Analysis of the ecotoxicity data submitted within the framework of the REACH Regulation. Part 3. Experimental sediment toxicity assays

Fragments quantum descriptors in classification of bio-accumulative compounds

The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended databases. A number of compounds with results from quantum-chemical calculations conducted with Psi4 quantum chemistry package was also added to the quantum properties database. Classification results are compared with a baseline of random guesses and predictions obtained with the traditional RDKit generated molecular descriptors. Chosen classification metrics show that results obtained with fragments quantum descriptors fall between results from baseline and those provided by molecular descriptors widely applied in cheminformatics. According to the results, the implementation of principal component analysis, causes a drop in categorization metrics.

Towards the design of organosilicon compounds for environmental degradation by using structure biodegradability relationships

Organosilicon compounds have numerous applications in consumer products. After entering the environment most of them are resistant against microbial degradation and they persist in the environment. Accordingly, they are ubiquitously present in the environment. Therefore, better environmentally degradable organosilicon compounds are urgently needed. A systematic investigation of environmental degradability of organosilicon compounds allows to derive some general design principles, which in turn would enable chemists to reduce or better avoid environmental persistence of organosilicon compounds in the environment. Therefore, in this study, all organosilicon substances registered in the European Chemicals Agency (ECHA) database were evaluated for their environmental biodegradability. Results of own experiments with different organosilicon substances were added to extend the data basis. A dataset was generated. An assessment of all data was done and invalid data were excluded. The remaining 182 substances were grouped regarding their structure to derive general rules for the environmental biodegradability of organosilicon compounds. Non-biodegradable at all were for example cyclic, linear and branched siloxanes. Groups like ethers, esters, oximes, amines, and amides were prone to hydrolysis, which can result in readily biodegradable intermediates if they do not contain silicon functional groups anymore. This knowledge could be used for the design of better degradable organosilicon compounds as non-degradable substances should be avoided if they enter the environment after their usage.

The nematode Caenorhabditis elegans as an integrated toxicological tool to assess water quality and pollution

Determination of water quality status in rivers is critical to establish a sustainable water management policy. For this reason, over the last decades it has been recommended to perform integrated water assessments that include water quantities and physicochemical, ecological and toxicological tests. However, sometimes resources are limited and it is not possible to perform large-scale chemical determinations of pollutants or conduct numerous ecotoxicological tests. To overcome this problem we use and measure the growth, as a response parameter, of the soil nematode Caenorhabditis elegans to assess water quality in rivers. The C. elegans is a ubiquitous organism that has emerged as an important model organism in aquatic and soil toxicology research. The Tunuyán River Basin (Province of Mendoza, Argentina) has been selected as a representative traditional water monitoring system to test the applicability of the C. elegans toxicological bioassay to generate an integrated water quality evaluation. Jointly with the C. elegans toxic assays, physicochemical and bacteriological parameters were determined for each monitoring site. C. elegans bioassays help to identify different water qualities in the river basin. Multivariate statistical analysis (PCA and linear regression models) has allowed us to confirm that traditional water quality studies do not predict potential toxic effects on living organisms. On the contrary, physicochemical and bacteriological analyzes explain <62% of the C. elegans growth response variability, showing that ecotoxicological bioassays are important to obtain a realistic scenario of water quality threats. Our results confirm that the C. elegans bioassay is a sensible and suitable tool to assess toxicity and should be implemented in routine water quality monitoring.