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Assessment of river sediment toxicity: combining empirical zebrafish embryotoxicity testing with in silico toxicity characterization

Babić, Sanja; Barišić, Josip; Stipaničev, Draženka; Repec, Siniša; Lovrić, Mario; Malev, Olga; Martinović-Weigelt, Dalma; Čož-Rakovac, Rozelindra; Klobučar, Goran (2018) Assessment of river sediment toxicity: combining empirical zebrafish embryotoxicity testing with in silico toxicity characterization. Science of the Total Environment, 643 . pp. 435-450. ISSN 0048-9697

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Quantitative chemical analyses of 428 organic contaminants (OCs) indicated the presence of 313 OCs in the sediment extracts from Sava River, Croatia. Pharmaceuticals were present in higher concentrations than pesticides thus confirming their increasing threat to freshwater ecosystems. Toxicity evaluation of the sediment extracts from four locations (Jesenice, Rugvica, Galdovo and Lukavec) using zebrafish embryotoxicity test (ZET) accompanied with semi-quantitative histopathological analyses exhibited correlation with cumulative number and concentrations of OCs at the investigated sites (10.05, 15.22, 1.25, and 9.13 µg/g respectively). Toxicity of sediment extracts and sediment was predicted using Toxic unit (TU) approach and persistence, bioaccumulation and toxicity (PBT) ranking. Additionally, influential OCs and genes were identified by graph mining of the prior knowledge informed, site-specific chemical-gene interaction models. Predicted toxicity of sediment extracts (TUext) was similar to the results obtained by ZET and associated histopathology with Rugvica sediment being the most toxic, followed by Jesenice, Lukavec and Galdovo. Sediment TU (TUsed) favoured OCs with low octanol-water partition coefficients like herbicide glyphosate and antibiotics ciprofloxacin and sulfamethazine thus indicating locations containing higher concentrations of these OCs (Galdovo and Rugvica) as the most toxic. Results suggest that comprehensive in silico sediment toxicity predictions advocate providing equal attention to organic contaminants with either very low or very high log Kow.

Item Type: Article
Uncontrolled Keywords: toxicity prediction ; Danio rerio ; pharmaceuticals ; pesticides ; QSAR ; histopathology: sediment
Subjects: NATURAL SCIENCES > Biology
NATURAL SCIENCES > Biology > Ecology
Divisions: Division of Materials Chemistry
Depositing User: Sanja Babić
Date Deposited: 01 Jul 2019 13:10
DOI: 10.1016/j.scitotenv.2018.06.124

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