State-of-the-art nanoplatform-integrated MALDI-MS impacting resolutions in urinary proteomics

Urine proteomics has become a subject of interest, since it has led to a number of breakthroughs in disease diagnostics. Urine contains information not only from the kidney and the urinary tract but also from other organs, thus urinary proteome analysis allows for identification of biomarkers for both urogenital and systemic diseases. The following review gives a brief overview of the analytical techniques that have been in practice for urinary proteomics. MALDI-MS technique and its current application status in this area of clinical research have been discussed. The review comments on the challenges facing the conventional MALDI-MS technique and the upgradation of this technique with the introduction of nanotechnology. This review projects nano-based techniques such as nano-MALDI-MS, surface-assisted laser desorption/ionization, and nanostructure-initiator MS as the platforms that have the potential in trafficking MALDI-MS from the lab to the bedside.     

Resilience of super users’ mental models of enterprise-wide systems

Research on information system training has focused primarily on methods, while neglecting the effects of interruption intervals between training and system implementation. This empirical study examines the resilience of accurate mental models of an enterprise-wide system in a large health care facility. Accurate mental models were shown to withstand the passage of time and resulted in superior field performance following a crash conversion. Consistent with prior experimental research, certain types of learners were more likely to acquire these sounder mental models. In large organisations where the simultaneous training of users on a complex system is virtually impossible, scheduling is an important facet of the training paradigm. The main practical implications of this study involve the development of: (1) training programmes emphasising performance on far-transfer tasks, (2) training schedules designed to minimise knowledge erosion, and (3) criteria for selecting highly capable super users.     

Electrophysiological and pharmacological responses of chronically denervated lower esophageal sphincter of the opossum

BACKGROUND & AIMS: Achalasia is characterized by loss of myenteric neurons and incomplete relaxation of the lower esophageal sphincter (LES). The aim of this study was to develop an achalasia model in the opossum using the surfactant benzyldimethyltetradecylammonium chloride (BAC). This study further characterizes the achalasia model. METHODS: BAC or saline was injected circumferentially into the LES of 14 adult opossums. Eight months after injection, manometry, isolated muscle bath studies, electrical field stimulation, and histochemical analysis were performed. RESULTS: Manometrically, the LES of BAC-treated opossums showed higher pressures (38.7 +/- 12 mm Hg vs. 17 +/- 3.0 mm Hg) and reduced esophageal body contraction amplitudes (4.2 +/- 3 mm Hg vs. 27.4 +/- 12 mm Hg). Isolated muscle strips challenged with carbachol and sodium nitroprusside contracted and relaxed similarly to controls. Electrical field stimulation failed to induce relaxation in BAC-treated tissue but did induce contraction. Contractile responses were markedly reduced by tetrodotoxin and atropine in BAC-treated animals and controls. An altered nitric oxide system was shown by the lack of response to L-arginine and N omega-nitro-L-arginine. Histology showed loss of myenteric neurons and increased cholinergic nerve bundles. CONCLUSIONS: Loss of NO inhibitory myenteric neurons markedly reduces the relaxation of the LES, and histology and pharmacological responses suggest a proliferation of cholinergic nerves into the LES contributing to the static elevated pressures of the amyenteric LES.     

Red, green, and blue LEDs for white light illumination

The rapid improvement of the white light efficacy achievable with light-emitting diodes (LEDs) opens up new opportunities in the general illumination market. An LED light source made of red, green, and blue LEDs (RGB-LEDs) can provide the unique feature of color variability, allowing the user to select the desired color point of the lamp. The white light color accuracy required in the general illumination market is a challenge for LEDs. The variation in lumen output and wavelength for nominally identical LEDs and the change in these parameters with temperature and time result in an unacceptably high variability in the color point of white light from RGB-LEDs. In this paper, we show that these problems can be overcome with suitable feedback control schemes that can be implemented in a practical LED lamp. We present results of experiment and theoretical modeling that shows the performance that can be achieved with a number of different control schemes     

Low Temperature Water–Gas Shift Reaction Over Alkali Metal Promoted Cobalt Carbide Catalysts

Low temperature water–gas shift (LT-WGS) was performed over various group I alkali metal (Li, Na, K, Rb, Cs) promoted cobalt carbide (Co₂C) catalysts at temperatures ranging from 453 to 573 K and atmospheric pressure. Cobalt carbide (Co₂C) was found to be active for the WGS reaction. The stability of the catalyst is related to the stability of the cobalt carbide phases under reaction conditions. Potassium promoted cobalt carbide catalysts exhibited higher activity and stability compared to the other alkali promoted catalysts for LT-WGS. X-ray diffraction analyses of fresh and used catalysts suggest that the origin of deactivation of the catalysts is primarily due to the chemical transition of cobalt from carbide to metal during WGS.     

Prediction and analysis of surface roughness characteristics of a non-ferrous material using ANN in CNC turning

Surface roughness, an indicator of surface quality is one of the most-specified customer requirements in a machining process. For efficient use of machine tools, optimum cutting parameters (speed, feed, and depth of cut) are required. So it is necessary to find a suitable optimization method which can find optimum values of cutting parameters for minimizing surface roughness. The turning process parameter optimization is highly constrained and non-linear. In this work, machining process has been carried out on brass C26000 material in dry cutting condition in a CNC turning machine and surface roughness has been measured using surface roughness tester. To predict the surface roughness, an artificial neural network (ANN) model has been designed through feed-forward back-propagation network using Matlab (2009a) software for the data obtained. Comparison of the experimental data and ANN results show that there is no significant difference and ANN has been used confidently. The results obtained conclude that ANN is reliable and accurate for predicting the values. The actual R _a value has been obtained as 1.1999???m and the corresponding predicted surface roughness value is 1.1859???m, which implies greater accuracy.     

A strategy to reduce the control packet load of MANETs with bidirectional links using DSR

Dynamic source routing (DSR) is a robust protocol commonly applied to multi‐hop wireless mobile ad hoc networks (MANETs). In this paper, an algorithm is proposed for modifying the basic DSR protocol to enhance its performance by reducing the number of redundant route reply packets (RREPs). In the modified DSR (MDSR), for a source destination pair, the destination responds to the first received route request packet (RREQ) with an RREP, and the subsequently received RREQs, bearing the same request ID, are responded to only if the hop count is less than that of all the previously received RREQs. The performance of MDSR has been compared with that of the basic DSR for different network densities and for different mobility of nodes. Simulation results show that MDSR gives fewer control packets, less latency and a higher packet delivery ratio than DSR. Copyright © 2007 John Wiley & Sons, Ltd.