Death Dilemma and Organism Recovery in Ecotoxicology

Article English OPEN
Ashauer, Roman ; O'Connor, Isabel ; Hintermeister, Anita ; Escher, Beate I. (2015)
  • Subject: 1600 | 2304

Why do some individuals survive after exposure to chemicals while others die? Either, the tolerance threshold is distributed among the individuals in a population, and its exceedance leads to certain death, or all individuals share the same threshold above which death occurs stochastically. The previously published General Unified Threshold model of Survival (GUTS) established a mathematical relationship between the two assumptions. According to this model stochastic death would result in systematically faster compensation and damage repair mechanisms than individual tolerance. Thus, we face a circular conclusion dilemma because inference about the death mechanism is inherently linked to the speed of damage recovery. We provide empirical evidence that the stochastic death model consistently infers much faster toxicodynamic recovery than the individual tolerance model. Survival data can be explained by either, slower damage recovery and a wider individual tolerance distribution, or faster damage recovery paired with a narrow tolerance distribution. The toxicodynamic model parameters exhibited meaningful patterns in chemical space, which is why we suggest toxicodynamic model parameters as novel phenotypic anchors for in vitro to in vivo toxicity extrapolation. GUTS appears to be a promising refinement of traditional survival curve analysis and dose response models.
  • References (100)
    100 references, page 1 of 10

    (1) Berkson, J. Why I prefer logits to probits. Biometrics 1951, 7 (4), 327−339.

    (2) Newman, M. C.; McCloskey, J. T. The individual tolerance concept is not the sole explanation for the probit dose-effect model.

    Environ. Toxicol. Chem. 2000, 19 (2), 520−526.

    (3) Jager, T.; Albert, C.; Preuss, T. G.; Ashauer, R. General Unified Threshold Model of Survival - a Toxicokinetic-Toxicodynamic Framework for Ecotoxicology. Environ. Sci. Technol. 2011, 45 (7), 2529−2540.

    (4) Sprague, J. B. Measurement of pollutant toxicity to fish.I. Bioassay methods for acute toxicity. Water Res. 1969, 3 (11), 793−821.

    (5) Ashauer, R.; Boxall, A. B. A.; Brown, C. D. Simulating toxicity of carbaryl to Gammarus pulex after sequential pulsed exposure. Environ.

    Sci. Technol. 2007, 41 (15), 5528−5534.

    (6) Jager, T.; Kooijman, S. A. L. M. A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity.

    Ecotoxicology 2009, 18 (2), 187−196.

    (7) Ashauer, R.; Hintermeister, A.; O'Connor, I.; Elumelu, M.; Hollender, J.; Escher, B. I. Significance of Xenobiotic Metabolism for Bioaccumulation Kinetics of Organic Chemicals in Gammarus pulex.

  • Related Research Results (2)
  • Metrics
    0
    views in OpenAIRE
    0
    views in local repository
    19
    downloads in local repository

    The information is available from the following content providers:

    From Number Of Views Number Of Downloads
    White Rose Research Online - IRUS-UK 0 19
Share - Bookmark