Nano-QTTR development for interspecies aquatic toxicity of silver nanoparticles between daphnia and fish

被引:7
|
作者
Jung, Ukhyun [1 ]
Lee, Byongcheun [2 ]
Kim, Geunbae [2 ]
Shin, Hyun Kil [3 ]
Kim, Ki-Tae [1 ]
机构
[1] Seoul Natl Univ Sci & Technol, Dept Environm Engn, Seoul 01811, South Korea
[2] Natl Inst Environm Res, Risk Assessment Div, Incheon 22689, South Korea
[3] Korea Inst Toxicol, Dept Predict Toxicol, Daejeon 34114, South Korea
基金
新加坡国家研究基金会;
关键词
QSAR; QTTR; Silver nanoparticles; Interspecies toxicity; Daphnia; Fish; METAL-OXIDE NANOPARTICLES; QUASI-SMILES; PREDICTION; CYTOTOXICITY; MODEL; QSAR; APPLICABILITY; MECHANISMS;
D O I
10.1016/j.chemosphere.2021.131164
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Limited studies of quantitative toxicity-toxicity relationship (QTTR) modeling have been conducted to predict interspecies toxicity of engineered nanomaterials (ENMs) between aquatic test species. A meta-analysis of 66 publications providing acute toxicity data of silver nanoparticles (AgNPs) to daphnia and fish was performed, and the toxicity data, physicochemical properties, and experimental conditions were collected and curated. Based on Euclidean distance (ED) grouping, a meaningful correlation of logarithmic lethal concentrations between daphnia and fish was derived for bare (R-bare(2) = 0.47) and coated AgNPs (R-coated(2) = 0.48) when a distance of 10 was applied. The correlation of coated AgNPs was improved (R-coated( )2= 0.55) by the inclusion of descriptors of the coating materials. The correlations were further improved by R-bare (2)= 0.57 and R-coated(2) = 0.81 after additionally considering particle size only, and by R-bare(2) = 0.59 and R-coated(2) = 0.92 after considering particle size and zeta potential simultaneously. The developed ED-based nano-QTTR model demonstrated that inclusion of the coating material descriptors and physicochemical properties improved the goodness-of-fit to predict interspecies aquatic toxicity of AgNPs between daphnia and fish. This study provides insight for future in silico research on QTTR model development in ENM toxicology.
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页数:8
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