The Acute Toxicity of Selected Alkylphenols to Young and AdultDaphnia magna

Gerritsen, A.; Hoeven, Nelly van der; Pielaat, Annemarie

doi:10.1006/eesa.1997.1578

Cited by 26 publications

(28 citation statements)

References 21 publications

(16 reference statements)

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“…The parameter estimates for the NEC and killing rate in D. magna, from Gerritsen et al (1998), are well in line with our data for fathead minnows. This indicates that these parameters for narcotic compounds may be representative for a wide range of species, which is also supported by the very small sensitivity differences between species for acute narcotic effects, as observed by Jager et al (2007).…”

Section: Non-polar Narcosissupporting

confidence: 87%

“…Because hydrophobicity drives the concentration in the cell membrane, the NEC and killing rate should show a strong correlation to K ow (as a proxy for membrane lipids). Such strong correlations between hydrophobicity and these model parameters were previously observed for Daphnia magna exposed to a series of alkylphenols (Gerritsen et al 1998), which are expected to be narcotic (Russom et al 1997).…”

Section: Theoretical Considerations On Parameter Valuessupporting

confidence: 74%

“…To illustrate inter-species generalities, the K ow -relationships of the hazard model's parameters derived by Gerritsen et al (1998) for Daphnia magna exposed to alkyl phenols will also be included, together with the minnow data for narcotics.…”

Section: Data Selectionmentioning

confidence: 99%

“…Lines in top plots represent regression equations on the filled data points. Parameter estimates for Daphnia magna from Gerritsen et al (1998). For the elimination rate, model lines represent the toxicokinetic model of Sijm and Van der Linde (1995), parameterised for P. promelas Reactive chemicals Figure 3 shows the estimated parameters for compounds classified as electrophile/pro-electrophile reactive.…”

Section: Non-polar Narcosismentioning

confidence: 99%

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A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity

Jager

Kooijman

2008

Ecotoxicology

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Quantitative structure-activity relationships (QSARs) for ecotoxicity can be used to fill data gaps and limit toxicity testing on animals. QSAR development may additionally reveal mechanistic information based on observed patterns in the data. However, the use of descriptive summary statistics for toxicity, such as the 4-day LC50 for fish, introduces bias and ignores valuable kinetic information in the data. Biology-based methods use all of the toxicity data in time to derive time-independent and unbiased parameter estimates. Such an approach offers whole new opportunities for mechanism-based QSAR development. In this paper, we apply the hazard model from DEBtox to analyse survival data for fathead minnows (Pimephales promelas). Different modes of action resulted in different patterns in the parameter estimates, and therefore, the toxicity data by themselves reveal insight into the actual mechanism of toxic action.

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Section: Non-polar Narcosissupporting

confidence: 87%

Section: Theoretical Considerations On Parameter Valuessupporting

confidence: 74%

Section: Data Selectionmentioning

confidence: 99%

Section: Non-polar Narcosismentioning

confidence: 99%

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A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity

Jager

Kooijman

2008

Ecotoxicology

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“…For example, zooplankton (composed in part of eggs and larvae of crustaceans, polychaetes, molluscs and teleosts) is a very important lower trophic component of aquatic ecosystems. There is increasing empirical evidence that demonstrates zooplankton can be severely affected by anthropogenic pollutants at environmental concentrations (Gerritsen et al 1998;Bailey et al 2000;Palma et al 2009). Zooplankton are an integral component of the food chain and provide the first forage for nearly all wild fishes and many other aquatic animals.…”

Section: Discussionmentioning

confidence: 98%