Norwegian Institute for Water Research, Gaustadalleen 21, 0349 Oslo, Norway.
Norwegian Institute for Water Research, Gaustadalleen 21, 0349 Oslo, Norway.
Aquat Toxicol. 2014 May;150:45-54. doi: 10.1016/j.aquatox.2014.02.013. Epub 2014 Feb 28.
Organisms in the environment are exposed to a number of pollutants from different compound groups. In addition to the classic pollutants like the polychlorinated biphenyls, polyaromatic hydrocarbons (PAHs), alkylphenols, biocides, etc. other compound groups of concern are constantly emerging. Pharmaceuticals and personal care products (PPCPs) can be expected to co-occur with other organic contaminants like biocides, PAHs and alkylphenols in areas affected by wastewater, industrial effluents and intensive recreational activity. In this study, representatives from these four different compound groups were tested individually and in mixtures in a growth inhibition assay with the marine algae Skeletonema pseudocostatum (formerly Skeletonema costatum) to determine whether the combined effects could be predicted by models for additive effects; the concentration addition (CA) and independent action (IA) prediction model. The eleven tested compounds reduced the growth of S. pseudocostatum in the microplate test in a concentration-dependent manner. The order of toxicity of these chemicals were irgarol>fluoxetine>diuron>benzo(a)pyrene>thioguanine>triclosan>propranolol>benzophenone 3>cetrimonium bromide>4-tert-octylphenol>endosulfan. Several binary mixtures and a mixture of eight compounds from the four different compound groups were tested. All tested mixtures were additive as model deviation ratios, the deviation between experimental and predicted effect concentrations, were within a factor of 2 from one or both prediction models (e.g. CA and IA). Interestingly, a concentration dependent shift from IA to CA, potentially due to activation of similar toxicity pathways at higher concentrations, was observed for the mixture of eight compounds. The combined effects of the multi-compound mixture were clearly additive and it should therefore be expected that PPCPs, biocides, PAHs and alkylphenols will collectively contribute to the risk in areas contaminated by such complex mixtures.
环境中的生物体会接触到来自不同化合物组的多种污染物。除了多氯联苯、多环芳烃 (PAHs)、烷基酚、杀生物剂等典型污染物外,其他关注的化合物组也在不断涌现。在受废水、工业废水和密集娱乐活动影响的地区,预计药品和个人护理产品 (PPCPs) 将与杀生物剂、PAHs 和烷基酚等其他有机污染物同时存在。在这项研究中,来自这四个不同化合物组的代表分别在混合物中,用海洋藻类 Skeletonema pseudocostatum(以前称为 Skeletonema costatum)进行了生长抑制测定,以确定组合效应是否可以通过加性效应模型来预测;浓度加和(CA)和独立作用(IA)预测模型。在微孔板试验中,这 11 种测试化合物以浓度依赖的方式降低了 S. pseudocostatum 的生长。这些化学物质的毒性顺序为:irgarol>氟西汀>敌草隆>苯并(a)芘>硫鸟嘌呤>三氯生>普萘洛尔>二苯甲酮 3>十六烷基溴化铵>4-叔辛基苯酚>硫丹。测试了几种二元混合物和来自四个不同化合物组的八种化合物的混合物。所有测试混合物均为加性混合物,因为模型偏差比,即实验和预测效应浓度之间的偏差,在 2 倍以内来自一个或两个预测模型(例如 CA 和 IA)。有趣的是,在八种化合物混合物中观察到从 IA 到 CA 的浓度依赖性转变,这可能是由于在较高浓度下激活了类似的毒性途径。多化合物混合物的联合效应显然是加性的,因此应该预计 PPCPs、杀生物剂、PAHs 和烷基酚将共同导致受此类复杂混合物污染地区的风险增加。