Silica nanoparticles induce hepatocyte ferroptosis and liver injury <i>via</i> ferritinophagy

Liang, Qiong; Ma, Yanpeng; Wang, Fenghong; Sun, Mengqi; Lin, Lisen; Li, Tianyu; Sun, Zhiwei; Duan, Junchao

doi:10.1039/d2en00116k

Cited by 4 publications

(2 citation statements)

References 56 publications

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“…The final predictive models were used to predict the independent data sets derived from external studies published between 2017 and 2022. ,− Specifically, Gong et al (2017) exposed HaCaT cells to 15 nm SiO 2 -NPs for 24 h (nine samples). Similarly, Liu et al (2017) subjected A549 cells to 15 nm SiO 2 -NPs over a period of 24 h (eight samples), whereas Nishijima et al (2017) put 10–1000 nm SiO 2 -NPs in contact with THP-1 cells for 6–24 h (105 samples).…”

Section: Methodsmentioning

confidence: 99%

“…(2022) subjected HepG2 cells to 20 nm SiO 2 -NPs for a period of 24 h (10 samples). Similarly, Liang et al (2022) observed the effects of 50 nm SiO 2 -NPs on L-02 cells for 24 h (seven samples). Finally, Ma et al (2022) exposed BEAS-2B cells to 51.58 nm SiO 2 -NPs for 24 h (six samples), and Zhang et al (2022) subjected R28 cells to 15- and 50 nm SiO 2 -NPs for periods of 12 and 24 h (20 samples).…”

Section: Methodsmentioning

confidence: 99%

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Evidence-Based Prediction of Cellular Toxicity for Amorphous Silica Nanoparticles

et al. 2023

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Developing a generalized model for a robust prediction of nanotoxicity is critical for designing safe nanoparticles. However, complex toxicity mechanisms of nanoparticles in biological environments, such as biomolecular corona formation, prevent a reliable nanotoxicity prediction. This is exacerbated by the potential evaluation bias caused by internal validation, which is not fully appreciated. Herein, we propose an evidence-based prediction method for distinguishing between cytotoxic and noncytotoxic nanoparticles at a given condition by uniting literature data mining and machine learning. We illustrate the proposed method for amorphous silica nanoparticles (SiO2-NPs). SiO2-NPs are currently considered a safety concern; however, they are still widely produced and used in various consumer products. We generated the most diverse attributes of SiO2-NP cellular toxicity to date, using >100 publications, and built predictive models, with algorithms ranging from linear to nonlinear (deep neural network, kernel, and tree-based) classifiers. These models were validated using internal (4124-sample) and external (905-sample) data sets. The resultant categorical boosting (CatBoost) model outperformed other algorithms. We then identified 13 key attributes, including concentration, serum, cell, size, time, surface, and assay type, which can explain SiO2-NP toxicity, using the Shapley Additive exPlanation values in the CatBoost model. The serum attribute underscores the importance of nanoparticle–corona complexes for nanotoxicity prediction. We further show that internal validation does not guarantee generalizability. In general, safe SiO2-NPs can be obtained by modifying their surfaces and using low concentrations. Our work provides a strategy for predicting and explaining the toxicity of any type of engineered nanoparticles in real-world practice.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Evidence-Based Prediction of Cellular Toxicity for Amorphous Silica Nanoparticles

et al. 2023

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International consensus guidelines for the definition, detection, and interpretation of autophagy-dependent ferroptosis

Chen,

Tsvetkov,

Shen

et al. 2024

Autophagy

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Ferritinophagy was involved in long-term SiNPs exposure induced ferroptosis and liver fibrosis

Liang

Wang

et al. 2023

Nanotoxicology

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Silica nanoparticles induce hepatocyte ferroptosis and liver injury via ferritinophagy

Abstract: As one of the most mass-produced and extensively used engineered nanomaterials, silica nanoparticles (SiNPs) have gained attention to their environmental health and safety (EHS) concerns because of the increasing exposure...

Cited by 4 publications

References 56 publications

Evidence-Based Prediction of Cellular Toxicity for Amorphous Silica Nanoparticles

Evidence-Based Prediction of Cellular Toxicity for Amorphous Silica Nanoparticles

International consensus guidelines for the definition, detection, and interpretation of autophagy-dependent ferroptosis

Ferritinophagy was involved in long-term SiNPs exposure induced ferroptosis and liver fibrosis

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