Glucose transporter protein 1 expression in mucoepidermoid carcinoma of salivary gland: correlation with grade of malignancy

P>Mucoepidermoid carcinoma (MEC), the most common primary salivary malignancy, shows great variability in clinical behaviour, thus demanding investigation to identify of prognostic markers. Since Warburg`s studies, unrestricted cell growth during tumorigenesis has been linked to altered metabolism, implying hypoxic stimulation of glycolysis and diminished contribution of mitochondrial oxidative phosphorylation to cellular ATP supply. Hypothesizing that the study of MEC metabolic status could lead to the discovery of prognostic markers, we investigated by immunohistochemistry the expression of glucose transporter 1 (Glut-1), mitochondrial antigen and peroxiredoxin I (Prx I) in samples of MEC from different histological grades. Our results showed that mitochondrial antigen and Prx I were expressed in the majority of the MEC cases independent of the histological grade. In contrast Glut-1 expression increased significantly as the tumours became more aggressive. These results suggested that oxidative phosphorylation may contribute to ATP supply in all stages of MEC progression, and that the relative contribution of glycolysis over mitochondria for cellular ATP supply increases during MEC progression, favouring growth under low oxygen concentration. In addition, the observed high Prx I protein levels could provide protection to tumour cells against reactive oxygen species generated as a consequence of mitochondrial function and hypoxia-reoxygenation cycling. Altogether our findings suggest that upregulation of Glut-1 and Prx I constitute successful adaptive strategies of MEC cells conferring a growth advantage over normal salivary gland cells in the unstable oxygenation tumour environment.

Regional investment strategies (RIS) and coastal catchment initiative (CCI) project alignmnet to Great Barrier Reef Water Quality Protection Plan

The Great Barrier Reef Water Quality Protection Plan (the Reef Plan) is a joint initiative of the Australian and Queensland Governments. The Reef Plan aims to progress an integrated approach to natural resource management planning by building on the existing partnerships between the different levels of government, industry groups, the community and research providers within the Reef catchments, principally through partnerships with the regional natural resource management (NRM) bodies.

Developing community-based watershed management in Greater Sao Paulo: the case of Santo Andre

This paper describes how watershed protection is being combined with settlement upgrading and land-use management within an area that serves as one of Greater Sao Paulo's main sources of fresh water. This is being undertaken in the municipality of San to Andre. Unlike previous watershed protection measures, which proved ineffective, it recognizes the need to combine the protection of water-sheds with the improvement of conditions in existing settlements and guiding, rather than prohibiting, further settlement. The paper describes how, the community-based watershed management involves the inhabitants of illegal settlements and other stakeholders in an adaptive planning framework that first seeks consensus on what is to be planned before developing the plan, its implementation and its operation, maintenance and monitoring.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Immunization with tumor-associated epitopes fused to an endoplasmic reticulum translocation signal sequence affords protection against tumors with down-regulated expression of MHC and peptide transporters

Treatment of human cancers with an inherent antigen-processing defect due to a loss of peptide transporters (TAP-1 and TAP-2) and/or MHC class I antigen expression remains a considerable challenge. There is now an increasing realization that tumor cells with down-regulated expression of TAP and/or MHC class I antigens display strong resistance to cytotoxic T lymphocyte (CTL)mediated immune control, and often fail to respond to the conventional immunotherapeutic protocols based on active immunization with tumor-associated epitopes (TAE) or adoptive transfer of tumor-specific T cells, In the present study, we describe a novel approach based on immunization with either genetically modified tumor cells or naked DNA vectors encoding TAE fused to an endoplasmic reticulum (ER) signal sequence (ER-TAE) which affords protection against challenge by melanoma cells with down-regulated expression of TAP-1/2 and MHC class I antigens. In contrast, animals immunized with a vaccine based on TAE alone showed no protection against tumor challenge. Although MHC-peptide tetramer analysis showed a similar frequency of antigen-specific CTL in both ER-TAE- and TAE-immunized mice, functional analysis revealed that CTL activated following immunization with ER-TAE displayed significantly higher avidity for TAE when compared to animals immunized with the TAE alone, These observations provide a new strategy in anti-cancer vaccine design that allows activation of a highly effective and well-defined CTL response against tumors with down-regulated expression of TAP and MHC class I antigens.

Ethanol-related adaptive changes and physical dependence in rats after exposure to ethanol

Adaptive changes that occur after chronic exposure to ethanol are an important component in the development of physical dependence. We have focused our research on ethanol-induced changes in the expression of several genes that may be important in adaptation. In this article, we describe adaptive changes at the level of the N-methyl-D-aspartate receptor, in the protein expression and activity of the Egr transcription factors, and in the expression of a novel gene of unknown function. (C) 2001 Elsevier Science Inc. All rights reserved.

The effects of time delays in adaptive phase measurements

It is not possible to make measurements of the phase of an optical mode using linear optics without introducing an extra phase uncertainty. This extra phase variance is quite large for heterodyne measurements, however it is possible to reduce it to the theoretical limit of log (n) over bar (4 (n) over bar (2)) using adaptive measurements. These measurements are quite sensitive to experimental inaccuracies, especially time delays and inefficient detectors. Here it is shown that the minimum introduced phase variance when there is a time delay of tau is tau/(8 (n) over bar). This result is verified numerically, showing that the phase variance introduced approaches this limit for most of the adaptive schemes using the best final phase estimate. The main exception is the adaptive mark II scheme with simplified feedback, which is extremely sensitive to time delays. The extra phase variance due to time delays is considered for the mark I case with simplified feedback, verifying the tau /2 result obtained by Wiseman and Killip both by a more rigorous analytic technique and numerically.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.