Endocrinologia Y Nutricion最新文献

Background and objective

The triglyceride/HDL cholesterol ratio, as a surrogate marker of insulin resistance, may be associated to presence of subclinical carotid atherosclerosis in postmenopausal women. The aim of this study was to explore this association.

Patients and methods

Women (last menstrual period ≥ 2 years) in primary prevention up to 65 years of age were recruited. Association between the triglyceride/HDL cholesterol (HDL-C) ratio and presence of carotid plaque, assessed by ultrasonography, was analyzed. ROC analysis was performed, determining the precision of this ratio to detect carotid plaque.

Results

A total of 332 women (age 57 ± 5 years) were recruited. Triglyceride/HDL-C ratio was 2.35 ± 1.6. Prevalence of carotid plaque was 29%. Women with carotid plaque had higher triglyceride/HDL-C ratios (3.33 ± 1.96 vs. 2.1 ± 1.2, p < 0.001) than women with no carotid plaque. A positive relationship was seen between quintiles of this ratio and prevalence of carotid plaque (p < 0.001). Regardless of other risk factors, women with higher triglyceride/HDL-C ratios were more likely to have carotid plaque (odds ratio 1.47, 95% confidence interval 1.20–1.79, p < 0.001). The area under the curve of the triglyceride/HDL-C ratio to detect carotid plaque was 0.71 (95% confidence interval 0.65 to 0.76), and the optimal cut-off point was 2.04.

Conclusions

In postmenopausal women in primary prevention, insulin resistance, estimated from the triglyceride/HDL-C ratio, was independently associated to a greater probability of carotid plaque. A value of such ratio greater than 2 may be used for assessing cardiovascular risk in this particular group of women.

Most research in diabetes mellitus (DM) has been conducted in animals, and their replacement is currently a chimera. As compared to when they started to be used by modern science in the 17th century, a very high number of animal models of diabetes is now available, and they provide new insights into almost every aspect of diabetes. Approaches combining human, in vitro, and animal studies are probably the best strategy to improve our understanding of the underlying mechanisms of diabetes, and the choice of the best model to achieve such objective is crucial. Traditionally classified based on pathogenesis as spontaneous or induced models, each has its own advantages and disadvantages. The most common animal models of diabetes are described, and in addition to non-obese diabetic mice, biobreeding diabetes-prone (BB-DP) rats, streptozotocin-induced models, or high-fat diet-induced diabetic C57Bl/6J mice, new valuable models, such as dogs and cats with spontaneous diabetes, are described.

Pituitary adenomas are uncommon, difficult to diagnose tumors whose heterogeneity and low incidence complicate large-scale studies. The Molecular Registry of Pituitary Adenomas (REMAH) was promoted by the Andalusian Society of Endocrinology and Nutrition (SAEN) in 2008 as a cooperative clinical-basic multicenter strategy aimed at improving diagnosis and treatment of pituitary adenomas by combining clinical, pathological, and molecular information. In 2010, the Spanish Society of Endocrinology and Nutrition (SEEN) extended this project to national level and established 6 nodes with common protocols and methods for sample and clinical data collection, molecular analysis, and data recording in a common registry (www.remahnacional.com). The registry combines clinical data with molecular phenotyping of the resected pituitary adenoma using quantitative real-time PCR of expression of 26 genes: pituitary hormones (GH-PRL-LH-FSH-PRL-ACTH-CGA), receptors (somatostatin, dopamine, GHRH, GnRH, CRH, arginine–vasopressin, ghrelin), other markers (Ki67, PTTG1), and control genes. Until 2015, molecular information has been collected from 704 adenomas, out of 1179 patients registered. This strategy allows for comparative and relational analysis between the molecular profile of the different types of adenoma and the clinical phenotype of patients, which may provide a better understanding of the condition and potentially help in treatment selection. The REMAH is therefore a unique multicenter, interdisciplinary network founded on a shared database that provides a far-reaching translational approach for management of pituitary adenomas, and paves the way for the conduct of combined clinical-basic innovative studies on large patient samples.