AIMC Topic: Epithelial Cells

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Quantitative scoring of epithelial and mesenchymal qualities of cancer cells using machine learning and quantitative phase imaging.

Journal of biomedical optics
SIGNIFICANCE: We introduce an application of machine learning trained on optical phase features of epithelial and mesenchymal cells to grade cancer cells' morphologies, relevant to evaluation of cancer phenotype in screening assays and clinical biops...

[Toxicity of vehicle exhaust on BEAS-2B cells in vitro by air-liquid interface].

Wei sheng yan jiu = Journal of hygiene research
OBJECTIVE: To evaluate the toxic effect of vehicle exhaust( VE) on lung epithelial cells by air-liquid interface( ALI) method in vitro, and analyze the different toxicity of VE after being treated with 0. 2 μm filter.

Identification of human flap endonuclease 1 (FEN1) inhibitors using a machine learning based consensus virtual screening.

Molecular bioSystems
Human Flap endonuclease1 (FEN1) is an enzyme that is indispensable for DNA replication and repair processes and inhibition of its Flap cleavage activity results in increased cellular sensitivity to DNA damaging agents (cisplatin, temozolomide, MMS, e...

[The Protective Effect of Inhibition of PARP-1 on Inflammation Induced by PM2.5 in Human Bronchial Epithelial Cell Line.].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVES: To explore whether the inhibition of poly ADP-ribose polymerase-1(PARP-1) could attenuated inflammation induced by fine particulate matter (PM2.5) in human bronchial epithelial cell line.

[Oxidative stress and mitochondrion-related cell apoptosis in human bronchial epithelial 16HBE cells induced by silica dust].

Zhonghua lao dong wei sheng zhi ye bing za zhi = Zhonghua laodong weisheng zhiyebing zazhi = Chinese journal of industrial hygiene and occupational diseases
OBJECTIVE: To investigate oxidative stress and mitochondria-related cell apoptosis induced by silica dust in human normal bronchial epithelial 16HBE cells.