Assessing limits of detection in qualitative methods: A simple implementation of logistic regression in a web-based R Shiny application environment and its potential in toxicology and doping control.

The estimation of limits of detection (LOD) for solely qualitative methods in analytical chemistry may prove challenging because all the approaches with which chemists are familiar require some type of numeric data input. The best model to describe the binary response in these methods (detected/not detected) is a logistic model; however, these models are not easily handled by most of the laboratories and generally demand expensive statistical software packages. In this work, the advantages of applying this approach are discussed and its implementation using commercial spreadsheet software is demonstrated. A free online application based on the R environment using shinyapps was developed and its application was validated and discussed with a dataset of 57 different target compounds analyzed in urine according to the requirements of the World Anti-Doping Agency (WADA). This tool allows free, extremely quick, and easy determinations of LOD in qualitative analyses as well as the determination of the probabilities of detection in any given concentration.

Variable Data Independent Acquisition and Data Mining Exploring Feature-Based Molecular Networking Analysis for Untargeted Screening of Synthetic Cannabinoids in Oral Fluid.

Novel psychoactive substances (NPS) are constantly emerging in the drug market, and synthetic cannabinoids (SCs) are included in this NPS family. Forensic laboratories often struggle with these continually emerging SCs, forcing them to develop an untargeted workflow to incorporate these psychoactive drugs in their procedures. Usually, forensic laboratories select analytical methods based on targeted mass spectrometry (MS) technologies for strictly tracking already known NPS. The appropriate way to tackle unknown substances is to develop pipelines for untargeted analysis that include LC-HRMS analytical methods and data analysis. Once established, this strategy would allow drug testing laboratories to be always one step ahead of the new trends concerning the "designer drugs" market. To address this challenge an untargeted workflow based on mass spectrometry data acquisition and data analysis was developed to detect SCs in oral fluid (OF) samples at a low concentration range. The samples were extracted by mixed-mode solid-phase extraction and analyzed by Liquid Chromatography - High-Resolution Mass Spectrometry (LC-HRMS). Tandem mass spectra (MS2) were recorded performing a variable isolation width across a mass range of all theoretical precursor ions (vDIA) after the chromatographic separation. After raw data processing with the MSDial software, the deconvoluted features were sent to GNPS for Feature-Based Molecular Networking (FBMN) construction for nontargeted data mining. The FBMN analysis created a unique integrated network for most of the SCs assessed in the OF at a low level (20 ng/mL). These results demonstrate the potential of an untargeted approach to detect different derivatives of SCs at trace levels for forensic applications.

Non-targeted acquisition strategy for screening doping compounds based on GC-EI-hybrid quadrupole-Orbitrap mass spectrometry: A focus on exogenous anabolic steroids.

This is a first look at a non-targeted screening method based on Orbitrap gas chromatography-mass spectrometry (GC-MS) technology for a large number of banned compounds in sports found in urine, including exogenous anabolic steroids, ß-agonists, narcotics, stimulants, hormone modulators, and diuretics. A simple sample preparation was processed in four steps: an enzymatic hydrolysis, liquid-liquid extraction, evaporation, and trimethylsilylation. All compounds were able to meet the World Anti-Doping Agency's sensitivity criteria with mass accuracies less than 1 ppm and with sufficient points across the peak by running the Orbitrap GC-MS in full-scan mode. In addition, we discuss our initial findings of using a full-scan selected ion monitoring-tandem mass spectrometry (SIM-MS/MS) approach as a way to obtain lower detection limits and reach desirable selectivity for some exogenous anabolic steroids.

Doping control analysis at the Rio 2016 Olympic and Paralympic Games.

This paper summarises the results obtained from the doping control analyses performed during the Summer XXXI Olympic Games (August 3-21, 2016) and the XV Paralympic Games (September 7-18, 2016). The analyses of all doping control samples were performed at the Brazilian Doping Control Laboratory (LBCD), a World Anti-Doping Agency (WADA)-accredited laboratory located in Rio de Janeiro, Brazil. A new facility at Rio de Janeiro Federal University (UFRJ) was built and fully operated by over 700 professionals, including Brazilian and international scientists, administrative staff, and volunteers. For the Olympic Games, 4913 samples were analysed. In 29 specimens, the presence of a prohibited substance was confirmed, resulting in adverse analytical findings (AAFs). For the Paralympic Games, 1687 samples were analysed, 12 of which were reported as AAFs. For both events, 82.8% of the samples were urine, and 17.2% were blood samples. In total, more than 31 000 analytical procedures were conducted. New WADA technical documents were fully implemented; consequently, state-of-the-art analytical toxicology instrumentation and strategies were applied during the Games, including different types of mass spectrometry (MS) analysers, peptide, and protein detection strategies, endogenous steroid profile measurements, and blood analysis. This enormous investment yielded one of the largest Olympic legacies in Brazil and South America. Copyright © 2017 John Wiley & Sons, Ltd.

Detection of new exemestane metabolites by liquid chromatography interfaced to electrospray-tandem mass spectrometry.

Exemestane is an irreversible aromatase inhibitor used for anticancer therapy. Unfortunately, this drug is also misused in sports to avoid some adverse effects caused by steroids administration. For this reason exemestane has been included in World Anti-Doping Agency prohibited list. Usually, doping control laboratories monitor prohibited substances through their metabolites, because parent compounds are readily metabolized. Thus metabolism studies of these substances are very important. Metabolism of exemestane in humans is not clearly reported and this drug is detected indirectly through analysis of its only known metabolite: 17ß-hydroxyexemestane using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and gas chromatography coupled to mass spectrometry (GC-MS). This drug is extensively metabolized to several unknown oxidized metabolites. For this purpose LC-MS/MS has been used to propose new urinary exemestane metabolites, mainly oxidized in C6-exomethylene and simultaneously reduced in 17-keto group. Urine samples from four volunteers obtained after administration of a 25mg dose of exemestane were analyzed separately by LC-MS/MS. Urine samples of each volunteer were hydrolyzed followed by liquid-liquid extraction and injected into a LC-MS/MS system. Three unreported metabolites were detected in all urine samples by LC-MS/MS. The postulated structures of the detected metabolites were based on molecular formulae composition obtained through high accuracy mass determination by liquid chromatography coupled to hybrid quadrupole-time of flight mass spectrometry (LC-QTOF MS) (all mass errors below 2ppm), electrospray (ESI) product ion spectra and chromatographic behavior.