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This work focuses on the influence of the selected LC-HRMS platform on the final annotated compounds in non-targeted metabolomics. Two platforms that differed in columns, mobile phases, gradients, chromatographs, mass spectrometers (Orbitrap [Platform#1] and Q-TOF [Platform#2]), data processing and marker selection protocols were compared. A total of 42 wines samples from three different protected denomination of origin (PDO) were analyzed. At the feature level, good (O)PLS-DA models were obtained for both platforms (Q(2)[Platform#1]=0.89, 0.83 and 0.72; Q(2)[Platform#2]=0.86, 0.86 and 0.77 for Penedes, Ribera del Duero and Rioja wines respectively) with 100% correctly classified samples in all cases. At the annotated metabolite level, platforms proposed 9 and 8 annotated metabolites respectively which were identified by matching standards or the MS/MS spectra of the compounds. At this stage, there was no coincidence among platforms regarding the suggested metabolites. When screened on the raw data, 6 and 5 of these compounds were detected on the other platform with a similar trend. Some of the detected metabolites showed complimentary information when integrated on biological pathways. Through the use of some examples at the annotated metabolite level, possible explanations of this initial divergence on the results are presented. This work shows the complications that may arise on the comparison of non-targeted metabolomics platforms even when metabolite focused approaches are used in the identification., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The modelling and prediction of reversed-phase chromatographic retention time (tR) under gradient elution conditions for 166 pharmaceuticals in wastewater extracts is presented using artificial neural networks for the first time. Radial basis function, multilayer perceptron and generalised regression neural networks were investigated and a comparison of their predictive ability for model solutions discussed. For real world application, the effect of matrix complexity on tR measurements is presented. Measured tR for some compounds in influent wastewater varied by >1min in comparison to tR in model solutions. Similarly, matrix impact on artificial neural network predictive ability was addressed towards developing a more robust approach for routine screening applications. Overall, the best neural network had a predictive accuracy of <1.3min at the 75th percentile of all measured tR data in wastewater samples (<10% of the total runtime). Coefficients of determination for 30 blind test compounds in wastewater matrices lay at or above R(2)=0.92. Finally, the model was evaluated for application to the semi-targeted identification of pharmaceutical residues during a weeklong wastewater sampling campaign. The model successfully identified native compounds at a rate of 83±4% and 73±5% in influent and effluent extracts, respectively. The use of an HRMS database and the optimised ANN model was also applied to shortlisting of 37 additional compounds in wastewater. Ultimately, this research will potentially enable faster identification of emerging contaminants in the environment through more efficient post-acquisition data mining., (Copyright © 2015 Elsevier B.V. All rights reserved.)

In this work, an ultra high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) methodology is proposed for the multi-class multi-residue screening of banned and unauthorized veterinary drugs in bovine urine, using an Orbitrap Exactive™ analyzer working at a resolving power of 50,000 FWHM in full scan, both in positive and negative mode. The method currently covers 87 analytes belonging to different families such as steroid hormones, β-agonists, resorcylic acid lactones (RAL), stilbens, tranquillizers, nitroimidazoles, corticosteroids, NSAIDs, amphenicoles, thyreostatics and other substances such as dapsone. A database including the elemental composition, the polarity of acquisition, retention time and expected adducts was built for the targeted analysis, and a high mass accuracy (<5 ppm) was set as one of the identification criteria. After comparing different sample preparation procedures, QuEChERS was selected as the most appropriate methodology. An efficient separation of analytes was achieved using ultra high performance liquid chromatography with a column packed with sub-2 μm particles. The performance of the method has been evaluated in accordance with the EU guidelines for the validation of screening methods for the analysis of veterinary drugs residues. The screening target concentrations were established between 0.2 μg/l and 20 μg/l, demonstrating the usefulness of UHPLC-HRMS as an ideal tool for compliance monitoring in regulatory laboratories., (Copyright © 2012 Elsevier B.V. All rights reserved.)

There is an increasing need for applications in food and environmental areas able to cope with a large number of analytes in very complex matrices. The new analytical procedures demand sensitivity, robustness and high resolution within an acceptable analysis time. The purpose of this review is to describe new trends based on fast liquid chromatography applied to the food and environmental analysis. It includes different column technologies, such as monolithic, sub-2 μm, porous shell, as well as different stationary phases such as reversed phase (C8 and C18), hydrophilic interaction liquid chromatography (HILIC) and fluorinated columns. Additionally, recent sample extraction and clean-up methodologies applied to reduce sample manipulation and total analysis time in food and environmental analysis--QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe), on line solid phase extraction coupled to ultrahigh pressure liquid chromatography (on line SPE-UHPLC), turbulent flow chromatography (TFC) and molecularly imprinted polymers (MIPs), were also addressed. The advantages and drawbacks of these methodologies applied to the fast and sensitive analyses of food and environmental samples are going to be discussed., (Copyright © 2011 Elsevier B.V. All rights reserved.)

The psychoactive properties of N,N-dimethyltryptamine (DMT) are known to induce altered states of consciousness in humans. These properties attract great interest from clinical, neuroscientific, clandestine and forensic communities. The Breath of Hope Synthesis was reported on an internet website as a convenient two-step methodology for the preparation of DMT. The analytical characterisation of the first stage was the subject of previous publications by the authors and involved the thermal decarboxylation of tryptophan and the formation of tryptamine. The present study reports on the characterisation of the second step of this procedure which was based on the methylation of tryptamine. This employed methyl iodide and benzyltriethylammonium chloride/sodium hydroxide as a phase transfer catalyst. The reaction product was characterised by liquid chromatography/electrospray ionisation tandem mass spectrometry and orthogonal acceleration time-of-flight mass spectrometry. Quantitative evaluation was carried out in positive multiple reaction monitoring mode (MRM), which included synthesis of the identified reaction products. MRM screening of the product did not lead to the detection of DMT. Instead, 11.1% tryptamine starting material, 21.0% N,N,N-trimethyltryptammonium iodide (TMT) and 47.4% 1-N-methyl-TMT were detected. A 0.5% trace of the monomethylated N-methyltryptamine was also detected. This study demonstrated the impact on product purity of doubtful synthetic methodologies discussed on the internet.

A number of N,N-dialkylated tryptamines show psychoactive properties in man which resulted in a renewed interest in psychopharmacological research. Attempts to manufacture these derivatives are increasing within a clandestine environment, where literature procedures are adapted and information is exchanged on the Internet. One such example is based on the thermolytic decarboxylation of tryptophan to tryptamine as the precursor to psychoactive derivatives. This procedure was proposed to make use of household solvents such as turpentine substitute and white spirit to facilitate decarboxylation. Discussions on websites also suggested the catalytic use of natural oils in order to accelerate these reactions. In this research, the analytical characterization of this preparation procedure was carried out using gas chromatography-ion trap single and tandem stage mass spectrometry in electron and chemical ionization mode that led to the identification of previously unreported 1-mono and 1,1-disubstituted tetrahydro-beta-carboline (THBCs) by-products. The tryptamine product and several THBC by-products were determined quantitatively and a "fingerprint" analysis of the crude products allowed for the differentiation between the essential oil catalysts involved as indicated by the presence of tetrahydro-beta-carbolines and their imine intermediates.