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.

Exploring correlations between MS and NMR for compound identification using essential oils: A pilot study.

INTRODUCTION: In this era of 'omics' technology in natural products studies, the complementary aspects of mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques must be taken into consideration. The advantages of using both analytical platforms are reflected in a higher confidence of results especially when using replicated samples where correlation approaches can be used to statistically link results from MS to NMR. OBJECTIVES: Demonstrate the use of Statistical Total Correlation (STOCSY) for linking results from MS and NMR data to reach higher confidence in compound identification. METHODOLOGY: Essential oil samples of Melaleuca alternifolia and M. rhaphiophylla (Myrtaceae) were used as test objects. Aliquots of 10 samples were collected for GC-MS and NMR data acquisition [proton (1 H)-NMR, and carbon-13 (13 C)-NMR as well as two-dimensional (2D) heteronuclear single quantum correlation (HSQC), heteronuclear multiple-bond correlation (HMBC), and HSQC-total correlated spectroscopy (TOCSY) NMR]. The processed data was imported to Matlab where STOCSY was applied. RESULTS: STOCSY calculations led to the confirmation of the four main constituents of the sample-set. The identification of each was accomplished using; MS spectra, retention time comparison, 13 C-NMR data, and scalar correlations of the 2D NMR spectra. CONCLUSION: This study provides a pipeline for high confidence in compound identification using a set of essential oils samples as test objects for demonstration.

Proteomics in quality control: Whey protein-based supplements.

UNLABELLED: The growing consumption of nutritional supplements might represent a problem, given the concern about the quality of these supplements. One of the most used supplements is whey protein (WP); because of its popularity, it has been a target of adulteration with substitute products, such as cheaper proteins with lower biological value. To investigate this type of adulteration, this study used shotgun proteomics analyses by MS(E) (multiplexed, low- and high-collision energy, data-independent acquisition) of WP-based supplements. Seventeen WP-based supplement samples were evaluated. Chicken, maize, rice, potato, soybean, and wheat proteins were considered as probable sources of bovine whey adulteration. Collectively, 523 proteins were identified across all 16 samples and replicates, with 94% of peptides inside a normal distribution within 10ppm of maximum error. In 10 of the 16 samples analyzed, only proteins from bovine whey could be detected, while in the other samples several other protein sources were detected in high concentrations, especially soybean, wheat, and rice. These results point out a probable adulteration and/or sample contamination during manufacturing that could only be detected using this proteomic approach. SIGNIFICANCE: The present work shows how shotgun proteomics can be used to provide reliable answers in quality control matters, especially focusing on Whey Protein nutritional supplements which are a very popular subject in food and nutrition. In order to achieve an appropriate methodology, careful evaluation was performed applying extremely rigorous quality criteria, established for the proteomic analysis. These criteria and the methodological approach used in this work might serve as a guide for other authors seeking to use proteomics in quality control.

Salbutamol extraction from urine and its stability in different solutions: identification of methylation products and validation of a quantitative analytical method.

Salbutamol is commonly used in asthma treatment, being considered a short-effect bronchodilator. This drug poses special interest in certain fields of chemical analysis, such as food, clinical and doping analyses, in which it needs to be analyzed with quantitative precision and accuracy. Salbutamol, however, is known to degrade under certain conditions and this is critical if quantitative results must be generated. The present work aimed to investigate salbutamol extraction from urine samples, to determine whether salbutamol is unstable in other solvents as well as in urine samples, to elucidate the structures of the possible degradation products and to validate an analytical method using the extraction procedure evaluated. Stability investigations were performed in urine at different pH values, in methanol and acetone at different temperatures. Semi-preparative liquid chromatography was performed for the isolation of degradation products, and gas chromatography coupled to mass spectrometry as well as nuclear magnetic resonance were used for identification. Three unreported methylation products were detected in methanolic solutions and had their structures elucidated. Urine samples showed a reduction in salbutamol concentration of up to 25.8% after 5 weeks. These results show that special care must be taken regarding salbutamol quantitative analyses, since degradation either in standard solutions or in urine could lead to incorrect values.

Detection of designer steroid methylstenbolone in "nutritional supplement" using gas chromatography and tandem mass spectrometry: elucidation of its urinary metabolites.

The use of "nutritional supplements" containing unapproved substances has become a regular practice in amateur and professional athletes. This represents a dangerous habit for their health once no data about toxicological or pharmacological effects of these supplements are available. Most of them are freely commercialized online and any person can buy them without medical surveillance. Usually, the steroids intentionally added to the "nutritional supplements" are testosterone analogues with some structural modifications. In this study, the analyzed product was bought online and a new anabolic steroid known as methylstenbolone (2,17α-dimethyl-17ß-hydroxy-5α-androst-1-en-3-one) was detected, as described on label. Generally, anabolic steroids are extensively metabolized, thus in-depth knowledge of their metabolism is mandatory for doping control purposes. For this reason, a human excretion study was carried out with four volunteers after a single oral dose to determine the urinary metabolites of the steroid. Urine samples were submitted to enzymatic hydrolysis of glucuconjugated metabolites followed by liquid-liquid extraction and analysis of the trimethylsilyl derivatives by gas chromatography coupled to tandem mass spectrometry. Mass spectrometric data allowed the proposal of two plausible metabolites: 2,17α-dimethyl-16ξ,17ß-dihydroxy-5α-androst-1-en-3-one (S1), 2,17α-dimethyl-3α,16ξ,17ß-trihydroxy-5α-androst-1-ene (S2). Their electron impact mass spectra are compatible with 16-hydroxylated steroids O-TMS derivatives presenting diagnostic ions such as m/z 231 and m/z 218. These metabolites were detectable after one week post administration while unchanged methylstenbolone was only detectable in a brief period of 45 h.

Detection of new urinary exemestane metabolites by gas chromatography coupled to mass spectrometry.

Exemestane is an aromatase enzyme complex inhibitor. Its metabolism in humans is not fully described and there is only one known metabolite: 17ß-hydroxyexemestane. In this work, excretion studies were performed with four volunteers aiming at the detection of new exemestane metabolites in human urine by gas chromatography coupled to mass spectrometry (GC-MS) after enzymatic hydrolysis and liquid-liquid extraction. Urine samples collected from four volunteers were analyzed separately. The targets of the study were mainly the 6-exomethylene oxidized metabolites. Two unreported metabolites were identified in both free and glucuconjugated urine fractions from all four volunteers, both of them were the result of the 6-exomethylene moiety oxidation: 6ξ-hydroxy-6ξ-hydroxymethylandrosta-1,4-diene-3,17-dione (metabolite 1) and 6ξ-hydroxyandrosta-1,4-diene-3,17-dione (metabolite 2). Furthermore, only in glucoconjugated fractions from all volunteers, one metabolite arising from the A-ring reduction was identified as well, 3ξ-hydroxy-5ξ-androst-1-ene-6-methylene-17-one (metabolite 3). The molecular formulae of all these metabolites were ascertained by the determination of exact masses using gas chromatography coupled to high resolution mass spectrometry (GC-HRMS). Moreover, all metabolites were confirmed using an alternative derivatization with methoxyamine and MSTFA/TMS-imidazole.