Literature DB >> 16646492

Temporal dynamics of effect concentrations.

Olga Alda Alvarez1, Tjalling Jager, Beatriz Nuñez Colao, Jan E Kammenga.   

Abstract

In effect assessment the comparability and applicability of LCx and ECx values, which are calculated at single points in time during exposure, relies on the ability to perform a valid extrapolation to other time points of interest. The behavior of LCx in time has been extensively studied, and the behavior of ECx in time is expected to follow similar dynamics, as it is considered that the LCx is just a specific case of ECxs. However, most models have focused on validating the dynamics of LCx, and hardly anything is known about the time dependence of ECx for other endpoints or whether it is comparable to that of LCxs. We have created four scenarios where we study the dynamics of the ECx for different endpoints and how it is affected by the characteristics of two different compounds (carbendazim and pentachlorobenzene) and of two different life history strategies (hermaphroditic and sexually reproducing strains of Caenorhabditis elegans). The observed patterns of behavior in time of the ECx for body size and for reproduction showed unexpected dynamics that deviate considerably from that of the LCx. It was demonstrated that the temporal dynamics of ECx were very different for each particular endpoint. The shape of the ECx-time curves depends on the intrinsic characteristics of the endpoint of study, as well as on the characteristics of the compound and life history strategy of the organism. This makes extrapolation in time or between endpoints difficult and hampers the comparability of results based on this summary statistic. The interpretation of the results from toxicity tests can be improved through process-based modeling, as demonstrated on the current data set.

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Year:  2006        PMID: 16646492     DOI: 10.1021/es052260s

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  7 in total

1.  Simplified models to analyse time- and dose-dependent responses of populations to toxicants.

Authors:  Francisco Sánchez-Bayo; Kouichi Goka
Journal:  Ecotoxicology       Date:  2007-07-11       Impact factor: 2.823

2.  Hormesis on life-history traits: is there such thing as a free lunch?

Authors:  Tjalling Jager; Alpar Barsi; Virginie Ducrot
Journal:  Ecotoxicology       Date:  2012-11-25       Impact factor: 2.823

3.  Extrapolating ecotoxicological effects from individuals to populations: a generic approach based on Dynamic Energy Budget theory and individual-based modeling.

Authors:  Benjamin T Martin; Tjalling Jager; Roger M Nisbet; Thomas G Preuss; Monika Hammers-Wirtz; Volker Grimm
Journal:  Ecotoxicology       Date:  2013-02-22       Impact factor: 2.823

4.  A biology-based approach for mixture toxicity of multiple endpoints over the life cycle.

Authors:  Tjalling Jager; Tine Vandenbrouck; Jan Baas; Wim M De Coen; Sebastiaan A L M Kooijman
Journal:  Ecotoxicology       Date:  2009-09-22       Impact factor: 2.823

5.  Linking toxicant physiological mode of action with induced gene expression changes in Caenorhabditis elegans.

Authors:  Suresh Swain; Jodie F Wren; Stephen R Stürzenbaum; Peter Kille; A John Morgan; Tjalling Jager; Martijs J Jonker; Peter K Hankard; Claus Svendsen; Jenifer Owen; B Ann Hedley; Mark Blaxter; David J Spurgeon
Journal:  BMC Syst Biol       Date:  2010-03-23

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

Authors:  Tjalling Jager; Sebastiaan A L M Kooijman
Journal:  Ecotoxicology       Date:  2008-10-19       Impact factor: 2.823

7.  Reduced life expectancy model for effects of long term exposure on lethal toxicity with fish.

Authors:  Vibha Verma; Qiming J Yu; Des W Connell
Journal:  ISRN Toxicol       Date:  2013-12-26
  7 in total

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