In the environment, chemical substances appear as complex mixtures and consequently organisms are exposed to a variety of chemicals from different sources (e.g. wastewater treatment plants, agriculture runoffs). When studying chemical mixtures, there are two conceptual models usually used to predict toxicity: the Independent Action (IA) and Concentration Addition (CA) models. However, deviations from these reference models can occur as synergism or antagonism, dose ratio or dose level dependency. The aim of the present study was to investigate the effects of triclosan and carbendazim, and their binary mixture to Daphnia magna. With this purpose, immobilisation, feeding inhibition, and reproduction were assessed as main ecotoxicity endpoints. In addition, in vivo genotoxicity of both chemicals was investigated using the comet assay. In the single exposure, carbendazim was more toxic to D. magna than triclosan. When daphnids were exposed to both single compounds, DNA damage was observed. Concerning mixture exposures, different endpoints followed different patterns of response, from additivity: IA model (feeding inhibition and reproduction data), to deviations that indicate interaction between chemicals inside the organism: dose level dependency (immobilisation data) and dose ratio dependency (DNA damage). This study showed that additivity does not rule the dose-effect relation in chemical mixtures of carbendazim and triclosan and interactions between both chemicals might induce generally higher toxicity than predicted based on single chemical exposures.
Terrestrial isopods from the species Porcellionides pruinosus were exposed to the maximum allowed nickel concentration in the Canadian framework guideline (50 mg Ni/kg soil) and to 5× this concentration (250 mg Ni/kg soil). The exposure lasted for 28 days and was followed by a recovery period of 14 days where organisms were changed to clean soil. Organisms were sampled after 24 h, 48 h, 96 h, 7 days, 14 days, 21 days, and 28 days of exposure, and at days 35 and 42 during the recovery period. For each sampling time the acetylcholinesterase (AChE), glutathione-S-transferases (GST), catalase (CAT), lactate dehydrogenase (LDH) activities were determined as well as lipid peroxidation rate (LPO) along with lipids, carbohydrates, proteins content, energy available (Ea), energy consumption (Ec) and cellular energy allocation (CEA). The integrated biomarker response (IBR) was calculated for each sampling time as well as for each one of the above parameters. In addition, mortality was also recorded throughout the assay. The results obtained showed that nickel induced oxidative stress, evidenced by results on GST, GPx, CAT or LPO, but also on changes in the energy reserves content of these organisms. In addition, this study showed that these organisms possess a specific strategy to handle nickel toxicity. In this case, biomarkers were associated with costs in the energy budget, and the increase of energy reserves has a compensation for that cost.
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