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Modes of action in ecotoxicology: Their role in body burdens, species sensitivity, QSARs, and mixture effects

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ENVIRONMENTAL SCIENCE & TECHNOLOGY
卷 36, 期 20, 页码 4201-4217

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AMER CHEMICAL SOC
DOI: 10.1021/es015848h

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In contrast to the general research attitude in the basic sciences, environmental sciences are often goal-driven and should provide the scientific basis for risk assessment procedures, cleanup, and precautionary measures and. finally provide a decision support for policy and management. Hence, the prominent role of mechanistic studies in ecotoxicology is not only to understand the impact of pollutants on living organisms but also to deduce general principles for the categorization and, assessment of effects. The goal of this review is, therefore, not to provide an exhaustive coverage of modes of toxic action and their underlying biochemical mechanisms but rather to discuss critically the application of this knowledge in ecotoxicological risk assessment. Knowing the mechanism or, at least, the mode of toxic action is indispensable for developing descriptive and predictive models in ecotoxicology. This review. seeks. to show the crucial role of target sites, interactions with the-target site(s), and mechanisms for an adequate and, efficient ecotoxicological risk, assessment. Emphasis in the discussion is on target effect concentrations (or target occupancy), species selectivity and species sensitivity, time perspective of effect studies, Quantitative Structure-Activity Relationships (QSAR), and mixture toxicity. A particular focus of this review is on multiple mechanisms. Although;the illustrative examples were mainly taken from studies in, aquatic, ecotoxicology, the proposed conceptual approach is also in principle applicable and even particularly useful for soil and sediment, systems. Recommendations for further research and developments include the use of internal effect concentrations and target site concentrations in site-specific risk assessment and as a mixture toxicity parameter as well as general considerations for the derivation of mechanistically meaningful QSAR and other predictive models.

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