Relationship between composition and organizational levels of nanostructured systems formed by Oleth 10 and PPG-5-Ceteth-20 for potential drug delivery

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Diazepam, em dose única, inibe a migração celular, a estimulação macrofágica e a atividade de TNF-α na reação inflamatória aguda induzida por LPS em camundongos

Benzodiazepines are one of the most frequently prescribed drugs due to their anxiolytic properties. The aim of this study was to evaluate the effects of diazepam on lipopolysaccharide-induced peritoneal acute inflammatory responses. Swiss mice were treated with diazepam in a single dose of 1 or 10 mg/kg- subcutaneously 1 h before an intraperitoneal injection of lipopolysaccharide or sterile saline solution. The mice were killed 16 h after and the cells were washed from the peritoneal cavity to determine the total number of cells and the mononuclear and polimorfonuclear subpopulations, as well as the TNF-alpha activity and percentage of spread macrophages. Our results showed that the diazepam treatment (1 and 10 mg/kg) induced a significant reduction in the LPS-induced macrophage stimulation and TNF-α activity. Diazepam (10 mg/kg) also reduced the inflammatory cellular migration when compared to the control. It can be concluded that the diazepam treatment in a single dose is able to influence the inflammatory cellular influx, macrophage stimulation and TNF-α activity in the acute inflammatory response in mice, having possible implications on the anti-infectious response efficiency.

Utilização dos parâmetros físico-químicos e redes neurais artificiais na identificação dos méis de abelhas (Apis mellifera L.) produzidos no verão e inverno na microrregião de Campos de Jordão, São Paulo

The objective of this work was to typify, through physicochemical parameters, honey from Campos do Jordão’s microrregion, and verify how samples are grouped in accordance with the climatic production seasonality (summer and winter). It were assessed 30 samples of honey from beekeepers located in the cities of Monteiro Lobato, Campos do Jordão, Santo Antonio do Pinhal e São Bento do Sapucaí-SP, regarding both periods of honey production (November to February; July to September, during 2007 and 2008; n = 30). Samples were submitted to physicochemical analysis of total acidity, pH, humidity, water activity, density, aminoacids, ashes, color and electrical conductivity, identifying physicochemical standards of honey samples from both periods of production. Next, we carried out a cluster analysis of data using k-means algorithm, which grouped the samples into two classes (summer and winter). Thus, there was a supervised training of an Artificial Neural Network (ANN) using backpropagation algorithm. According to the analysis, the knowledge gained through the ANN classified the samples with 80% accuracy. It was observed that the ANNs have proved an effective tool to group samples of honey of the region of Campos do Jordao according to their physicochemical characteristics, depending on the different production periods.