Rutaecarpine exhibits anti-diabetic potential in high fat diet–multiple low dose streptozotocin induced type 2 diabetic mice and in vitro by modulating hepatic glucose homeostasis
吴茱萸次碱在高脂饮食-多次低剂量链脲佐菌素诱导的 2 型糖尿病小鼠和体外通过调节肝脏葡萄糖稳态表现出抗糖尿病的潜力
- 作者列表："Laishram Surbala","Chingakham Brajakishor Singh","Rajkumari Vidyabati Devi","Oinam Joychandra Singh
Rutaecarpine, an indolopyridoquinazoline alkaloid, attracted attentions because of possessing various biological activities. The objective of this study was to investigate the effect of rutaecarpine on glucose and lipid metabolism in high fat diet–multiple low dose streptozotocin induced type 2 diabetic (HFD-db) mice and to understand the mechanism of action. HFD-db mice showed impaired glucose metabolism and lipid profile. Oral administration of rutaecarpine reduced the blood glucose levels, decreased blood hemoglobin A1c (HbA1c) levels, improved glucose tolerance and restored insulin sensitivity in HFD-db mice. Rutaecarpine also decreased body weight gain, water intake and visceral fat gain in HFD-db mice. Total cholesterol, triglycerides, very low density lipoprotein and low density lipoprotein were reduced and high density lipoprotein level was augmented in rutaecarpine treated HFD-db mice. Rutaecarpine also reduced the elevated levels of serum glutamic oxaloacetic transaminase, serum glutamic pyruvic transaminase, urea and creatinine in HFD-db mice. Rutaecarpine significantly promoted the rate of glucose consumption, glucose uptake and glycolysis in C2C12 myotubes. Western blotting results showed that rutaecarpine augmented p-GSK-3β and p-AMPK expression, and suppressed G6Pase expression in HepG2 cells. These results suggest that rutaecarpine might be having therapeutic importance to fight against type 2 diabetes mellitus associated with dyslipidemia.
吴茱萸次碱是一种吲哚并喹唑啉类生物碱，因具有多种生物活性而备受关注。本研究旨在探讨吴茱萸次碱对高脂饮食多次小剂量链脲佐菌素诱导的 2 型糖尿病 (HFD-db) 糖脂代谢的影响。小鼠并了解其作用机制。HFD-db 小鼠出现糖代谢和血脂受损。口服吴茱萸次碱可降低 HFD-db 小鼠的血糖水平，降低血血红蛋白 A1c (HbA1c) 水平，改善糖耐量，恢复胰岛素敏感性。吴茱萸次碱还降低了 HFD-db 小鼠的体重增加、水分摄入和内脏脂肪增加。吴茱萸次碱处理的 HFD-db 小鼠总胆固醇、甘油三酯、极低密度脂蛋白和低密度脂蛋白降低，高密度脂蛋白水平升高。吴茱萸次碱还降低了 HFD-db 小鼠血清谷草转氨酶、血清谷丙转氨酶、尿素和肌酐的升高水平。吴茱萸次碱显著促进 C2C12 肌管的葡萄糖消耗、葡萄糖摄取和糖酵解速率。Western blotting 结果显示，吴茱萸次碱增强 HepG2 细胞 p-gsk-3 β 和 p-AMPK 的表达，抑制 G6Pase 的表达。这些结果表明，吴茱萸次碱可能具有对抗与血脂异常相关的 2 型糖尿病的治疗重要性。
METHODS:Aims We aimed to develop a prediction model based on clinical and biochemical variables for gestational diabetes mellitus (GDM) based on the 2013 World Health Organization (WHO) criteria. Methods A total of 1843 women from a Belgian multi-centric prospective cohort study underwent universal screening for GDM. Using multivariable logistic regression analysis, a model to predict GDM was developed based on variables from early pregnancy. The performance of the model was assessed by receiver-operating characteristic (AUC) analysis. To account for over-optimism, an eightfold cross-validation was performed. The accuracy was compared with two validated models (van Leeuwen and Teede). Results A history with a first degree relative with diabetes, a history of smoking before pregnancy, a history of GDM, Asian origin, age, height and BMI were independent predictors for GDM with an AUC of 0.72 [95% confidence interval (CI) 0.69–0.76)]; after cross-validation, the AUC was 0.68 (95% CI 0.64–0.72). Adding biochemical variables, a history of a first degree relative with diabetes, a history of GDM, non-Caucasian origin, age, height, weight, fasting plasma glucose, triglycerides and HbA_1c were independent predictors for GDM, with an AUC of the model of 0.76 (95% CI 0.72–0.79); after cross-validation, the AUC was 0.72 (95% CI 0.66–0.78), compared to an AUC of 0.67 (95% CI 0.63–0.71) using the van Leeuwen model and an AUC of 0.66 (95% CI 0.62–0.70) using the Teede model. Conclusions A model based on easy to use variables in early pregnancy has a moderate accuracy to predict GDM based on the 2013 WHO criteria.
METHODS:Leveraging the availability of nationwide electronic health records from over 500,000 pregnancies in Israel, a machine-learning approach offers an alternative means of predicting gestational diabetes at high accuracy in the early stages of pregnancy. Gestational diabetes mellitus (GDM) poses increased risk of short- and long-term complications for mother and offspring^ 1 – 4 . GDM is typically diagnosed at 24–28 weeks of gestation, but earlier detection is desirable as this may prevent or considerably reduce the risk of adverse pregnancy outcomes^ 5 , 6 . Here we used a machine-learning approach to predict GDM on retrospective data of 588,622 pregnancies in Israel for which comprehensive electronic health records were available. Our models predict GDM with high accuracy even at pregnancy initiation (area under the receiver operating curve (auROC) = 0.85), substantially outperforming a baseline risk score (auROC = 0.68). We validated our results on both a future validation set and a geographical validation set from the most populated city in Israel, Jerusalem, thereby emulating real-world performance. Interrogating our model, we uncovered previously unreported risk factors, including results of previous pregnancy glucose challenge tests. Finally, we devised a simpler model based on just nine questions that a patient could answer, with only a modest reduction in accuracy (auROC = 0.80). Overall, our models may allow early-stage intervention in high-risk women, as well as a cost-effective screening approach that could avoid the need for glucose tolerance tests by identifying low-risk women. Future prospective studies and studies on additional populations are needed to assess the real-world clinical utility of the model.
METHODS::Repurposing of currently approved medications is an attractive option for the development of novel treatment strategies against physiological and infectious diseases. The antidiabetic sulfonylurea glyburide has demonstrated off-target capacity to inhibit activation of the NLRP3 inflammasome in a variety of disease models, including vaginal candidiasis, caused primarily by the fungal pathogen Candida albicans Therefore, we sought to determine which of the currently approved sulfonylurea drugs prevent the release of interleukin 1β (IL-1β), a major inflammasome effector, during C. albicans challenge of the human macrophage-like THP1 cell line. Findings revealed that the second-generation antidiabetics (glyburide, glisoxepide, gliquidone, and glimepiride), which exhibit greater antidiabetic efficacy than prior iterations, demonstrated anti-inflammatory effects with various degrees of potency as determined by calculation of 50% inhibitory concentrations (IC50s). These same compounds were also effective in reducing IL-1β release during noninfectious inflammasome activation (e.g., induced by lipopolysaccharide [LPS] plus ATP), suggesting that their anti-inflammatory activity is not specific to C. albicans challenge. Moreover, treatment with sulfonylurea drugs did not impact C. albicans growth and filamentation or THP1 viability. Finally, the use of ECE1 and Candidalysin deletion mutants, along with isogenic NLRP3-/- cells, demonstrated that both Candidalysin and NLRP3 are required for IL-1β secretion, further confirming that sulfonylureas suppress inflammasome signaling. Moreover, challenge of THP1 cells with synthetic Candidalysin peptide demonstrated that this toxin is sufficient to activate the inflammasome. Treatment with the experimental inflammasome inhibitor MCC950 led to similar blockade of IL-1β release, suggesting that Candidalysin-mediated inflammasome activation can be inhibited independently of potassium efflux. Together, these results demonstrate that the second-generation antidiabetic sulfonylureas retain anti-inflammatory activity and may be considered for repurposing against immunopathological diseases, including vaginal candidiasis.