Silvia Marchini

Herbicidal triazines: Acute toxicity onDaphnia, fish, and plants and analysis of its relationships with structural factors

The 24- and 48-hr EC50 immobilization test of Daphnia magna has been performed on 14 herbicidal triazines characterized by structural differences with respect to the substituent groups at the three carbon atoms in the s-triazinic ring. EC50 values of the tested compounds were found to vary within a factor of 6 to 7; such variations of toxicity have been analyzed in terms of structural variations concerning (i) the type of substituents, i.e., Cl, SCH3, or OCH3, at the carbon atom C-2, and (ii) the number and size of the alkyl groups at the aminic nitrogen atoms bound to the ring carbons C-4 and C-6. Literature data relative to the acute toxicity of the considered herbicides on fish and plants were also analyzed with reference to the above structural features. The possibility that separate contributions to toxic effects of triazines are provided by specific groups bound to the common structural moiety, constituted by the 1,3,5-triazinic ring, is examined and discussed.

Comparison of the susceptibility of daphnids and fish to benzene derivatives

Abstract A battery of acute toxicity tests with a variety of aquatic organisms may represent a valid approach for preliminary hazard assessment. As the difference in sensitivity among species can be very large, it is fundamental that the test organisms are properly selected. The paper compares the sensitivity of three aquatic species — Ceriodaphnia dubia, Daphnia magna , and Pimephales promelas (fathead minnow) larvae — to acute effects of toxicants. The comparison is based on data for nine compounds; namely, benzene and eight monosubstituted benzenes (MBs) expected to span a sufficiently wide range of toxicity. The results of acute toxicity tests with Ceriodaphnia dubia and fish larvae showed that the two organisms have a very similar susceptibility towards the tested chemicals, with the major exception of aniline, which was more toxic to daphnids than to fish (the actual LC 50 s differing by more than two orders of magnitude). Toxicity data for Daphnia magna , available from a previous study, show a trend similar to that observed with Ceriodaphnia dubia , but, at the same time, suggest that this species is equally or more sensitive than Ceriodaphnia dubia and fathead minnow.

Updating and validation of a daphnia toxicity model for benzene derivatives

Abstract A QSAR model for predicting the acute toxicity to Daphnia of mono-substituted benzenes (MBs) has been updated and validated experimentally. The model had been previously constructed by using a training set of eight MBs, which were selected by a statistical design out of a series of 100 and subsequently tested on their toxicity. For updating the model, a recently developed data analytic method based on PLS (Partial Least Squares) has been applied. For its validation, a total number of thirteen MBs have been tested under the same conditions as used for the training set. The selection of the validation compounds was carried out with a view to identifying potential structural and mechanistic outliers. The study allowed us to clarify the range of the model and to assess the accuracy of the predictions for non-tested MBs. The agreement between actual and predicted toxicities was good for the validation compounds ( Q 2 = 0.89); it was also acceptable for other MBs whose toxicities were reported in the literature.

Quantitative Structure—Activity Relationships (QSARs): An Integrated Multivariate Approach for Risk Assessment Studies

The conditions and methods for constructing reliable QSARs are revised in relation to each component of a QSAR study: the selection of a training set out of a QSAR compatible series, the collection of data pertinent to the descriptors matrix (X) and to the effects matrix (Y), the analysis of data to connect X to Y by a regression model, and the validation of the model. In discussing these conditions, attention is given to the constraints that arise from the theoretical foundation of QSARs as analogy models of local validity and to the complexity and limited knowledge about the mechanisms of action. Hence, emphasis is placed on the need and importance to adopt multivariate methods for dealing with (1) the characterization of the structures, (2) the selection of a representative set of training compounds, and (3) analysis of the data. It is finally shown that the same integrated multivariate approach applies to the modeling of biological activities and other properties—chemical and biological—as well as to the modeling of correlations between batteries of data. The role of QSAR in risk assessment is addressed in the second part of the article. The framework of a strategy for an efficient screening assessment of toxic substances through the modeling of their exposure and toxicity-related properties is outlined. Applications of the strategy are reported that deal with two series of compounds. Examples of toxicity and persistency models are illustrated.