Carnitine palmitoyltransferase 1A (CPT1A) is a potential therapeutic target for several cancers. The inhibition of CPT1A has anticancer effects. Teglicar is a new reversible CPT1A inhibitor. The aim of this research was to expound the effect of teglicar in cervical cancer cells. Cell proliferation was conducted using the CCK8 assay. The apoptotic rate was examined by Annexin V-APC/PI staining and flow cytometry. The expression levels of apoptosis-related proteins and endoplasmic reticulum (ER) stress-related proteins were determined by western blot assay. Teglicar was found to inhibit the proliferation of HeLa cells in a dose-dependent manner, with an IC 50 value of 18.38 lM at 24 h. The apoptotic rate of HeLa cells was significantly increased following treatment with teglicar. Western blot analysis indicated that the treatment of teglicar enhanced ER stress and apoptosis in HeLa cells. However, inhibition of proliferation and enhancement of apoptosis in teglicar-treated HeLa cells was reversed by 4-PBA. These results revealed that teglicar promoted apoptosis of HeLa cells via ER stress.
BackgroundIn recent years, AI has been applied to disease diagnosis in many medical and engineering researches. We aimed to explore the diagnostic performance of the models based on different imaging modalities for ovarian cancer.MethodsPubMed, EMBASE, Web of Science, and Wanfang Database were searched. The search scope was all published Chinese and English literatures about AI diagnosis of benign and malignant ovarian tumors. The literature was screened and data extracted according to inclusion and exclusion criteria. Quadas-2 was used to evaluate the quality of the included literature, STATA 17.0. was used for statistical analysis, and forest plots and funnel plots were drawn to visualize the study results.ResultsA total of 11 studies were included, 3 of them were modeled based on ultrasound, 6 based on MRI, and 2 based on CT. The pooled AUROCs of studies based on ultrasound, MRI and CT were 0.94 (95% CI 0.88-1.00), 0.82 (95% CI 0.71-0.93) and 0.82 (95% Cl 0.78-0.86), respectively. The values of I2 were 99.92%, 99.91% and 92.64% based on ultrasound, MRI and CT. Funnel plot suggested no publication bias.ConclusionThe models based on ultrasound have the best performance in diagnostic of ovarian cancer.
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