Development and validation of a rapid method for microcystins in fish and comparing LC-MS/MS results with ELISA

Microcystins (MCs) are the most common cyanotoxins found worldwide in freshwater, brackish, and marine environments. The rapid and accurate analysis of MCs and nodularin (Nod-R) in fish tissue is important for determining occurrence, following trends, and monitoring exposure for risk assessment and other purposes. The aim of this study was to develop a streamlined and reliable sample preparation method for eight MCs (MC-RR, MC-YR, MC-LR, MC-WR, MC-LA, MC-LY, MC-LW, and MC-LF) and Nod-R in fish, and conduct a validation of the new method using liquid chromatography–tandem mass spectrometry (LC-MS/MS) for analysis and compare the results with a commercial enzyme-linked immunosorbent assay (ELISA) kit. Different sample preparation methods were compared, and a simple extraction protocol with acidified acetonitrile/water (3:1) followed by hexane partitioning cleanup was found to be most effective. Thorough validation of the final method was conducted, and 90–115% recoveries were achieved for all analytes except for MC-RR, which gave 130% average recovery (isotopically labeled internal standards were unavailable to correct for possible biases). The use of electrospray ionization in the negative mode gave few interferences and minimal matrix effects in the LC-MS/MS analysis overall. Precision was typically 10–20% RSD among multiple days in experiments, detection limits were <10 ng/g in the fish tissue (catfish, basa, and swai filets), and no false-positives or false-negatives occurred in blind analyses of many spiked samples. The ELISA was unable to distinguish between MCs but was found to correctly assess the presence or absence of MCs and Nod-R in the blind-fortified fish tissues. The capability of these approaches to measure covalently bound MCs was not assessed.     

Trace analysis of pesticides in paddy field water by direct injection using liquid chromatography-quadrupole-linear ion trap-mass spectrometry

A multiresidue method was developed for the quantification and confirmation of 70 pesticides in paddy field water. After its filtration, water was injected directly in a liquid chromatograph coupled to a hybrid triple quadrupole-linear ion trap-mass spectrometer (QqLIT). The list of target analytes included organophosphates, phenylureas, sulfonylureas, carbamates, conazoles, imidazolinones and others compounds widely used in different countries where rice is cropped. Detection and quantification limits achieved were in the range from 0.4 to 80 ng L(-1) and from 2 to 150 ng L(-1), respectively. Correlation coefficients for the calibration curves in the range 0.1-50 μg L(-1) were higher than 0.99 except for diazinon (0.1-25 μg L(-1)). Only 9 pesticides presented more than 20% of signal suppression/enhancement, no matrix effect was observed in the studied conditions for the rest of the target pesticides. The method developed was used to investigate the occurrence of pesticides in 59 water samples collected in paddy fields located in Spain and Uruguay. The study shows the presence of bensulfuron methyl, tricyclazole, carbendazim, imidacloprid, tebuconazole and quinclorac in a concentration range from 0.08 to 7.20 μg L(-1).     

On a new semi‐empirical electrotopological index for QSRR models

A new semi‐empirical electrotopological index, I_SET, for quantitative structure–retention relationships (QSRR) models was developed based on the refinement of the previously published semi‐empirical topological index, I_ET. We demonstrate that the values of C_i fragments that were firstly attributed from the experimental chromatographic retention and theoretical deductions have an excellent relationship with the net atomic charge of the carbon atoms. Thus, the values attributed to the vertices in the hydrogen‐suppressed graph of carbon atoms (C_i) are calculated from the correlation of the net atomic charge in each carbon atom, which is obtained from quantum chemical semi‐empirical calculations, and the C_i fragments for primary, secondary, tertiary and quaternary carbon atoms (1.0, 0.9, 0.8 and 0.7, respectively) obtained from the experimental values. This shows that I_ET encoded this quantum physical reality and that it is possible to calculate a new I_SET (the semi‐empirical electrotopological index) through the net atomic charge values obtained from a Mulliken population analysis using the semi‐empirical AM1 method and their correlation with the values attributed to the different types of carbon atoms. This demonstrates that the I_SET encodes information on the charge distribution of the solute on which dispersive and electrostatic interactions between the solute (alkanes and alkenes) and the stationary phase strongly depend. Thus, this new method can be considered as an initial step towards forthcoming QSRR/QSAR studies. Copyright © 2008 John Wiley & Sons, Ltd.     

Semi-empirical topological index: development of QSPR/QSRR and optimization for alkylbenzenes

The semi-empirical topological index, I(ET), was developed and optimized to describe the chromatographic retention of alkylbenzenes on the squalane stationary phase. The simple linear regression between the chromatographic retention and the proposed index, for 122 alkylbenzenes studied, is of good quality (determination coefficient, r(2)=0.9996, standard deviation, S.D.=5.5, and leave-one-out cross-validation correlation coefficient, r(CV)(2)=0.9996). The predictive ability of I(ET) was also verified for stationary phases with two different polarities (SE-30 and Carbowax 20 M), and good results were obtained, especially for the stationary phase with low polarity, showing that the specific molecular interactions occur on highly polar phases. The I(ET) was applied to construct quantitative structure-property relationship (QSPR) models for representative properties such as boiling point, Bp(degrees C), octanol/water partition coefficient, log P, van der Waals volume (V(W)) and molar refractivity (R(M)). Satisfactory quality QSPR models were obtained with Bp, V(W) and R(M) showing that the molecular size and dispersive forces are dominating factors with respect to the chromatographic retention.