Related Experiment Video
Updated: Aug 13, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Predicting single and mixture toxicity of petrogenic polycyclic aromatic hydrocarbons to the copepod Oithona davisae
Carlos Barata1, Albert Calbet, Enric Saiz
1Laboratory of Environmental Toxicology (UPC), CN 150 Km 14.5, Terrassa 08220, Spain. barata@intexter.upc.es barata@intexter.upc.edu
Abstract:
In the present study, the acute toxicity of 10 polycyclic aromatic hydrocarbons (PAHs) associated with the Prestige fuel oil spill (Spain, 2002) were evaluated, either as single substances or in mixtures, in adults of the copepod Oithona davisae. All but dimethylphenanthrene had negative effects on O. davisae survival at concentrations below their water solubility, with 48-h median lethal concentrations for naphthalene and pyrene of 56.1 and 0.8 micromol/L, respectively, making these the least and most toxic compounds. Polycyclic aromatic hydrocarbons had narcotic effects on copepods, as evidenced by the lack of motility at lower concentrations than those causing death. Naphthalene showed the greatest narcotic effects, and phenanthrene showed minor effects. Acute toxicity of the tested PAHs was inversely related (r2 = 0.9) with their octanol-water partition coefficient, thereby confirming the validity of the baseline quantitative structure-activity regression models for predicting the toxicity of PAH compounds in copepod species. When supplied in mixtures, the toxic effect of PAHs was additive. These results indicate that the many PAHs in an oil spill can be considered unambiguous baseline toxicants (class 1) acting additively as nonpolar narcotics in copepods; hence, their individual and combined toxicity can be predicted using their octanol-water partition coefficient.
More Related Videos
04:39A Modified QuEChERS-HPLC Method for Detection of Polycyclic Aromatic Hydrocarbons in Zebrafish Embryos Exposed to Fine Particulate Matter
Published on: June 13, 2025
09:01A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
Published on: March 14, 2019