Mechanisms Of Insulin Resistance In The Amygdala: Influences On Food Intake.

Obesity is increasing worldwide and is triggered, at least in part, by enhanced caloric intake. Food intake is regulated by a complex mechanism involving the hypothalamus and hindbrain circuitries. However, evidences have showing that reward systems are also important in regulating feeding behavior. In this context, amygdala is considered a key extra-hypothalamic area regulating feeding behavior in human beings and rodents. This review focuses on the regulation of food intake by amygdala and the mechanisms of insulin resistance in this brain area. Similar to the hypothalamus the anorexigenic effect of insulin is mediated via PI3K (phosphoinositide 3-kinase)/Akt (protein kinase B) pathway in the amygdala. Insulin decreases NPY (neuropeptide Y) and increases oxytocin mRNA levels in the amygdala. High fat diet and saturated fatty acids induce inflammation, ER (endoplasmic reticulum) stress and the activation of serine kinases such as PKCθ (protein kinase C theta), JNK (c-Jun N-terminal kinase) and IKKβ (inhibitor of nuclear factor kappa-B kinase beta) in the amygdala, which have an important role in insulin resistance in this brain region. Overexpressed PKCθ in the CeA (central nucleus of amygdala) of rats increases weight gain, food intake, insulin resistance and hepatic triglycerides content. The inhibition of ER stress ameliorates insulin action/signaling, increases oxytocin and decreases NPY gene expression in the amygdala of high fat feeding rodents. Those data suggest that PKCθ and ER stress are main mechanisms of insulin resistance in the amygdala of obese rats and play an important role regulating feeding behavior.

Jnk And Ikkβ Phosphorylation Is Reduced By Glucocorticoids In Adipose Tissue From Insulin-resistant Rats.

Peripheral insulin resistance (IR) is one of the main side effects caused by glucocorticoid (GC)-based therapies, and the molecular mechanisms of GC-induced IR are not yet fully elucidated. Thus, we aimed to investigate the effects of dexamethasone treatment on the main components of insulin and inflammatory signaling in the adipose tissue of rats. Male Wistar rats received daily injections of dexamethasone (1mg/kg body weight (b.w.), intraperitoneally (i.p.)) for 5 days (DEX), whereas control rats received saline (CTL). The metabolic status was investigated, and the epididymal fat fragments were collected for lipolysis and western blot analyses. The DEX rats became hyperglycemic, hyperinsulinemic, insulin resistant and glucose intolerant, compared with the CTL rats (P<0.05). The basal glycerol release in the fat fragments was 1.5-fold higher in the DEX rats (P<0.05). The phosphorylation of protein kinase B (PKB) at ser(473) decreased by 44%, whereas, the phosphorylation of insulin receptor substrate (IRS)-1 at ser(307) increased by 93% in the adipose tissue of the DEX rats after an oral bolus of glucose (P<0.05). The basal phosphorylation of c-jun-N-terminal kinase (JNK) and inhibitor of nuclear factor kappa-B (IKKβ) proteins was reduced by 46% and 58%, respectively, in the adipose tissue of the DEX rats (P<0.05). This was paralleled with a significant reduction (47%) in the glucocorticoid receptor (GR) protein content in the adipose tissue of the DEX rats (P<0.05). The insulin-resistant status of rats induced by dexamethasone administration have PKB and IRS-1 activity attenuated in epididymal fat without increases in the phosphorylation of the proinflammatory signals JNK and IKKβ.

High Prevalence Of Insulin Resistance Assessed By The Glucose Clamp Technique In Hormonal And Non-hormonal Contraceptive Users.

Objective To assess the prevalence of insulin resistance (IR) and associated factors in contraceptive users. Methods A total of 47 women 18 to 40 years of age with a body mass index (kg/m(2)) < 30, fasting glucose levels < 100 mg/dl and 2-hour glucose level < 140 mg/dl after a 75-g oral glucose load were submitted to a hyperinsulinemic-euglycemic clamp. The women were distributed in tertiles regarding M-values. The analysed variables were use of combined hormonal/non-hormonal contraception, duration of use, body composition, lipid profile, glucose levels and blood pressure. Results IR was detected in 19% of the participants. The women with low M-values presented significantly higher body fat mass, waist-to-hip ratio, fasting insulin, HOMA-IR and were nulligravida, showed > 1 year of contraceptive use and higher triglyceride levels. IR was more frequent among combined oral contraceptive users, however no association was observed after regression analysis. Conclusions The prevalence of IR was high among healthy women attending a family planning clinic independent of the contraceptive method used with possible long-term negative consequences regarding their metabolic and cardiovascular health. Although an association between hormonal contraception and IR could not be found this needs further research. Family planning professionals should be proactive counselling healthy women about the importance of healthy habits.

Comparison between the 1% and 2% ibopamine provocative test in primary open-angle glaucoma patients: sensitivity, specificity and tolerability

PURPOSE: To compare intraocular pressure (IOP) rise in normal individuals and primary open-angle glaucoma patients and the safety and efficacy of ibopamine eye drops in different concentrations as a provocative test for glaucoma. METHODS: Glaucoma patients underwent (same eye) the ibopamine provocative test with two concentrations, 1% and 2%, in a random sequence at least 3 weeks apart, but not more than 3 months. The normal individuals were randomly submitted to one of the concentrations of ibopamine (1% and 2%). The test was considered positive if there was an IOP rise greater than 3 or 4 mmHg at 30 or 45 minutes to test which subset of the test has the best sensitivity (Se)/specificity (Sp). RESULTS: There was no statistically significant difference in any of the IOP measurements, comparing 1% with 2% ibopamine. The IOP was significantly higher at 30 and 45 minutes with both concentrations (p<0.001). The best sensitivity/specificity ratio was achieved with the cutoff point set as greater than 3 mmHg at 45 minutes with 2% ibopamine (area under the ROC curve: 0.864, Se: 84.6%; Sp:73.3%). All patients described a slight burning after ibopamine's instillation. CONCLUSION: 2% ibopamine is recommended as a provocative test for glaucoma. Because both concentrations have similar ability to rise IOP, 1% ibopamine may be used to treat ocular hypotony.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.