Cargando…
A biology-based approach for mixture toxicity of multiple endpoints over the life cycle
Typical approaches for analyzing mixture ecotoxicity data only provide a description of the data; they cannot explain observed interactions, nor explain why mixture effects can change in time and differ between endpoints. To improve our understanding of mixture toxicity we need to explore biology-ba...
Autores principales: | , , , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Springer US
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811243/ https://www.ncbi.nlm.nih.gov/pubmed/19771510 http://dx.doi.org/10.1007/s10646-009-0417-z |
Sumario: | Typical approaches for analyzing mixture ecotoxicity data only provide a description of the data; they cannot explain observed interactions, nor explain why mixture effects can change in time and differ between endpoints. To improve our understanding of mixture toxicity we need to explore biology-based models. In this paper, we present an integrated approach to deal with the toxic effects of mixtures on growth, reproduction and survival, over the life cycle. Toxicokinetics is addressed with a one-compartment model, accounting for effects of growth. Each component of the mixture has its own toxicokinetics model, but all compounds share the effect of body size on uptake kinetics. The toxicodynamic component of the method is formed by an implementation of dynamic energy budget theory; a set of simple rules for metabolic organization that ensures conservation of mass and energy. Toxicant effects are treated as a disruption of regular metabolic processes such as an increase in maintenance costs. The various metabolic processes interact, which means that mixtures of compounds with certain mechanisms of action have to produce a response surface that deviates from standard models (such as ‘concentration addition’). Only by separating these physiological interactions from the chemical interactions between mixture components can we hope to achieve generality and a better understanding of mixture effects. For example, a biology-based approach allows for educated extrapolations to other mixtures, other species, and other exposure situations. We illustrate our method with the interpretation of partial life-cycle data for two polycyclic aromatic hydrocarbons in Daphnia magna. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10646-009-0417-z) contains supplementary material, which is available to authorized users. |
---|