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Updated: Jan 31, 2026

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机器学习引导的Nano-QSAR建模预测了HepaRG细胞膜毒性工程纳米粒子的机械洞察力

Xinyu Hao1, Ting Ren1, Shuo Chen1

  • 1Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, P. R. China.

Cell biology and toxicology
|January 29, 2026
PubMed
概括

本研究介绍了Nano-QSAR模型,通过评估细胞膜损伤来预测工程纳米粒子 (ENP) 毒性. 这些模型为ENP提供可靠的毒性评估,对于人类健康风险评估至关重要.

关键词:
细胞膜损伤导致细胞膜损伤.欧洲留学计划 (ENP) 是一个欧洲留学计划.机器学习是机器学习.在纳米-QSAR.毒性预测 毒性预测

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