The sympathetic nervous system regulates the three glycerol-3P generation pathways in white adipose tissue of fasted, diabetic and high-protein diet-fed rats

The aim of the present study was to investigate the participation of the sympathetic nervous system (SNS) in the control of glycerol-3-P (G3P) generating pathways in white adipose tissue (WAT) of rats in three situations in which the plasma insulin levels are low. WAT from 48 h fasted animals, 3 day-streptozotocin diabetic animals and high-protein, carbohydrate-free (HP) diet-fed rats was surgical denervated and the G3P generation pathways were evaluated. Food deprivation, diabetes and the HP diet provoke a marked decrease in the rate of glucose uptake and glycerokinase (GyK) activity, but a significant increase in the glyceroneogenesis, estimated by the phosphoenolpyruvate carboxykinase (PEPCK) activity and the incorporation of 1-[C-14]-pyruvate into glycerol-TAG. The denervation provokes a reduction (similar to 70%) in the NE content of WAT in fasted, diabetic and HP diet-fed rats. The denervation induced an increase in WAT glucose uptake of fed, fasted, diabetic and HP diet-fed rats (40%, 60%, 3.2 fold and 35%, respectively). TAG-glycerol synthesis from pyruvate was reduced by denervation in adipocytes of fed (58%) and fasted (36%), saline-treated (58%) and diabetic (23%), and HP diet-fed rats (11%). In these same groups the denervation reduced the PEPCK mRNA expression (75%-95%) and the PEPCK activity (35%-60%). The denervation caused a similar to 35% decrease in GyK activity of control rats and a further similar to 35% reduction in the already low enzyme activity of fasted, diabetic and HP diet-fed rats. These data suggest that the SNS plays an important role in modulating G3P generating pathways in WAT, in situations where insulin levels are low. (C) 2012 Elsevier Inc. All rights reserved.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.