Mc Calleja

Comparative acute toxicity of the first 50 Multicentre Evaluation of In Vitro Cytotoxicity chemicals to aquatic non-vertebrates

The acute toxicity data of the first 50 chemicals of the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme is compared for three “cyst-based toxicity tests” (Artoxkit M with Artemia salina, Streptoxkit F with Streptocephalus proboscideus, and Rotoxkit F with Brachionus calyciflorus), and two other tests (the Daphnia magna and the Photobacterium phosphoreum Microtox™ tests) commonly used in ecotoxicology. The difference in sensitivity for the 50 chemicals was as high as 19 orders of magnitude (on a molecular weight basis) between the most and least sensitive species. Generally, a similar toxicity ranking of the 5 test species was found for most of the chemicals and the interspecies correlations were high. Results from Principal Component Analysis (PCA) and cluster analysis indicated that the groupings are not related to a clear and defined chemical structure. However, the loading plot of the first two principal components may aid in selecting the minimum number and type of tests that have to be included in a battery which encompasses a broad spectrum of toxicity levels. Consequently, this study supports the use of a selected battery of tests to evaluate ecotoxicity and suggests its possible importance for screening of biologically-active compounds from natural sources.

Human acute toxicity prediction of the first 50 MEIC chemicals by a battery of ecotoxicological tests and physicochemical properties

Five acute bioassays consisting of three cyst-based tests (with Artemia salina, Streptocephalus proboscideus and Brachionus calyciflorus), the Daphnia magna test and the bacterial luminescence inhibition test (Photobacterium phosphoreum) are used to determine the acute toxicity of the 50 priority chemicals of the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme. These tests and five physiocochemical properties (n-octanol-water partition coefficient, molecular weight, melting point, boiling point and density) are evaluated either singly or in combination to predict human acute toxicity. Acute toxicity in human is expressed both as oral lethal doses (HLD) and as lethal concentrations (HLC) derived from clinical cases. A comparison has also been made between the individual tests and the conventional rodent tests, as well as between rodent tests and the batteries resulting from partial least squares (PLS), with regard to their predictive power for acute toxicity in humans. Results from univariate regression show that the predictive potential of bioassays (both ecotoxicological and rodent tests) is generally superior to that of individual physicochemical properties for HLD. For HLC prediction, however, no consistent trend could be discerned that indicated whether bioassays are better estimators than physicochemical parameters. Generally, the batteries resulting from PLS regression seem to be more predictive than rodent tests or any of the individual tests. Prediction of HLD appears to be dependent on the phylogeny of the test species: cructaceans, for example, appear to be more important components in the test battery than rotifers and bacteria. For HLC prediction, one anostracan and one cladoceran crustacean are considered to be important. When considering both ecotoxicological tests and physicochemical properties, the battery based on the molecular weight and the cladoceran crustacean predicts HLC substantially better than any other combination.

Qsar Models for Predicting the Acute Toxicity of Selected Organic Chemicals with Diverse Structures to Aquatic Non-Vertebrates and Humans

The linear and non-linear relationships of acute toxicity (as determined on five aquatic non-vertebrates and humans) to molecular structure have been investigated on 38 structurally-diverse chemicals. The compounds selected are the organic chemicals from the 50 priority chemicals prescribed by the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme. The models used for the evaluations are the best combination of physico-chemical properties that could be obtained so far for each organism, using the partial least squares projection to latent structures (PLS) regression method and backpropagated neural networks (BPN). Non-linear models, whether derived from PLS regression or backpropagated neural networks, appear to be better than linear models for describing the relationship between acute toxicity and molecular structure. BPN models, in turn, outperform non-linear models obtained from PLS regression. The predictive power of BPN models for the crustacean test species are better than the model for humans (based on human lethal concentration). The physico-chemical properties found to be important to predict both human acute toxicity and the toxicity to aquatic non-vertebrates are the n-octanol water partition coefficient (Pow) and heat of formation (HF). Aside from the two former properties, the contribution of parameters that reflect size and electronic properties of the molecule to the model is also high, but the type of physico-chemical properties differs from one model to another. In all of the best BPN models, some of the principal component analysis (PCA) scores of the 13C-NMR spectrum, with electron withdrawing/accepting capacity (LUMO, HOMO and IP) are molecular size/volume (VDW or MS1) parameters are relevant. The chemical deviating from the QSAR models include non-pesticides as well as some of the pesticides tested. The latter type of chemical fits in a number of the QSAR models. Outliers for one species may be different from those of other test organisms.