Τίτλος:
Immobilized artificial membrane chromatography as a tool for the prediction of ecotoxicity of pesticides
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
The potential of Immobilized Artificial Membrane (IAM) chromatography to predict ecotoxicological endpoints of pesticides was investigated. For this purpose, retention factors of 39 structurally-diverse pesticides were measured on an IAM stationary phase. A representative test set of 6 pesticides was carefully selected. The training set, involving the remaining pesticides for which experimental data were available, served to establish linear IAM models with LC50/EC50 values in a series of aquatic organisms involving Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD50 values in honey bee, compiled from literature sources. For reasons of comparison, corresponding models were derived by replacing IAM retention factors with octanol-water partition coefficients (logP). Considering the similar regression equations obtained for the 4 fish species, general models to predict toxicity in fish were established. Most models were improved upon inclusion of additional physicochemical parameters. The positive contribution of Molecular Weight to ecotoxicity along with the positive sign of hydrogen bond indices in most cases implies that toxic action is manifested mainly by accumulation on the membrane rather than through diffusion across them. IAM models are generally followed by better statistics and superior predictive performance than those based on experimental or computed logP. Predictions based on IAM chromatography were comparable or even superior with those performed by EPI Suite Software. Hence, IAM retention factors are suggested as promising indices in order to screen or rank chemicals with respect to their ecotoxicological risk, especially in the case of new entities. © 2019 Elsevier Ltd
Συγγραφείς:
Stergiopoulos, C.
Makarouni, D.
Tsantili-Kakoulidou, A.
Ochsenkühn-Petropoulou, M.
Tsopelas, F.
Εκδότης:
Elsevier Ireland Ltd
Λέξεις-κλειδιά:
Fish; Forecasting; Hydrogen bonds; Pesticides; Toxicity, Ecotoxicological endpoints; Ecotoxicological risks; Immobilized artificial membrane chromatographies; Lipophilicity; Octanol-water partition coefficient; Phospholipophilicity; Physicochemical parameters; Predictive performance, Chromatography, aldrin; allicin; azinphos ethyl; azinphos methyl; bifenthrin; chlorpyrifos; cinnamaldehyde; cypermethrin; dimpylate; endosulfan; ethion; eugenol; fenoxycarb; fluometuron; geraniol; gibberellic acid; imidacloprid; limonene; menthol; myclobutanil; octanol; parathion; penconazole; pendimethalin; permethrin; pesticide; pyrethrin; quinalphos; urea; pesticide, chemical bonding; chromatography; diffusion; ecotoxicology; flea; honeybee; hydrogen; immobilization; molecular analysis; mollusc; perciform; pesticide; prediction; software, Article; artificial membrane; bioaccumulation; chemical structure; chromatography; chromatography by stationary phase; Cladocera; controlled study; Crassostrea virginica; diffusion; ecotoxicity; honeybee; hydrogen bond; immobilized artificial membrane chromatography; Lepomis macrochirus; molecular weight; nonhuman; Oncorhynchus mykiss; physical chemistry; Pimephales promelas; predictive value; animal; aquatic species; artificial membrane; bee; biological model; drug effect; ecotoxicology; fish; procedures, Apis mellifera; Cladocera; Crassostrea virginica; Cyprinodon variegatus; Lepomis macrochirus; Oncorhynchus mykiss; Pimephales promelas, Animals; Aquatic Organisms; Bees; Chromatography; Ecotoxicology; Fishes; Membranes, Artificial; Models, Biological; Molecular Weight; Pesticides
DOI:
10.1016/j.chemosphere.2019.02.075
