Concerns regarding chronic injuries (e.g., fibrosis and carcinogenesis) induced by nanoparticles raised public health concerns and need to be rapidly assessed in hazard identification. Although in silico analysis is commonly used for risk assessment of chemicals, predicting chronic in vivo nanotoxicity remains challenging due to the intricate interactions at multiple interfaces like nano-biofluids and nano-subcellular organelles. Herein, we develop a multimodal feature fusion analysis framework to predict the fibrogenic potential of metal oxide nanoparticles (MeONPs) in female mice. Treating each nano-bio interface as an independent entity, eighty-seven features derived from MeONP-lung interactions are used to develop a machine learning-based predictive framework for lung fibrosis. We identify cell damage and cytokine (IL-1β and TGF-β1) production in macrophages and epithelial cells as key events closely associated with particle size, surface charge, and lysosome interactions. Experimental validations show that the developed in silico model has 85% accuracy. Our findings demonstrate the potential usefulness of this predictive model for risk assessment of nanomaterials and in assisting regulatory decision-making. While the model is developed based on 52 MeONPs, further validation using a larger nanoparticle library is necessary to confirm its broader applicability.

• MeSH
• epitelové buňky účinky léků   metabolismus   MeSH
• hodnocení rizik MeSH
• interleukin-1beta metabolismus   MeSH
• kovové nanočástice * toxicita   chemie   MeSH
• lidé MeSH
• makrofágy účinky léků   metabolismus   MeSH
• myši inbrední C57BL MeSH
• myši MeSH
• nanostruktury * toxicita   MeSH
• oxidy toxicita   chemie   MeSH
• plíce účinky léků   patologie   metabolismus   MeSH
• plicní fibróza * chemicky indukované   patologie   MeSH
• strojové učení * MeSH
• transformující růstový faktor beta1 metabolismus   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• myši MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• interleukin-1beta MeSH
• oxidy MeSH
• transformující růstový faktor beta1 MeSH