Fipronil is an efficient phenylpyrazole insecticide that acts on insect γ-aminobutyric acid (GABA) receptors (GABARs) and has low toxicity to mammals but high toxicity to nontarget organisms such as fish. To develop novel efficient low-toxicity insecticides, it is necessary to determine the detailed toxic mechanism at the molecular target level. In this work, methods including affinity chromatography, fluorescent-labeled binding assays, and molecular modeling were integrated to explore the binding of fipronil to GABARs in fish ( Aristichthys nobilis) and insects ( Musca domestica). Affinity chromatography revealed that fipronil acts on two different subunits of GABARs in fish and M. domestica. Moreover, fluorescence assays revealed that fipronil exhibits similar affinity to the two GABARs. The K and B of fipronil binding to the A. nobilis GABAR were 346 ± 6 nmol/L and 40.6 ± 3.5 pmol/mg of protein, respectively. And the K and B of fipronil binding to the GABAR in M. domestica brain were 109 ± 9 nM and 21.3 ± 2.5 pmol/mg of protein, respectively. In addition, similar fipronil binding positions but different binding modes were observed in docking studies with Brachydanio rerio var. and M. domestica GABARs. These findings indicated similar interactions of fipronil with fish and insects, leading to high toxicity. The different binding features of fipronil between the two species might be helpful for the design and development of highly selective insecticides with low toxicity to fish.
Abstract:The motivation of this paper is that the effect of landscape pattern information on the accuracy of particulate matter estimation is seldom reported. The landscape pattern indexes were incorporated in a land use regression (LUR) model to investigate the performance of PM 2.5 simulation over Zhejiang Province. The study results show that the prediction accuracy of the model has been improved significantly after the incorporation of the landscape pattern indexes. At class-level, waters and residential areas were clearly landscape components influencing decreasing or increasing PM 2.5 concentration. At landscape-level, CONTAG (contagion index) played a huge negative role in pollutant concentrations. Latitude and relative humidity are key factors affecting the PM 2.5 concentration at province level. If the land use regression model incorporating landscape pattern indexes was used to simulate distribution of PM 2.5 , the accuracy of ordinary kriging for the LUR-based data mining was higher than the accuracy of LUR-based ordinary kriging, especially in the area of low pollution concentration.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.