Antagonism between heavy metal and selenium (Se) could significantly affect their biotoxicity, but little is known about the mechanisms underlying such microbial-mediated antagonistic processes as well as the formed products. In this work, we examined the cadmium (Cd)–Se interactions and their fates in Caenorhabditis elegans through in vivo and in vitro analysis and elucidated the machinery of Se-stimulated Cd detoxification. Although the Se introduction induced up to 3-fold higher bioaccumulation of Cd in C. elegans than the Cd-only group, the nematode viability remained at a similar level to the Cd-only group. The relatively lower level of reactive oxygen species in the Se & Cd group confirms a significantly enhanced Cd detoxification by Se. The Cd–Se interaction, mediated by multiple thiols, including glutathione and phytochelatin, resulted in the formation of less toxic cadmium selenide (CdSe)/cadmium sulfide (CdS) nanoparticles. The CdSe/CdS nanoparticles were mainly distributed in the pharynx and intestine of the nematodes, and continuously excreted from the body, which also benefitted the C. elegans survival. Our findings shed new light on the microbial-mediated Cd–Se interactions and may facilitate an improved understanding and control of Cd biotoxicity in complicated coexposure environments.

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Due to the large number of ionic liquids (ILs) and their potential environmental risk, assessing the toxicity of ILs by ecotoxicological experiment only is insufficient. Quantitative structureactivity relationship (QSAR) has been proven to be a quick and effective method to estimate the viscosity, melting points, and even toxicity of ILs. In this work, the LC 50 values of 30 imidazolium-based ILs were determined with Caenorhabditis elegans as a model animal. Four suitable molecular descriptors were selected on the basis of genetic function approximation algorithm to construct a QSAR model with an R 2 value of 0.938. The predicted lgLC 50 in this work are in agreement with the experimental values, indicating that the model has good stability and predictive ability. Our study provides a valuable model to predict the potential toxicity of ILs with different sub-structures to the environment and human health.