Machine learning framework for predicting cytotoxicity and identifying toxicity drivers of disinfection byproducts.
J Hazard Mater
; 469: 133989, 2024 May 05.
Article
em En
| MEDLINE
| ID: mdl-38461660
ABSTRACT
Drinking water disinfection can result in the formation disinfection byproducts (DBPs, > 700 have been identified to date), many of them are reportedly cytotoxic, genotoxic, or developmentally toxic. Analyzing the toxicity levels of these contaminants experimentally is challenging, however, a predictive model could rapidly and effectively assess their toxicity. In this study, machine learning models were developed to predict DBP cytotoxicity based on their chemical information and exposure experiments. The Random Forest model achieved the best performance (coefficient of determination of 0.62 and root mean square error of 0.63) among all the algorithms screened. Also, the results of a probabilistic model demonstrated reliable model predictions. According to the model interpretation, halogen atoms are the most prominent features for DBP cytotoxicity compared to other chemical substructures. The presence of iodine and bromine is associated with increased cytotoxicity levels, while the presence of chlorine is linked to a reduction in cytotoxicity levels. Other factors including chemical substructures (CC, N, CN, and 6-member ring), cell line, and exposure duration can significantly affect the cytotoxicity of DBPs. The similarity calculation indicated that the model has a large applicability domain and can provide reliable predictions for DBPs with unknown cytotoxicity. Finally, this study showed the effectiveness of data augmentation in the scenario of data scarcity.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Poluentes Químicos da Água
/
Água Potável
/
Purificação da Água
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Desinfetantes
Limite:
Animals
Idioma:
En
Revista:
J Hazard Mater
Assunto da revista:
SAUDE AMBIENTAL
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Estados Unidos
País de publicação:
HOLANDA
/
HOLLAND
/
NETHERLANDS
/
NL
/
PAISES BAJOS
/
THE NETHERLANDS