The association between serum Sestrin2 and the risk of coronary heart disease in patients with type 2 diabetes mellitus.

BACKGROUND: Coronary heart disease (CHD) is one of the most common causes of morbidity and mortality in type 2 diabetes mellitus (T2DM). Oxidative stress is one of the important contributors to the pathogenesis of CHD. Sestrin2 is a stress-induced antioxidant protein that plays a important role in T2DM and CHD. However, the relationship between serum Sestrin2 levels and T2DM with CHD remains unclear. AIM: This study aimed to investigate the relationship between serum Sestrin2 levels and CHD in patients with type 2 diabetes. METHODS: A total of 70 T2DM patients with CHD and 69 T2DM patients were enrolled in this study. Clinical features and metabolic indices were identified. Serum Sestrin2 was measured by ELISA. RESULTS: Serum Sestrin2 levels in T2DM-CHD groups were significantly lower compared with the T2DM group (11.17 (9.79, 13.14) ng/mL vs 9.46 (8.34, 10.91) ng/mL). Bivariate correlation analysis revealed that serum Sestrin2 levels were negatively correlated with age (r = - 0.256, P = 0.002), BMI (r = - 0.206, P = 0.015), FBG (r = - 0.261, P = 0.002) and Tyg index (r = - 0.207, P < 0.014). Binary logistic regression suggested that low serum Sestrin2 levels were related to the increased risk of T2DM-CHD (P < 0.05). In addition, the receiver operating characteristic analysis revealed that the area under the curve of Sestrin2 was 0.724 (95% CI 0.641-0.808, P < 0.001) to predict T2DM-CHD patients (P < 0.001). CONCLUSION: The Sestrin2 levels were highly associated with CHD in diabetes patients. Serum Sestrin2 may be involved in the occurrence and development of diabetic with CHD.

GLP­1 receptor agonist protects palmitate-induced insulin resistance in skeletal muscle cells by up-regulating sestrin2 to promote autophagy.

In this study, we aimed to determine whether liraglutide could effectively reduce insulin resistance (IR) by regulating Sestrin2 (SESN2) expression in L6 rat skeletal muscle cells by examining its interactions with SESN2, autophagy, and IR. L6 cells were incubated with liraglutide (10-1000 nM) in the presence of palmitate (PA; 0.6 mM), and cell viability was detected using the cell counting kit-8 (CCK-8) assay. IR-related and autophagy-related proteins were detected using western blotting, and IR and autophagy-related genes were analyzed using quantitative real-time polymerase chain reaction. Silencing SESN2 was used to inhibit the activities of SESN2. A reduction in insulin-stimulated glucose uptake was observed in PA-treated L6 cells, confirming IR. Meanwhile, PA decreased the levels of GLUT4 and phosphorylation of Akt and affected SESN2 expression. Further investigation revealed that autophagic activity decreased following PA treatment, but that liraglutide reversed this PA-induced reduction in autophagic activity. Additionally, silencing SESN2 inhibited the ability of liraglutide to up-regulate the expression of IR-related proteins and activate autophagy signals. In summary, the data showed that liraglutide improved PA-induced IR in L6 myotubes by increasing autophagy mediated by SESN2.

Application of machine learning tools: Potential and useful approach for the prediction of type 2 diabetes mellitus based on the gut microbiome profile.

The gut microbiota plays an important role in the regulation of the immune system and the metabolism of the host. The aim of the present study was to characterize the gut microbiota of patients with type 2 diabetes mellitus (T2DM). A total of 118 participants with newly diagnosed T2DM and 89 control subjects were recruited in the present study; six clinical parameters were collected and the quantity of 10 different types of bacteria was assessed in the fecal samples using quantitative PCR. Taking into consideration the six clinical variables and the quantity of the 10 different bacteria, 3 predictive models were established in the training set and test set, and evaluated using a confusion matrix, area under the receiver operating characteristic curve (AUC) values, sensitivity (recall), specificity, accuracy, positive predictive value and negative predictive value (npv). The abundance of Bacteroides, Eubacterium rectale and Roseburia inulinivorans was significantly lower in the T2DM group compared with the control group. However, the abundance of Enterococcus was significantly higher in the T2DM group compared with the control group. In addition, Faecalibacterium prausnitzii, Enterococcus and Roseburia inulinivorans were significantly associated with sex status while Bacteroides, Bifidobacterium, Enterococcus and Roseburia inulinivorans were significantly associated with older age. In the training set, among the three models, support vector machine (SVM) and XGboost models obtained AUC values of 0.72 and 0.70, respectively. In the test set, only SVM obtained an AUC value of 0.77, and the precision and specificity were both above 0.77, whereas the accuracy, recall and npv were above 0.60. Furthermore, Bifidobacterium, age and Roseburia inulinivorans played pivotal roles in the model. In conclusion, the SVM model exhibited the highest overall predictive power, thus the combined use of machine learning tools with gut microbiome profiling may be a promising approach for improving early prediction of T2DM in the near feature.

Characteristics of Gut Microbiota in Female Patients with Diabetic Microvascular Complications.

Objective: To explore the characteristics and analyze the gut microbiota in female patients with diabetic microvascular complications (DMC). Methods: Thirty-seven female patients with type 2 diabetes mellitus (T2DM) were included in the study. These patients were divided into DM group with microvascular complications (T2DM-MC, n = 17) and no microvascular complications group (T2DM-0, n = 20). Patients in the microvascular group presented with the involvement of at least one of the following: kidney, retinal, or peripheral nerves. Using real-time fluorescence quantitative polymerase chain reaction, fecal samples from the two groups were tested for Bacteroides, Prevotella, Bifidobacterium spp, Lactobacillus, Faecalibacterium prausnitzii, Enterococcus spp, Eubacterium rectale, Veillonellaceae, Clostridium leptum, and Roseburia inulinivorans. Levels of fasting and 2 h postprandial blood glucose, glycosylated hemoglobin (HbA1c), lipids, and creatinine were determined to explore the correlation between gut microbiota and blood sugar. Mann-Whitney U test was used to analyze the differences between the two groups. Spearman correlation analysis was used to determine the correlation between gut microbiota and blood glucose. Multifactor logistic regression was used to analyze the risk factors for DMC. Results: The HbA1c levels in the T2DM-MC group were higher than those in the T2DM-0 group. The abundances of Bacteroides and Enterococcus spp in the T2DM-MC group were higher than that in the T2DM-0 group. The abundances of Bacteroides and Enterococcus spp in the T2DM-MC group were lower than that in the T2DM-0 group. Spearman's correlation analysis showed that Bacteroides, Prevotella, Lactobacillus, C. leptum, and R. inulinivorans were related to the levels of HbA1c or blood glucose (p < 0.05). Logistic regression analysis showed that after adjusting for confounding factors such as age, body mass index, family history, HbA1c, hypertension, dyslipidemia, and creatinine, Bacteroides remained an independent risk factor in female patients with DMC. Conclusion: Gut microbiota is related to blood glucose levels. Female patients with DMC experience gut microbiota disorders. The abundances of Bacteroidesare related to DMC, and the abundances of intestinal flora may affect the blood sugar levels of the body.

Doege-Potter syndrome: A review of the literature including a new case report.

RATIONALE: We reviewed 76 published cases of Doege-Potter syndrome, and non-islet cell tumor hypoglycemia (NICTH) secondary to a solitary fibrous tumor (SFT) between 1989 and 2016, to study disease pathogenesis, diagnosis, and treatment of this rare paraneoplastic disease. Further, we report 1 new case of a patient presenting with Doege-Potter syndrome. PATIENTS CONCERNS: The tumors originated from the pleural cavity, lung, pelvis, liver, retroperitoneum, kidney, mediastinal, the sella, uterus, bladder, intestine, mandibular, and the thigh. The most common location was the pleural cavity (left 12 cases and right 28 cases). Moreover, 28/71 (39.4%) were benign and 43/71 (60.6%) were malignant. SFTs with NICTH were more likely to be malignant and present at a higher rate than previously published (5%-10.4%). The malignancy rate of extrathoracic SFTs was higher than that of thoracic SFTs, 20 (66.7%) as compared with 23 (56.1%). Age of onset varied from 24 to 85 years (mean 59 years), with 47 males and 28 females, and gender unavailable for 1 case. When comparing clinical characteristics of patients with benign as compared malignant tumors, no significant differences in the age of onset, gender, or size of tumor were seen. Among 15/19 cases, the insulin-like growth factor II (IGF-II)/IGF-I ration was >10.0. Complete tumor resection remained the only definitive treatment. OUTCOMES AND LESSENS: Glucocorticoids dose-dependently reduce the frequency and severity of hypoglycemic episodes. Low doses of prednisone were ineffective at relieving hypoglycemia. The effect of neoadjuvant treatment, consisting of chemoradiation, and consecutive selective embolization of vessels feeding the tumor were not identified.