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预测抗生素混合物对发光菌产生兴奋效应的新方法。

Novel approach to predicting hormetic effects of antibiotic mixtures on Vibrio fischeri.

机构信息

State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.

出版信息

Chemosphere. 2013 Feb;90(7):2070-6. doi: 10.1016/j.chemosphere.2012.09.042. Epub 2012 Nov 30.

Abstract

The determination of the hormetic effects of a mixture is quite difficult because of the moderate simulation and the complexity of measurement in low doses. In the present study, two typical models for mixture toxicity prediction, concentration additive (CA) and independent action (IA), were used to predict the hormetic effects of mixtures. The predictive power of those models was validated by the hormetic effects (24-h exposure) of antibiotic's binary mixtures to Vibrio fischeri. The results showed that CA and IA were unable to predict the hormetic dose-response of mixture, especially those of the interactive mixtures. As an alternative, a novel model, which was named as "six-point" and developed based on the quantitative features in the determined dose-response curve and on the Quantitative Structure Activity Relationships (QSARs) approach, was proposed for predicting the hormetic effects of mixtures in low dose. The results indicated that the "six-point" model can accurately predict the mixture hormetic effects in low dose, not only for non-interactive mixtures but also for interactive mixtures. Therefore, the "six-point" model is a powerful tool to predict the mixture hormetic effects at low dose, and may offer an important approach in the environment risk assessment of mixtures.

摘要

由于在低剂量下的适度模拟和测量的复杂性,混合物的兴奋效应的确定相当困难。在本研究中,使用了两种典型的混合物毒性预测模型,浓度加和(CA)和独立作用(IA),来预测混合物的兴奋效应。通过抗生素二元混合物对发光菌的 24 小时暴露的兴奋效应验证了这些模型的预测能力。结果表明,CA 和 IA 均无法预测混合物的兴奋剂量反应,特别是那些相互作用的混合物。作为替代方法,提出了一种新的模型,称为“六点”模型,该模型基于确定的剂量反应曲线中的定量特征和定量构效关系(QSARs)方法开发,用于预测低剂量混合物的兴奋效应。结果表明,“六点”模型可以准确地预测低剂量混合物的兴奋效应,不仅对于非相互作用的混合物,而且对于相互作用的混合物也是如此。因此,“六点”模型是预测低剂量混合物兴奋效应的有力工具,并可能为混合物的环境风险评估提供重要方法。

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