Predicting joint toxicity of chemicals by incorporating a weighted descriptor into a mixture model: Cases for binary antibiotics and binary nanoparticles

An Insight into the Combined Toxicity of 3,4-Dichloroaniline with Two-Dimensional Nanomaterials: From Classical Mixture Theory to Structure-Activity Relationship

The assessment and prediction of the toxicity of engineered nanomaterials (NMs) present in mixtures is a challenging research issue. Herein, the toxicity of three advanced two-dimensional nanomaterials (TDNMs), in combination with an organic chemical (3,4-dichloroaniline, DCA) to two freshwater microalgae (Scenedesmus obliquus and Chlorella pyrenoidosa), was assessed and predicted not only from classical mixture theory but also from structure-activity relationships. The TDNMs included two layered double hydroxides (Mg-Al-LDH and Zn-Al-LDH) and a graphene nanoplatelet (GNP). The toxicity of DCA varied with the type and concentration of TDNMs, as well as the species. The combination of DCA and TDNMs exhibited additive, antagonistic, and synergistic effects. There is a linear relationship between the different levels (10, 50, and 90%) of effect concentrations and a Freundlich adsorption coefficient (K_F) calculated by isotherm models and adsorption energy (E_a) obtained in molecular simulations, respectively. The prediction model incorporating both parameters K_F and E_a had a higher predictive power for the combined toxicity than the classical mixture model. Our findings provide new insights for the development of strategies aimed at evaluating the ecotoxicological risk of NMs towards combined pollution situations.