Prediction of toxicity and identification of key components for complex mixtures containing hormetic components.

Mixtures containing hormetic components are likely to induce hormesis. However, due to the presence of stimulatory effects, predicting the toxicity of such mixtures and identifying their key components face challenges. This study investigated the complex relationship between the stimulatory effects of individual components and their mixtures, focusing on predicting mixture toxicity and identifying key components influencing this toxicity. Sixteen chemicals, commonly found in disinfectants and hand sanitizers, were selected to construct a complex mixture system containing hormetic components. Using Vibrio qinghaiensis sp.-Q67 as an indicator organism, the study employed microplate toxicity tests to collect toxicity data for individual chemicals and their mixtures. The independent action (IA) and back-propagation neural network (BPNN) methods were utilized to predict mixture toxicity, while global sensitivity analysis (GSA) identified key components affecting toxicity. Results revealed that six of the sixteen chemicals exhibited time-dependent hormesis. However, when combined into mixtures, the stimulatory effects observed in individual components tended to diminish or disappear, leading to higher overall toxicity, likely due to synergism. Traditional models like the IA significantly underestimated mixture toxicity, whereas the BPNN model demonstrated superior predictive performance. GSA identified five key components, and changes in the levels of some non-toxic components significantly altered the toxicity of the mixtures. Moreover, increasing the levels of certain key components could either increase or decrease the mixture's toxicity, making the strategy of reducing their concentration to control mixture toxicity ineffective. This study revealed the potential of neural networks in predicting the toxicity of mixtures containing hormetic components and the possible characteristics of the effects of key components on mixture toxicity.