Liquid chromatography-tandem mass spectrometric analysis and regulatory issues of polar pesticides in natural and treated waters

Pesticides are among the most detected contaminants in the aquatic environment. This is mainly due to their use in agriculture and their physico-chemical properties that enable transportation and a persistent or pseudo-persistent existence in the water media. Several directives and guidelines set maximum levels of pesticides in water in order to protect the human and environmental health. A brief discussion of the existing directives and guidelines concerning pesticides in water is presented, e.g., the new regulatory framework for the Registration, Evaluation and Authorisation of Chemicals (REACH), and the Directive 91/414/EEC concerning the placing of plant protection products on the market. Up-to-date analytical tools to support the REACH program are of prime importance to ensure its complete implementation. Since liquid chromatography (LC) coupled to mass spectrometry (MS) is considered the most appropriate technique for determination of most modern pesticides in environmental waters, the most recent developments and applications in this field are discussed in detail in this review.     

Consensus QSAR models estimating acute toxicity to aquatic organisms from different trophic levels: algae,Daphnia and fish

ABSTRACT

We report new consensus models estimating acute toxicity for algae, Daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSE_ext = 0.56–0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/ColorAtom utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracy and data coverage.

Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending the applicability domain and relevance for application in an industrial context. Generated models and collected public data are made freely available.     

Optimisation of pressurised liquid extraction by experimental design for quantification of pesticides and alkyl phenols in sludge,suspended materials and atmospheric fallout by liquid chromatography–tandem mass spectrometry

The study proposes an analytical method to quantify 10 alkylphenols and 12 pesticides at ultra-trace levels by liquid chromatography in reverse mode coupled to positive electrospray ionisation–tandem mass spectrometry. The extraction procedure from environmental solids was optimised by pressurised liquid extraction using acetonitrile:isopropanol (1:1, v/v). The influence of several extraction experimental factors, temperature, pressure, duration and number of cycles, related to the PLE was investigated by an original and efficient chemometric approach. The optimised extraction method (80 °C, 40 bar, 10 min, 1 cycle) exhibited recoveries between 67 and 127% with RSD mostly under 13%. The whole method was applied to real samples: sludge, suspended materials, atmospheric fallouts and roof deposit. Pollutant levels were between 1 μg kg⁻¹ and 5.9 mg kg⁻¹.     

ToxRead: A tool to assist in read across and its use to assess mutagenicity of chemicals

Life sciences, and toxicology in particular, are heavily impacted by the development of methods for data collection and data analysis; they are moving from an analytical approach to a modelling approach. The scarce availability of experimental data is a known bottleneck in assessing the properties of new chemicals. Even when a model is available, the resulting predictions have to be assessed by close scrutiny of the chemicals and the biological properties of the compounds concerned. To avoid unnecessary testing, a read across strategy is often suggested and used. In this paper we discuss how to improve and standardize read across activity using ad hoc visualization and data search methods which use similarity measures and fragment search to organize in a chart a picture of all the relevant information that the expert needs to make an assessment. We show in particular how to apply our system to the case of mutagenicity.     

Characterization of Polypropylene in Dibutoxymethane by High-Temperature Gel Permeation Chromatography with Triple Detection

This study presents the possibility of replacing the 1,2,4-trichlorobenzene (TCB) recommended by ASTM D 6474 for the analysis by gel permeation chromatography (GPC) of polypropylenes with dibutoxymethane (DBM, butylal), a halogen-free and less toxic solvent. The molecular weight distributions as well as the K and alpha parameters of the Mark-Houwink-Sakurada equation were measured for different types of commercial polypropylene samples solubilized in TCB and DBM, using a GPC system with triple detection (light scattering, differential refractive index, and viscometer). For the analyzed resins, covering typical applications of polypropylene, the GPC method in DBM provided results similar to those obtained in TCB.     

Validation and extension of a similarity-based approach for prediction of acute aquatic toxicity towards Daphnia magna

Quantitative structure–activity relationship (QSAR) models for predicting acute toxicity to Daphnia magna are often associated with poor performances, urging the need for improvement to meet REACH requirements. The aim of this study was to evaluate the accuracy, stability and reliability of a previously published QSAR model by means of further external validation and to optimize its performance by means of extension to new data as well as a consensus approach. The previously published model was validated with a large set of new molecules and then compared with ChemProp model, from which most of the validation data were taken. Results showed better performance of the proposed model in terms of accuracy and percentage of molecules outside the applicability domain. The model was re-calibrated on all the available data to confirm the efficacy of the similarity-based approach. The extended dataset was also used to develop a novel model based on the same similarity approach but using binary fingerprints to describe the chemical structures. The fingerprint-based model gave lower regression statistics, but also less unpredicted compounds. Eventually, consensus modelling was successfully used to enhance the accuracy of the predictions and to halve the percentage of molecules outside the applicability domain.     

An evaluation of experimental design in QSAR modelling utilizing the k‐medoid clustering

A reliable selection of a representative subset of chemical compounds has been reported to be crucial for numerous tasks in computational chemistry and chemoinformatics. We investigated the usability of an approach on the basis of the k‐medoid algorithm for this task and in particular for experimental design and the split between training and validation set. We therefore compared the performance of models derived from such a selection to that of models derived using several other approaches, such as space‐filling design and D‐optimal design. We validated the performance on four datasets with different endpoints, representing toxicity, physicochemical properties and others. Compared with the models derived from the compounds selected by the other examined approaches, those derived with the k‐medoid selection show a high reliability for experimental design, as their performance was constantly among the best for all examined datasets. Of all the models derived with all examined approaches, those derived with the k‐medoid approach were the only ones that showed a significantly improved performance compared with a random selection, for all datasets, the whole examined range of selected compounds and for each dimensionality of the search space. Copyright © 2012 John Wiley & Sons, Ltd.     

微波消解-ICP-AES法测定欧盟REACH高度关注物质

采用浓HNO3-H2O2溶液微波法消解样品,电感耦合等离子体原子发射光谱（ICP-AES）测定欧盟REACH高度关注物质样品中Sn,As,Pb,Co,Cr元素的含量。样品中Sn,As,Pb,Co,Cr元素的含量在0．01～10mg／L范围内与发射强度呈线性关系,线性相关系数大于0．9999,各元素的回收率在94．9％～104．8％之间,样品测定结果的相对标准偏差小于5％（n=10）。Sn,As,Pb,Co,Cr元素的检出限分别为0．004,0．004,0．005,0．002,0．002mg／L。该方法测定结果准确可靠,适用于欧盟REACH高关注物质的快速初筛。