ANVAS: Artificial Neural Variables Adaptation System for descriptor selection

A new algorithm model-oriented for variable selection is presented in this study. It is based on the combination of genetic algorithms (GA) for hyperspace exploration, and counterpropagation artificial neural network (CP ANN) for deriving the fitness score. The proposed method performed very well on both well defined synthetic data sets and real academic data sets.     

Fractionation and toxicity evaluation of waste waters

Several toxicity-based procedures have been proposed for waste water risk assessment but the toxic agents could never be identified in these very complex mixtures. A procedure was adopted using disposable solid-phase extraction cartridges to extract organic chemicals and preparative HPLC to fractionate them in relation of their hydrophobicity. Acute toxicity of whole samples and their fractions was measured on Daphnia magna, using a commercially available biokit. The procedure was applied to leachate from an industrial landfill and a textile effluent. In both cases the toxic effects due to xenobiotics were highest in the most hydrophobic HPLC fraction. The compounds responsible for the observed toxicity were identified and quantified by GC-MS. Reconstructed mixtures were analysed to assess their fitting with GC profiles and tested for toxicity to compare the responses of individual chemicals and mixtures.     

CAESAR models for developmental toxicity

Background

The new REACH legislation requires assessment of a large number of chemicals in the European market for several endpoints. Developmental toxicity is one of the most difficult endpoints to assess, on account of the complexity, length and costs of experiments. Following the encouragement of QSAR (in silico) methods provided in the REACH itself, the CAESAR project has developed several models.

Results

Two QSAR models for developmental toxicity have been developed, using different statistical/mathematical methods. Both models performed well. The first makes a classification based on a random forest algorithm, while the second is based on an adaptive fuzzy partition algorithm. The first model has been implemented and inserted into the CAESAR on-line application, which is java-based software that allows everyone to freely use the models.

Conclusions

The CAESAR QSAR models have been developed with the aim to minimize false negatives in order to make them more usable for REACH. The CAESAR on-line application ensures that both industry and regulators can easily access and use the developmental toxicity model (as well as the models for the other four endpoints).

     

Three-dimensional in vivo scanning microscopy with inertia-free focus control

The acquisition of high-resolution images in three dimensions is of utmost importance for the morphological and functional investigation of biological tissues. Here, we present a laser scanning two-photon microscope with remote and motionless control of the focus position. The movement of the excitation spot along the propagation direction is achieved by shaping the laser wavefront with a spatial light modulator. Depending on the optical properties of the objective in use, this approach allows z movements in a range of tens to hundreds of micrometers with small changes of the point spread function. We applied this technique for the three-dimensional (3D) imaging of fluorescent cells in the mouse neocortex in vivo. The presented system bypasses the limitations of microscopes based on moving objectives, enabling high-resolution inertia-free 3D imaging.     

Idealization of correlations between optimal simplified molecular input-line entry system-based descriptors and skin sensitization

The Index of Ideality of Correlation (IIC) is a new criterion of the predictive potential for quantitative structure–property/activity relationships. The value of the IIC is a mathematical function sensitive to the value of the correlation coefficient and dispersion (expressed via mean absolute error). The IIC has been applied to develop QSAR models for skin sensitization achieving good predictive potential. The ‘ideal correlation’ is based on elementary fragments of simplified molecular input-line entry system (SMILES) and on the taking into account of the total numbers of nitrogen, oxygen, sulphur and phosphorus in the molecule.