Myocardial and vascular dysfunction and exercise capacity in the metabolic syndrome

The metabolic syndrome (MS) is associated with cardiovascular risk exceeding that expected from atherosclerotic risk factors, but the mechanism of this association is unclear. We sought to determine the effects of the MS on myocardial and vascular function and cardiorespiratory fitness in 393 subjects with significant risk factors but no cardiovascular disease and negative stress echocardiographic findings. Myocardial function was assessed by global strain rate, strain, and regional systolic velocity (s(m)) and diastolic velocity (e(m)) using tissue Doppler imaging. Arterial compliance was assessed using the pulse pressure method, involving simultaneous radial applanation tonometry and echocardiographic measurement of stroke volume. Exercise capacity was measured by expired gas analysis. Significant and incremental variations in left ventricular systolic (s(m), global strain, and strain rate) and diastolic (e(m)) function were found according to the number of components of MS (p <0.001). MS contributed to reduced systolic and diastolic function even in those without left ventricular hypertrophy (p <0.01). A similar dose-response association was present between the number of components of the MS and exercise capacity (p <0.001) and arterial compliance. The global strain rate and em were independent predictors of exercise capacity. In conclusion, subclinical left ventricular dysfunction corresponded to the degree of metabolic burden, and these myocardial changes were associated with reduced cardiorespiratory fitness.' Subjects with MS who also have subclinical myocardial abnormalities and reduced cardiorespiratory fitness may have a higher risk of cardiovascular disease events and heart failure. (C) 2005 Elsevier Inc. All rights reserved.

High throughput analysis of endogenous glutamate release using a fluorescence plate reader

Recent discoveries of different modes of exocytosis and a plethora of molecules involved in neurotransmitter release has resulted in demand for more rapid and efficient methods for monitoring endogenous glutamate release from various tissue sources. In this article, we describe a high throughput microplate version of the enzyme-linked fluorescence detection method for the measurement of released glutamate, which utilises glutamate dehydrogenase, and the reduction of NADP to NADPH. Previous versions of this method rely upon cuvette-based fluorimeters for detection that are limited by large sample volumes and small numbers of samples that can be measured simultaneously. Comparison between the two methods shows that the microplate assay has comparable performance to the cuvette-based assay but has the capacity to analyse many times more samples in a given run. This increased capacity provides improved experimental design opportunities, higher experimental throughput and better comparison between experimental conditions. (c) 2005 Elsevier B.V. All rights reserved.

Mg-based nanocomposites with high capacity and fast kinetics for hydrogen storage

Magnesium and its alloys have shown a great potential in effective hydrogen storage due to their advantages of high volumetric/ gravimetric hydrogen storage capacity and low cost. However, the use of these materials in fuel cells for automotive applications at the present time is limited by high hydrogenation temperature and sluggish sorption kinetics. This paper presents the recent results of design and development of magnesium-based nanocomposites demonstrating the catalytic effects of carbon nanotubes and transition metals on hydrogen adsorption in these materials. The results are promising for the application of magnesium materials for hydrogen storage, with significantly reduced absorption temperatures and enhanced ab/desorption kinetics. High level Density Functional Theory calculations support the analysis of the hydrogenation mechanisms by revealing the detailed atomic and molecular interactions that underpin the catalytic roles of incorporated carbon and titanium, providing clear guidance for further design and development of such materials with better hydrogen storage properties.

Quantitative analysis of MC1R gene expression in human skin cell cultures

To address the issue of melanocortin-1 receptor (MC1R) expression in non-melanocytic cells, we have quantitatively evaluated the relative expression levels of both MC1R mRNA and protein in a subset of different cell types. Using semi-quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) at high cycle numbers, we detected MC1R mRNA in all cell types examined, including human embryonic kidney-293 (HEK 293) cells, a cell type widely used as a negative control in melanocortin expression studies. Quantitative real-time PCR revealed the highest levels of MC1R transcripts were in melanocytic cells, whereas the keratinocyte and fibroblast cell cultures examined had only a low level of expression, similar to that of HEK 293 cells. Antibody mediated detection of MC1R protein in membrane extracts demonstrated exogenous receptor in MC1R transfected cell lines, as well as endogenous MC1R in melanoma cells. However, radioligand binding procedures were required to detect MC1R protein of normal human melanocytes and no surface expression of MC1R was detected in any of the non-melanocytic cells examined. This was consistent with their low level of mRNA, and suggests that, if present, the levels of surface receptor are significantly lower than that in melanocytes. The capacity of such limited levels of MC1R protein to influence non-melanocytic skin cell biology would likely be severely compromised. Indeed, the MC1R agonist [NIe(4), D-Phe(7)] alpha-melanocyte stimulating hormone (NDP-MSH) was unable to elevate intracellular cyclic adenosine monophosphate (cAMP) levels in the keratinocyte and fibroblast cells examined, whereas a robust increase was elicited in melanocytes. Although there are a variety of cell types with detectable MC1R mRNA, the expression of physiologically significant levels of the receptor may be more restricted than the current literature indicates, and within epidermal tissue may be limited to the melanocyte

Using multivariate analysis to predict the behaviour of soils under effluent irrigation

Onsite wastewater treatment systems aim to assimilate domestic effluent into the environment. Unfortunately failure of such systems is common and inadequate effluent treatment can have serious environmental implications. The capacity of a particular soil to treat wastewater will change over time. The physical properties influence the rate of effluent movement through the soil and its chemical properties dictate the ability to renovate effluent. A research project was undertaken to determine the role that physical and chemical soil properties play in predicting the long-term behaviour of soil under effluent irrigation and to determine if they have a potential function as early indicators of adverse effects of effluent irrigation on treatment sustainability. Principal Component Analysis (PCA) and Cluster Analysis grouped the soils independently of their soil classifications and allowed us to distinguish the most suitable soils for sustainable long term effluent irrigation and determine the most influential soil parameters to characterise them. Multivariate analysis allowed a clear distinction between soils based on the cation exchange capacities. This in turn correlated well with the soil mineralogy. Mixed mineralogy soils in particular sodium or magnesium dominant soils are the most susceptible to dispersion under effluent irrigation. The soil Exchangeable Sodium Percentage (ESP) was identified as a crucial parameter and was highly correlated with percentage clay, electrical conductivity, exchangeable sodium, exchangeable magnesium and low Ca:Mg ratios (less than 0.5).

Blind multiuser receiver for DS-CDMA wireless system

We consider blind signal detection in an asynchronous code-division multiple-access (CDMA) system employing short spreading sequences in the presence of unknown multipath fading. This approach is capable of countering the presence of multiple-access interference (MAI) in CDMA fading channels. The proposed blind multiuser detector is based on an independent component analysis (ICA) to mitigate both MAI and noise. This algorithm has been utilised in blind source separation (BSS) of unknown sources from their mixtures. It can also be used for estimating the basis vectors of BSS. The aim is to include an ICA algorithm within a wireless receiver in order to reduce the level of interference in wideband systems. This blind multiuser detector requires no training sequence compared with the conventional multiuser detection receiver. The proposed ICA blind multiuser detector is made robust with respect to knowledge of signature waveforms and the timing of the user of interest. Several experiments are performed in order to verify the validity of the proposed ICA algorithm.

Probabilistic cost benefit analysis of generation investment in a deregulated electricity market

A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

A novel grid computing approach for probabilistic small signal analysis

Grid computing is an advanced technique for collaboratively solving complicated scientific problems using geographically and organisational dispersed computational, data storage and other recourses. Application of grid computing could provide significant benefits to all aspects of power system that involves using computers. Based on our previous research, this paper presents a novel grid computing approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. A prototype computing grid is successfully implemented in our research lab to carry out PSSS analysis on two benchmark systems. Comparing to traditional computing techniques, the gird computing has given better performances for PSSS analysis in terms of computing capacity, speed, accuracy and stability. In addition, a computing grid framework for power system analysis has been proposed based on the recent study.

Performance analysis of multi-radio AODV in hybrid wireless mesh networks

Wireless Mesh Networks (WMNs), based on commodity hardware, present a promising technology for a wide range of applications due to their self-configuring and self-healing capabilities, as well as their low equipment and deployment costs. One of the key challenges that WMN technology faces is the limited capacity and scalability due to co-channel interference, which is typical for multi-hop wireless networks. A simple and relatively low-cost approach to address this problem is the use of multiple wireless network interfaces (radios) per node. Operating the radios on distinct orthogonal channels permits effective use of the frequency spectrum, thereby, reducing interference and contention. In this paper, we evaluate the performance of the multi-radio Ad-hoc On-demand Distance Vector (AODV) routing protocol with a specific focus on hybrid WMNs. Our simulation results show that under high mobility and traffic load conditions, multi-radio AODV offers superior performance as compared to its single-radio counterpart. We believe that multi-radio AODV is a promising candidate for WMNs, which need to service a large number of mobile clients with low latency and high bandwidth requirements.

Hop selection in peer-to-peer WPAN networks

Currently, wireless technology is revolutionizing the way we share information and communicate. The demands for mobility have made wireless technology the primary source for voice communication. Code-division multiple-access (CDMA) is a very popular spread spectrum application due to its claims of low transmission power, higher system capacity, ability to mitigate multipath fading and user interference. In that case, frequency-hopping code-division multiple access (FH-CDMA) has received considerable attention over the past few years. This technique will allow a better performance over a fading channel, message privacy, and immunity to narrowband interference. This paper addresses the characteristics of FH-CDMA in WPAN networks, with an emphasis on frequency-hopped Bluetooth systems. A performance evaluation of FH-CDMA is discussed and simulated. The analysis shows the interaction between the designed parameters and their effect on the network system. Most specifically, the FH-CDMA scheme provides frequency and temporal diversity to combat the effects of interference.