[ ABSTRACT] AIM:To investigate the effects of c-Met on the proliferation and the sensitivity to chemotherapeutic drugs of triple negative breast cancer cells.METHODS: Doxorubicin-resistant cells ( MDA-MB-231/ADR) were estab-lished.The expression of c-Met at mRNA and protein levels in the MDA-MB-231/ADR cells and parental MDA-MB-231 cells was detected by real-time PCR and Western blotting.c-Met siRNA and plasmid or AKT siRNA were transfected into the cancer cells.The cell proliferation and the sensitivity to doxorubicin were determined by MTT assay.RESULTS:The expression of c-Met at mRNA and protein levels in MDA-MB-231/ADR cells was significantly higher than that in parental MDA-MB-231 cells.Transfection with pBABE-puro TPR-MET plasmid into the MDA-MB-231 cells induced cell prolifera-tion and resistance to doxorubicin.Meanwhile, inhibition of c-Met in the MDA-MB-231/ADR cells by siRNA reversed the doxorubicin-resistance.In addition, over-expression of c-Met led to higher phosphorylation level of AKT, which was in-volved in the effects of c-Met on the MDA-MB-231 cell proliferation and doxorubicin-resistance.CONCLUSION: c-Met may have the potential as a therapeutic target in the treatment of triple negative breast cancer.

In recent years,deep learning,a pivotal subset of artificial intelligence machine learning,has achieved noteworthy advancements in the medical domain.It facilitates precise detection,diagnosis and prognostic assessment of various diseases through the analysis of medical images.Within ophthalmology,deep learning techniques have found wide-spread application in the diagnosis and prediction of thyroid-related eye diseases,orbital blowout fracture,melanoma,bas-al cell carcinoma,orbital abscess,lymphoma,retinoblastoma and other diseases.Leveraging images from computed tomo-graphy,magnetic resonance imaging and even pathological sections,this technology demonstrates a capacity to diagnose,differentiate and stage orbital diseases and ocular tumors with a high level of accuracy comparable to that of expert clini-cians.The promising prospects of this technology are expected to enhance the diagnosis and treatment of related diseases,concurrently reducing the time and cost associated with clinical practices.This review consolidates the latest research pro-gress on the application of artificial intelligence deep learning in orbital diseases and ocular tumors,aiming to furnish clini-cians with up-to-date information and developmental trends in this field,thereby furthering the clinical application and widespread adoption of this technology.