Degree of conversion of different composite resins photo-activated with light-emitting diode and argon ion laser

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

Effectiveness of the diode laser in the treatment of ligature-induced periodontitis in rats: a histopathological, histometric, and immunohistochemical study

The aim of this study was to evaluate the effects of the use of a high-power gallium-aluminum-arsenide diode laser (GaAlAs; 808 nm, 1 W, 20 s, 20 Hz, 10 J) alone or as adjunctive therapy to scaling and root planing in the treatment of induced periodontitis in rats. Periodontitis was induced by placing a ligature around the mandibular first molar of 60 rats. After 7 days, the ligature was removed and the animals were divided into four groups as follows: C (control), no periodontal treatment; SRP, scaling and root planing (SRP); DL, diode laser (DL) irradiation treatment; and SRP/DL, both SRP and DL irradiation treatment. Five animals from each group were euthanized at 7, 15, and 30 days posttreatment. The effectiveness of the treatments was evaluated in the furcation area using histopathological analysis, histometric analysis of alveolar bone loss (ABL), and immunohistochemical detection of tartrate-resistant acid phosphatase (TRAP), runt-related transcription factor 2 (RUNX2), and osteocalcin (OCN). DL, alone or in combination with adjunctive therapy to SRP in the treatment of experimental periodontitis, resulted in a decreased local inflammatory response. At 7-days posttreatment, the DL and SRP/DL groups had fewer TRAP-positive cells and more RUNX2-positive cells. There was greater OCN immunolabeling in the DL group than in the C and SRP groups at 15 days. There was less ABL in the DL and SRP/DL groups at 15 and 30 days. In conclusion, DL was effective in the treatment of ligature-induced periodontitis in rats, both when used alone and when used as adjunctive therapy to SRP.

Thermal inkjet printing of copper tetrasulfonated phthalocyanine (CuTsPc) as a semiconducting layer on flexible MIS capacitors

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

Validation of a stability-indicating HPLC method with diode array detection for the determination of beclomethasone dipropionate in aqueous suspension for nebulizer

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Caracterização da produção e qualidade físico-química de méis produzidos no Estado de Pernambuco

The present study had as objective contribute to the characterization of beekeeping in the Pernambuco State and evaluate the physical-chemical quality of the honeys produced in the region. For this, was applied a directed formulary to the representative organ of beekeeping class aboutthe productives and technicals aspects of beekeepers. Was obtained 14 samples of honey by Apis mellifera africanized, stored in sterile plastic vessels was sent to the Beekeeping Products Quality Control Laboratory (CEA-UNITAU). Was observed that the most of beekeepers have of 50 to 100 hives (57,14%), 28,57% of 100 to 200 hives and 14,28% more than 500 hives, being that 85,71% produce 30 to 50 kg honey/hives/flowering. All use the standard hive Langstroth and 85,71% obtain their swarm by capture. About the physical-chemical quality of the honey, was observed that moisture content varied from 18,2% to 22,0%, with mean value of 19,80±1,11; the water activity varied from 0,70 to 0,84 aw, with mean value of 0,79±0,05 aw; the total acidity was 24,91±8,99 meq/kg and the average index of hydroxymethylfurfural was 16,32±17,88 meq/kg. The results obtained are according to the quality limits established by the brazilian legislation, excepted the water activity that exceeded the maximum limit of 0,65 aw. The datasobtained in this paper shows the development of beekeeping in Pernambuco State and the honey presents nice quality.

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.