ACTA ENDOCRINOLOGICA (BUC)

Objective. To observe the impact of quercetin and isoquercitrin on gluconeogenesis in hepatocytes. Methods. Mouse primary hepatocytes were cultured with lactic acid and pyruvic acid. After treatment with quercetin and isoquercitrin for 24 hours, the glucose concentration in the culture supernatant was determined. RT-PCR was used to detect the mRNAs of PEPCK, G6Pase, LKB1, and AMPKα. Protein levels of LKB1, AMPKα, and Thr172 phosphorylation were evaluated by Western blot. Results. The glucose concentration in the gluconeogenesis group (GN) was significantly higher than in the control group (C), but the glucose concentrations in the high level quercetin(group 80Q) and high level isoquercitrin (group 80I) were significantly lower than in the group GN, P<0.01. In the group 80Q, and group 80I, the mRNA levels of PEPCK and LKB1were significantly lower than in the group GN (P<0.01), and the G6Pase mRNA were significantly lower than in the group GN (P<0.05). The protein levels of LKB1 and the phosphorylation of AMPKα Thr172 in the group 80Q, group 40I, and group 80I were higher than in the group GN. The effects of quercetin and isoquercitrin on LKB1 and AMPKα were similar to those of metformin. Conclusions. Quercetin and isoquercitrin inhibit gluconeogenesis in hepatocytes, which may be related to the LKB1 upregulation and phosphorylation of AMPKα.

Aim. To evaluate the diagnostic performance of radiomics features of two-dimensional (2D) and threedimensional (3D) ultrasound (US) in predicting extrathyroidal extension (ETE) status in papillary thyroid carcinoma (PTC). Patients and Methods. 2D and 3D thyroid ultrasound images of 72 PTC patients confirmed by pathology were retrospectively analyzed. The patients were assigned to ETE and non-ETE. The regions of interest (ROIs) were obtained manually. From these images, a larger number of radiomic features were automatically extracted. Lastly, the diagnostic abilities of the radiomics models and a radiologist were evaluated using receiver operating characteristic (ROC) analysis. We extracted 1693 texture features firstly. Results. The area under the ROC curve (AUC) of the radiologist was 0.65. For 2D US, the mean AUC of the three classifiers separately were: 0.744 for logistic regression (LR), 0.694 for multilayer perceptron (MLP), 0.733 for support vector machines (SVM). For 3D US they were 0.876 for LR, 0.825 for MLP, 0.867 for SVM. The diagnostic efficiency of the radiomics was better than radiologist. The LR model had favorable discriminate performance with higher area under the curve. Conclusion. Radiomics based on US image had the potential to preoperatively predict ETE. Radiomics based on 3D US images presented more advantages over radiomics based on 2D US images and radiologist.