Cognitive impairment is a prevalent but underestimated complication of diabetes, which can cause spatial memory and learning deficits. In the present study, a streptozotocin-induced type 2 diabetic rat model was employed to investigate the effects of vildagliptin, a new oral hypoglycemic agent that acts by inhibiting dipeptidyl peptidase-4, on diabetes-associated cognitive impairments, as well as the molecular mechanisms involved. The present findings demonstrated that vildagliptin treatment prevented memory impairment and decreased the apoptosis of hippocampal neurons. It also attenuated the abnormal expression of caspase-3, B cell lymphoma-2 (Bcl-2) and Bcl-2 associated X protein in the diabetic model. Vildagliptin treatment also reversed diabetes-induced decreases in phosphorylated (p)-protein kinase B (Akt) and p-glycogen synthase kinase 3β (GSK3β), brain-derived neurotrophic factor and nerve growth factor expression levels. The results indicated that the administration of vildagliptin exerts a protective effect against cognitive deficits by decreasing the expression of apoptosis-related proteins in the hippocampus and that this protective effect was mediated via the Akt/GSK3β signaling pathway.

to their diagnostic results at 24-28 weeks of pregnancy. Univariate analysis was performed to investigate the significance of the maternal clinical parameters for GDM diagnosis and a GDM prediction model was established using stepwise regression analysis. The predictive value of the model was evaluated using a Homer-Lemeshow goodness-of-fit test and a receiver operating characteristic curve (ROC). The model demonstrated that age, pre-pregnancy body mass index, a family history of diabetes mellitus, polycystic ovary syndrome, a history of GDM, high systolic pressures, glycosylated hemoglobin levels, triglyceride levels, total cholesterol levels, low-density lipoprotein cholesterol levels, serum hypersensitive C-reactive protein, increased subcutaneous fat thickness and visceral fat thickness were all correlated with an increased GDM risk (all P<0.01). The area under the curve value was 0.911 (95% CI, 0.893-0.930). Overall, the results indicated that the current model, which included ultrasound and serological data, may be a more effective predictor of GDM compared with other single predictor models. In conclusion, the present study developed a tool to determine the risk of GDM in pregnant women during the second trimester. This prediction model, based on various risk factors, demonstrated a high predictive value for the GDM occurrence in pregnant women in China and may prove useful in guiding future clinical practice.