Distribuição dos receptores da adenosina no plexo mioentérico – músculo longitudinal do íleo de rato: implicações funcionais

A acetilcolina (ACh) é o neurotransmissor mais importante no controlo da motilidade gastrointestinal. A libertação de ACh dos neurónios entéricos é regulada por receptores neuronais específicos (De Man et al., 2003). Estudos prévios demonstraram que a adenosina exerce um papel duplo na libertação de ACh dos neurónios entéricos através da activação dos receptores inibitórios A1 e facilitatórios A2A (Duarte-Araújo et al., 2004). O potencial terapêutico dos compostos relacionados com a adenosina no controlo da motilidade e da inflamação intestinal, levou-nos a investigar o papel dos receptores com baixa afinidade para a adenosina, A2B e A3, na libertação de acetilcolina induzida por estimulação eléctrica nos neurónios mioentéricos. Estudos de imunolocalização mostraram que os receptores A2B exibem um padrão de distribuição semelhante ao do marcador de células gliais (GFAP). No que respeita aos receptores A1 e A3, estes encontram-se distribuídos principalmente nos corpos celulares dos neurónios ganglionares mioentéricos, enquanto os receptores A2A estão localizados predominantemente nos terminais nervosos colinérgicos. Neste trabalho mostrou-se que a modulação da libertação de ACh-[3H] (usando os antagonistas selectivos DPCPX, ZM241385 e MRS1191) é balanceada através da activação tónica dos receptores inibitórios (A1) e facilitatórios (A2A e A3) pela adenosina endógena. O antagonista selectivo dos receptores A2B, PSB603, não foi capaz de modificar o efeito inibitório da NECA (análogo da adenosina com afinidade para receptores A2). O efeito facilitatório do agonista dos receptores A3, 2-Cl-IB MECA (1-10 nM), foi atenuado pelo MRS1191 e pelo ZM241385, os quais bloqueiam respectivamente os receptores A3 e A2A. Contrariamente à 2-Cl-IB MECA, a activação dos receptores A2A pelo CGS21680C, atenuou a facilitação da libertação de ACh induzida pela activação dos receptores nicotínicos numa situação em que a geração do potencial de acção neuronal foi bloqueada pela tetrodotoxina. A localização diferencial dos receptores excitatórios A3 e A2A ao longo dos neurónios mioentéricos explica porque razão a estimulação dos receptores A3 (com 2-Cl-IB MECA) localizados nos corpos celulares dos neurónios mioentéricos exerce um efeito sinérgico com os receptores facilitatórios A2A dos terminais nervosos no sentido de aumentarem a libertação de ACh. Os resultados apresentados consolidam e expandem a compreensão actual da distribuição e função dos receptores da adenosina no plexo mioentérico do íleo de rato, e devem ser tidos em consideração para a interpretação de dados relativos às implicações fisiopatológicas da adenosina nos transtornos da motilidade intestinal.

SNC / NCRF 24 – Acontecimentos após a data do balanço e suas implicações fiscais e de auditoria

Orientador Prof. Dr. João Domingues Costa

Geostatistical Mapping of Outfall Plume Dispersion Data gathered with an autonomous underwater vehicle

The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron’s classical estimator was used the compute the experimental semivariogram which was fitted to three theoretical models: spherical, exponential and gaussian. The cross-validation procedure suggested the best semivariogram model and ordinary kriging was used to obtain the predictions of salinity at unknown locations. The generated map shows clearly the plume dispersion in the studied area, indicating that the effluent does not reach the near by beaches. Our study suggests that an optimal design for the AUV sampling trajectory from a geostatistical prediction point of view, can help to compute more precise predictions and hence to quantify more accurately dilution. Moreover, since accurate measurements of plume’s dilution are rare, these studies might be very helpful in the future for validation of dispersion models.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

Norma internacional de contabilidade [NIC 10 ]: acontecimento após a data de balanço

Revista Fiscal Maio 2006

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.