María Martínez Galera

Detection of unintended stress effects based on a metabonomic study in tomato fruits after treatment with carbofuran pesticide. Capabilities of MCR-ALS applied to LC-MS three-way data arrays.

A chemometric strategy based on multivariate curve resolution and alternating least-squares (MCR-ALS) applied to LC-MS three-way data arrays has been developed to perform a metabonomic study in tomato (Lycopersicon esculentum) fruits (cultivar Rambo) following treatment with carbofuran. This methodology has proved to be adequate for the detection of unintended stress effects due to the previous treatment with this pesticide. MCR-ALS was performed on augmented matrices built with the LC-MS three-way data obtained from treated and nontreated samples through the sampling time. The strategy allowed us to obtain the concentration and spectra profiles of the main components (previously estimated with the SVD algorithm) from samples treated with pesticide as well as from blank samples, showing how they vary with time after plants treatment with the pesticide. In addition, a simple resolved mass spectrum was obtained corresponding to the peaks of a particular component in all matrices, thus avoiding ambiguity in the compound identity assignment. Different time profiles were found for some metabolites in treated and nontreated samples, which demonstrate that the presence of pesticide causes changes thorough time in the behavior of certain endogenous tomato metabolites as a result of physiological stress.

Multivariate curve resolution modeling of liquid chromatography–mass spectrometry data in a comparative study of the different endogenous metabolites behavior in two tomato cultivars treated with carbofuran pesticide

A metabonomic study based on the application of multivariate curve resolution and alternating least squares (MCR-ALS) to three-way data sets obtained by liquid chromatography coupled to mass spectrometry detection (LC-MS) was carried out for Rambo and Raf tomato cultivars treated with carbofuran pesticide. Samples were picked up during a 21 days period after treatment and analyzed by LC-MS in scan mode, along with the corresponding blank samples. Then, MCR-ALS was applied to the three-way data sets using column wise augmented matrices, and the evolutionary profiles as a function of the time after treatment were estimated for the metabolites present in both cultivars, as well as their corresponding pure spectra estimations. A comparative study using those estimations showed that some of these metabolites followed different behavior for the different cultivars after treatment. Since all treated and untreated Rambo and Raf samples were picked up according to the same sampling protocol and in a similar state of maturation, any difference in the behavior between profiles can be interpreted as an effect due to the presence of pesticide and to the kind of cultivar. Based on this hypothesis, several PLS-DA approaches were tested to check if it would be possible to classify samples by using the metabolites MCR estimations. Results showed that PLS-DA models for classification of treated or non-treated (blank) samples were the best ones obtained (98.44% of correct classifications for the validation set), which supports the stress effects related to carbofuran treatment. In addition, excellent discrimination among the four groups could be attained (89.06% of correct classifications for the validation set).

Determination of (fluoro)quinolones in environmental water using online preconcentration with column switching linked to large sample volumes and fluorescence detection

An analytical method based on online enrichment using coupled-column liquid chromatography with fluorescence detection has been developed to determine marbofloxacin, ciprofloxacin, danofloxacin, enrofloxacin, norfloxacin, lomefloxacin, oxolinic acid, and nalidixic acid at trace levels in surface water. The sample containing the pharmaceuticals was pumped through a short C18 column in such a way that the analytes were retained on the column, whereas polar interferences, eluting at the first of the chromatogram, were discarded to waste. Then, the analytes were transferred by the chromatographic mobile phase to a second C18 analytical column, where they were separated following a conventional chromatography. The optimized approach allowed to preconcentrate 15 mL of sample volume adjusted at acid pH with phosphoric acid and modified with 5% of methanol, at a flow rate of 1.5 mL/min in 10 min. R(2) values were between 0.994 and 0.998, detection and quantitation limits ranged between 0.001 and 0.080 and between 0.002 and 0.100 μg/L, respectively, and the interday precision was below 9.8%. Recoveries in three different surface water samples, spiked at concentration levels between 0.002 and 0.500 μg/L (n = 3 for each spiking level), ranged from 82.1 to 125.8% with the relative standard deviation lower than 12%.

Enhanced high-performance liquid chromatography method for the determination of retinoic acid in plasma. Development, optimization and validation

When determining endogenous compounds in biological samples, the lack of blank or analyte-free matrix samples involves the use of alternative strategies for calibration and quantitation. This article deals with the development, optimization and validation of a high performance liquid chromatography method for the determination of retinoic acid in plasma, obtaining at the same time information about its isomers, taking into account the basal concentration of these endobiotica. An experimental design was used for the optimization of three variables: mobile phase composition, flow rate and column temperature through a central composite design. Four responses were selected for optimization purposes (area under the peaks, quantity of peaks, analysis time and resolution between the first principal peak and the following one). The optimum conditions resulted in a mobile phase consisting of methanol 83.4% (v/v), acetonitrile 0.6% (v/v) and acid aqueous solution 16.0% (v/v); flow rate of 0.68 mL min(-1) and an column temperature of 37.10 °C. Detection was performed at 350 nm by a diode array detector. The method was validated following a holistic approach that included not only the classical parameters related to method performance but also the robustness and the expected proportion of acceptable results lying inside predefined acceptability intervals, i.e., the uncertainty of measurements. The method validation results indicated a high selectivity and good precision characteristics that were studied at four concentration levels, with RSD less than 5.0% for retinoic acid (less than 7.5% for the LOQ concentration level), in intra and inter-assay precision studies. Linearity was proved for a range from 0.00489 to 15.109 ng mL(-1) of retinoic acid and the recovery, which was studied at four different fortification levels in phuman plasma samples, varied from 99.5% to 106.5% for retinoic acid. The applicability of the method was demonstrated by determining retinoic acid and obtaining information about its isomers in human and frog plasma samples from different origins.

Simple, rapid, and sensitive determination of beta-blockers in environmental water using dispersive liquid–liquid microextraction followed by liquid chromatography with fluorescence detection

A novel method, dispersive liquid-liquid microextraction combined with liquid chromatography-fluorescence detection is proposed for the determination of three beta-blockers (metoprolol, bisoprolol, and betaxolol) in ground water, river water, and bottled mineral water. Some important parameters, such as the kind and volume of extraction and dispersive solvents, extraction time, pH, and salt effect were investigated and optimized. In the method, a suitable mixture of extraction solvent (60 μL carbon tetrachloride) and dispersive solvent (1 mL acetonitrile) were injected into the aqueous samples (5.00 mL) and the cloudy solution was observed. After centrifugation, the enriched analytes in the bottom CCl(4) phase were determined by liquid chromatography with fluorescence detection. Under the optimum conditions, the enrichment factors (EFs) for metoprolol, bisoprolol, and betaxolol were 180, 190, and 182, and the limits of detection (LODs) were 1.8, 1.4, and 1.0 ng L(-1) , respectively. A good linear relationship between the peak area and the concentration of analytes was obtained in the range of 3-150 ng L(-1) . The relative standard deviations (RSDs) for the extraction of 10 ng L(-1) of beta-blockers were in the range of 4.6-5.7% (n = 5). Compared with other methods, dispersive liquid-liquid microextraction is a very simple, rapid, sensitive (low limit of detection), and economical (only 1.06 mL volume of organic solvent) method, which is in compliance with the requirements of green analytical methodologies.

Analysis of β‐blockers in groundwater using large‐volume injection coupled‐column reversed‐phase liquid chromatography with fluorescence detection and liquid chromatography time‐of‐flight mass spectrometry

Atenolol, nadolol, metoprolol, bisoprolol and betaxolol were simultaneously determined in groundwater samples by large-volume injection coupled-column reversed-phase liquid chromatography with fluorescence detection (LVI-LC-LC-FD) and liquid chromatography-time-of-flight mass spectrometry (LC-TOF-MS). The LVI-LC-LC-FD method combines analyte isolation, preconcentration and determination into a single step. Significant reductions in costs for sample pre-treatment (solvent and solid phases for clean up) and method development times are also achieved. Using LC-TOF-MS, accurate mass measurements within 3 ppm error were obtained for all of the β-blockers studied. Empirical formula information can be obtained by this method, allowing the unequivocal identification of the target compounds in the samples. To increase the sensitivity, a solid-phase extraction step with Oasis MCX cartridge was carried out yielding recoveries of 79-114% (n=5) with RSD 2-7% for the LC-TOF-MS method. SPE gives a high purification of β-blockers compared with the existing methods. A 100% methanol wash was allowed for these compounds with no loss of analytes. Limit of quantification was 1-7 ng/L for LVI-LC-LC-FD and 0.25-5 ng/L for LC-TOF-MS. As a result of selective extraction and effective removal of coextractives, no matrix effect was observed in LVI-LC-LC-FD and LC-TOF-MS analyses. The methods were applied to detect and quantify β-blockers in groundwater samples of Almería (Spain).

Second-order advantage achieved by modeling excitation–emission fluorescence matrices affected by inner filter effects using a strategy which combines standardization and calibration: Reducing experimental and increasing analytical sensitivity

A methodology based on second-order data (excitation emission matrices) modeling with one of most popular algorithms presenting the second-order advantage, parallel factor analysis (PARAFAC), combined with transference of calibration is proposed to predict the analyte concentration when significant inner filter effects occur, even in the presence of unexpected sample components. The quantitation of phenylephrine hydrochloride (PHE) in water samples (concentrations ranged between 250 and 750 ng mL(-1)) in the presence of ibuprofen, acetyl salicylic acid and paracetamol (which produce inner filter effect across the useful wavelength range) was achieved. The strategy allows reducing the experimental work and increasing the analytical sensitivity in the determination of the analyte of interest in the presence of unexpected compounds and matrix effect caused by inner filter, avoiding the preparation of a large number of solutions and maintaining acceptable figures of merit. Recoveries between 97 and 102% for validation and real spiked water samples, respectively, and a relative prediction error of 5% were achieved. Results were compared with those obtained after the application of the classical standard addition method combined with PARAFAC, carrying out five additions to each sample, in triplicate. The presented methodology constitutes a simple and low-cost method for the determination of PHE in water samples with a considerable reduction in standard handling and time. This methodology can be extended to other systems presenting matrix effect and, consequently, can become in a useful tool to know the amount of pharmaceuticals in the aquatic environment and to evaluate the effect of conventional wastewater treatment plants in the elimination of pharmaceutical compounds.

Evaluation of supercritical fluid chromatography coupled to tandem mass spectrometry for pesticide residues in food

Supercritical fluid chromatography coupled to triple quadrupole mass spectrometry has been evaluated for pesticide residues in food. In order to check its advantages and limitations it was developed a method to identify and quantify 164 pesticides in three different matrices (tomato, orange and leek). A carbon dioxide gradient with methanol (containing 1 mM ammonium formate) was used allowing a flow rate of 1.5 mL/min that made the total run time of 12 min without any problem of overpressure. Addition of a post column flow 150 μL/min of Methanol with ammonium formate/formic acid was necessary to improve the ionization. The matrix effect study revealed that the percentages of pesticides with irrelevant matrix effect (suppression lower than 20%) was 99% in tomato, 87% in orange and 62% in leek, whereas significant suppression (higher than 50%) was not found in tomato and only 1% of the compounds in orange and 3% in leek.These results compare favorably with that typically obtained in LC-MS/MS. The absence of water in the mobile phase, also provided some important advantages regarding LC-MS/MS as (i) higher retention of polar compounds in the column, which elute with high sensitivity and good peak shape and (ii) a general increase of the sensitivity of the analysis, consequence of the high ionization and ion extraction efficiency. Pesticides evaluated were identified following the SANTE/11813/2017. At the spiking concentration of 5 μg/kg, 98% of the pesticides were identified in tomato, 98% in orange and 94% in leek, whereas for the concentration of 10 μg/kg all the compounds were identified in tomato and only spiromesifen was not identified in orange and leek. At the concentration of 20 μg/kg, spiromesifen was also identified in these two matrices. The linearity and reproducibility of the method were evaluated with results which guarantee high quality in the analytical measurements. Even though only 2 μL of final extract were injected, the sensitivity of the SFC method was enough to achieve stringent LOQs.Real samples, including 6 different fruits and vegetables, were analyzed by the SFC-MS/MS proposed method, the results being similar to those obtained by LC-MS/MS. The method was also applied to a proficiency test of fipronil in eggs with good results in all the cases. Carbon dioxide as mobile phase with methanol as modifier can represent a good alternative to LC-MS/MS with reduction of matrix effects and shorter run times.

Trace analysis of herbicides in wastewaters by a dispersive liquid–liquid microextraction approach and liquid chromatography with quadrupole linear ion trap mass spectrometry: Evaluation of green parameters

An analytical method for determining phenylureas (monuron, isoproturon, diuron, linuron and neburon) and propanil herbicides in wastewater has been developed and validated, and the most significant parameters were compared with the corresponding ones found in the literature, thus showing the method performance. The method involves pre-concentration by a simple, rapid, sensitive and low environmental toxicity temperature-controlled ionic liquid dispersive liquid-liquid microextraction procedure. The herbicides were identified and determined by liquid chromatography with a hybrid triple quadrupole linear ion trap mass spectrometer. Data acquisition in selected-reaction monitoring mode allowed the simultaneous identification and quantification of the analytes using two transitions. The information dependent acquisition scan was performed to carry out the identification of those analytes whose second transition was present at low intensity, also providing extra confirmation for the other analytes. Limits of quantification were in the range 1.0-5.0 ng/L. Good recoveries (95-103%) were obtained for the extraction of the target analytes in wastewater samples. The methodology developed was applied to analyze effluent wastewater samples from a wastewater treatment plant located in an agricultural zone of Almería (Spain) and the results indicated the presence of diuron at mean concentration levels of 73.5 ng/L.

Analysis and evaluation of (neuro)peptides in honey bees exposed to pesticides in field conditions

During the last years, declines in honey bee colonies are being registered worldwide. Cholinergic pesticides and their extensive use have been correlated to the decline of pollinators and there is evidence that pesticides act as neuroendocrine disruptors affecting the metabolism of neuropeptides. However, there is a big absence of studies with quantitative results correlating the effect of pesticide exposure with changes on neuropeptides insects, and most of them are conducted under laboratory conditions, typically with individual active ingredients. In this study, we present an analytical workflow to evaluate pesticide effects on honey bees through the analysis of (neuro)peptides. The workflow consists of a rapid extraction method and liquid chromatography with triple quadrupole for preselected neuropeptides. For non-target analysis, high resolution mass spectrometry, multivariate analysis and automatic identification of discriminated peptides using a specific software and protein sequence databases. The analytical method was applied to the analysis of target and non-target (neuro)peptides in honey bees with low and high content of a wide range of pesticides to which have been exposed in field conditions. Our findings show that the identification frequency of target neuropeptides decreases significantly in honey bees with high concentration of pesticides (pesticide concentrations ≥ 500 μg kg-1) in comparison with the honey bees with low content of pesticides (pesticide concentrations ≤ 20 μg kg-1). Moreover, the principal component analysis in non-target search shows a clear distinction between peptide concentration in honey bees with high level of pesticides and honey bees with low level. The use of high resolution mass spectrometry has allowed the identification of 25 non-redundant peptides responsible for discrimination between the two groups, derived from 18 precursor proteins.