requiring particular attention, since it exhibits antiepileptic properties similar to carbamazepine and potential neurotoxic effects in living organism.

Optimization and validation of a GC-MS quantitative method for the determination of an extended estrogenic profile in human urine: Variability intervals in a population of healthy women.

An analytical method based on GC-MS was developed for the determination of a wide panel of urinary estrogens, together with their principal metabolites. Because of the low concentration of estrogens in urine, an efficient sample pre-treatment was optimized by a design of experiment (DoE) procedure to achieve satisfactory sensitivity. A second DoE was built for the optimization of the chromatographic run, with the purpose of reaching the most efficient separation of analytes with potentially interfering ions and similar chromatographic properties. The method was fully validated using a rigorous calibration strategy: from several replicate analyses of blank urine samples spiked with the analytes, calibration models were built with particular attention to the study of heteroscedasticity and quadraticity. Other validation parameters, including the limit of detection, intra-assay precision and accuracy, repeatability, selectivity, specificity, and carry-over, were obtained using the same set of data. Further experiments were performed to evaluate matrix effect and extraction recovery. Then the urinary estrogen profiles of 138 post-menopausal healthy women were determined. These profiles provide a representation of physiological concentration ranges, which, in forthcoming studies, will be matched on the base of multivariate statistics with the urinary estrogenic profile of women with breast or ovarian cancer.

Determination of cannabinoids in urine, oral fluid and hair samples after repeated intake of CBD-rich cannabis by smoking.

Cannabidiol prevalent (CBD-rich) cannabis derivatives are increasingly popular and widely available on the market as replacement of THC, tobacco substitutes or therapeutics for various health conditions. In this paper, we evaluate the impact of a repeated CBD-rich cannabis intake on levels of cannabinoids in biological samples. Urine, oral fluid and hair (pubic and head) samples were obtained from a naive user during a 26-day smoking period of one 250-mg CBD-rich cannabis joint/day containing 6.0% cannabidiol (CBD; 15mg) and 0.2% delta-9-tetrahydrocannabinol (THC; 0.5mg). In total, 35 urine, 8 oral fluid and 4hair sample were collected. Cannabinoids concentrations were quantified by a UHPLC/MSn technique. The results suggested that the repeated exposure to CBD-rich cannabis (containing small amounts of THC) can generate positive results in biological samples. Urinary concentrations of 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH) were quantitatively detected after 8 days from the smoking start and exceeded the 15ng/mL cut-off limit on day-15 even in the urine sample collected 12h after the last intake. In the oral fluid collected on day-26, no cannabinoids were found before the cannabis intake, thus excluding accumulation, while THC was detectable up to 3h after the cannabis intake, at concentrations progressively decreasing from about 18 to 6ng/mL. Hair samples collected one week after the end of the study turned out negative for THC and THC-COOH, suggesting that this matrix is suitable to discriminate the chronic consumption of CBD-rich cannabis from THC-prevalent products. The obtained findings are relevant for the interpretations of cannabinoids levels in biological fluids, also in light of the legal implications of a positive result.

Individual and cyclic estrogenic profile in women: Structure and variability of the data.

The concentration of estrogens in the body fluids of women is highly variable, due to the menstrual cycle, circadian oscillations, and other physiological and pathological causes. To date, only the cyclic fluctuations of the principal estrogens (estradiol and estrone) have been studied, with limited outcome of general significance. Aim of the present study was to examine in detail the cyclic variability of a wide estrogens' panel and to interpret it by multivariate statistics. Four estrogens (17α-estradiol, 17ß-estradiol, estrone, estriol) and eleven of their metabolites (4-methoxyestrone, 2-methoxyestrone, 16α-hydroxyestrone, 4-hydroxyestrone, 2-hydroxyestrone, 4-methoxyestradiol, 2-methoxyestradiol, 4-hydroxyestradiol, 2-hydroxyestradiol, estriol, 16-epiestriol, and 17-epiestriol) were determined in urine by a gas chromatography - mass spectrometry method, which was developed by design of experiments and fully validated according to ISO 17025 requirements. Then, urine samples collected every morning for a complete menstrual cycle from 9 female volunteers aged 24-35 years (1 parous) were analysed. The resulting three-dimensional data (subjects × days × estrogens) were interpreted using several statistical tools. Parallel Factor Analysis compared the estrogen profiles in order to explore the cyclic and inter-individual variability of each analyte. Principal Component Analysis (PCA) provided clear separation of the sampling days along the cycle, allowing discrimination among the luteal, ovulation, and follicular phases. The scores obtained from PCA were used to build a Linear Discriminant Analysis classification model which enhanced the recognition of the three cycle's phases, yielding an overall classification non-error rate equal to 90%. These statistical models may find prospective application in fertility studies and the investigation of endocrinology disorders and other hormone-dependent diseases.

Determination of several synthetic cathinones and an amphetamine-like compound in urine by gas chromatography with mass spectrometry. Method validation and application to real cases.

Most routine practices for drugs-of-abuse testing do not include screening procedures for new psychoactive substances, despite their increasing diffusion, preventing clear knowledge of the real consumption of these drugs in the populations. To make up for this shortcoming, a gas chromatography with mass spectrometry method was developed for the simultaneous determination of 18 synthetic cathinones and one amphetamine-like compound in human urine. The sample preparation was based on liquid-liquid extraction under alkaline condition followed by derivatization with trifluoroacetic anhydride. The separation of the 19 analytes was achieved in less than 10 min. The whole methodology was validated according to national and international guidelines. Selectivity, linearity range, limit of detection and limit of quantitation, precision and accuracy were evaluated. For all the analytes, the calibration curve was linear in the 100-1000 ng/mL concentration range. The limits of detection ranged from 10 to 30 ng/mL and limits of quantitation from 30 to 100 ng/mL. Precisions were in the ranges 0.1-10.4%, and 1.0-12.1% for low (100 ng/mL) and high (1000 ng/mL) concentration, respectively. The accuracy, expressed as bias% was within ±20% for all the analytes. The present method was successfully applied to urine samples originating from autopsies, drug abuse/withdrawal controls, clinical investigations, roadside controls, driving re-licensing, and workplace testing.

Characterization of in vitro generated metabolites of the selective androgen receptor modulators S-22 and S-23 and in vivo comparison to post-administration canine urine specimens.

Selective androgen receptor modulators (SARMs) have great therapeutic potential in various diseases including cancer cachexia, sarcopenia, and osteoporosis, and the number of drug candidates has been growing over the last decade. The SARM drug candidates S-22 and S-23 belong to one of the most advanced groups of androgen receptor modulators and are based on an arylpropionamide-derived core structure. Due to their anabolic effects, SARMs have been prohibited in elite sports and have been a subject of sports drug testing programmes since January 2008. Consequently, the structure of analytically useful urinary metabolites should be elucidated to provide targets for sensitive and retrospective analysis. In the present study, the phase-I and -II metabolism of S-22 and S-23 was simulated using hepatic human enzymes, and resulting metabolites were characterized by means of state-of-the-art mass spectrometric approaches employing high resolution/high accuracy Orbitrap mass spectrometry. Subsequently, the newly defined target compounds including the glucuronic acid conjugates of S-22 and S-23, their corresponding monohydroxylated and bishydroxylated analogs, as well as their B-ring depleted counterparts were implemented into an existing routine doping control procedure, which was examined for its specificity for the added substances. In order to obtain proof-of-concept data for authentic urine specimens, canine urine samples collected up to 72 h after oral administration of S-22 to dogs were analyzed using the established approach outlining the capability of the presented assay to detect the glucuronide of S-22 as well as the B-ring-depleted metabolite (M3) in all samples following therapeutic (31.4 µg/kg) dosing. Finally, M3 was chemically synthesized, characterized by nuclear magnetic resonance spectroscopy and high resolution/high accuracy mass spectrometry, and chosen as primary target for future doping control analyses.