PUBLICATION

Toxicity assessment and i-QSTTR analysis of ionic liquids on D. magna, D. rerio, and R. subcapitata

Authors
Guan, R., Li, N., Cai, R., Guo, B., Wang, Q., Li, D., Zhao, C.
ID
ZDB-PUB-250114-1
Date
2025
Source
The Science of the total environment   958: 178029178029 (Journal)
Registered Authors
Keywords
Interspecies quantitative structure-toxicity-toxicity (i-QSTTR), Ionic liquids, Machine learning, Quantitative structure-activity relationship (QSAR), Toxic response
MeSH Terms
  • Quantitative Structure-Activity Relationship*
  • Ionic Liquids*/toxicity
  • Machine Learning
  • Animals
  • Toxicity Tests
  • Daphnia*/drug effects
  • Zebrafish*
  • Water Pollutants, Chemical*/toxicity
PubMed
39708752 Full text @ Sci. Total Environ.
Abstract
The study aimed to assess the impacts of ionic liquids (ILs) as innovative alternatives to traditional organic solvents on aquatic environments and human health. Five machine learning methods, including multiple linear regression (MLR), partial least squares regression (PLS), random forest regression (RF), support vector regression (SVR), and extreme gradient boosting (XGBoost), were used to construct the prediction models of the toxicity of ILs to D. magna, D. rerio, and R. subcapitata. Rigorous validation criteria were implemented to evaluate the robustness and predictive accuracy of these models. The results indicated SVR and XGBoost models demonstrated superior predictive performance. In addition, for these three species of D. magna, D. rerio, and R. subcapitata. The six interspecies quantitative structure-toxicity-toxicity (i-QSTTR) models were developed to analyze the cross-species toxicity responses of ILs. The results revealed a strong interspecies correlation in the toxicity of ILs to D. magna and D. rerio, as well as between D. rerio and R. subcapitata. However, the correlation between D. magna and R. subcapitata was weaker, indicating significant differences in the responses of ILs toxicity between these two aquatic species. This study not only filled the data gap in the biotoxicity of ILs but also provided an important theoretical basis for their safe application.
Genes / Markers
Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping