Occurrence of Lipid Peroxidation in Brain Microsomes in the Presence of NADH and Vanadate

Oxidation of NADH by rat brain microsomes was stimulated severalfold on addition of vanadate. During the reaction, vanadate was reduced, oxygen was consumed, and H2O2 was generated with a stoichiometry of 1:1 for NADH/O2, as in the case of other membranes. Extra oxygen was found to be consumed over that needed for H2O2 generation specifically when brain microsomes were used. This appears to be due to the peroxidation of lipids known to be accompanied by a large consumption of oxygen. Occurrence of lipid peroxidation in brain microsomes in the presence of NADH and vanadate has been demonstrated. This activity was obtained specifically with the polymeric form of vanadate and with NADH, and was inhibited by the divalent cations Cu2+, Mn2+, and Ca2+, by dihydroxy-phenolic compounds, and by hemin in a concentration-dependent fashion. In the presence of a small concentration of vanadate, addition of an increasing concentration of Fe2+ gave increasing lipid peroxidation. After undergoing lipid peroxidation in the presence of NADH and vanadate, the binding of quinuclidinyl benzylate, a muscarinic antagonist, to brain membranes was decreased.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Effect of undernutrition on the metabolism of phospholipids and gangliosides in developing rat brain

1. Phospholipid content of brains of 3- or 8-week-old undernourished rats was 7--9% less than that for the corresponding control animals and this deficit could not be made up by rehabilitation. Phosphatidyl ethanolamine and plasmalogen were the components most affected in brains of undernourished rats. 2. Incorporation of 32P into phospholipids by brain homogenates was 28% higher in 3-week-old undernourished rats. It is suggested that enhanced phospholipid metabolism in undernourished animals may be related to behavioural alterations noted previously (Sobotka, Cook & Brodie, 1974). 3. Ganglioside concentrations in 3- and 8-week-old undernourished animals were 14% and 11.5% less respectively than those of the control animals and this difference could be made up by rehabilitation. [14C]Glucosamine incorporation in vivo into brain gangliosides was not affected by undernutrition.

Neural network based approach to standard cell placement

We propose a novel algorithm for placement of standard cells in VLSI circuits based on an analogy of this problem with neural networks. By employing some of the organising principles of these nets, we have attempted to improve the behaviour of the bipartitioning method as proposed by Kernighan and Lin. Our algorithm yields better quality placements compared with the above method, and also makes the final placement independent of the initial partition.

Effect of phenyl and phenolic acids on mevalonate-5-Phosphate decarboxylase if the brain

Phenyl and phenolic acids are known to inhibit metabolism of mevalonate in rat brain. The site of inhibition has been found to be mevalonate-5-pyrophosphate decarboxylase. Phenolic acids also inhibited mevalonate-5-phosphate kinase on preincubation. The kinetics showed that p-coumaric acid and isoferulic acid were competing with substrates, mevalonate-5-phosphate or mevalonate-5-pyre phosphate, whereas others showed an uncompetitive type of inhibition. Chlorophenoxyisobutyrate, a hypocholesterolaemic drug, had no effect on these enzymes. An improved method for the synthesis of mevalonate-5-phosphate and mevalonate-5-pyrophosphate, labeled at carbon-1, is described.

A FIFO-based multicast network and its use in multicomputers

We present an implementation of a multicast network of processors. The processors are connected in a fully connected network and it is possible to broadcast data in a single instruction. The network works at the processor-memory speed and therefore provides a fast communication link among processors. A number of interesting architectures are possible using such a network. We show some of these architectures which have been implemented and are functional. We also show the system software calls which allow programming of these machines in parallel mode.

Analysis of transients in a canal network

A generalised formulation of the mathematical model developed for the analysis of transients in a canal network, under subcritical flow, with any realistic combination of control structures and their multiple operations, has been presented. The model accounts for a large variety of control structures such as weirs, gates, notches etc. discharging under different conditions, namely submerged and unsubmerged. A numerical scheme to compute and approximate steady state flow condition as the initial condition has also been presented. The model can handle complex situations that may arise from multiple gate operations. This has been demonstrated with a problem wherein the boundary conditions change from a gate discharge equation to an energy equation and back to a gate discharge equation. In such a situation the wave strikes a fixed gate and leads to large and rapid fluctuations in both discharge and depth.

A Low-Complexity Algorithm for Intrusion Detection in a PIR-Based Wireless Sensor Network

We present a low-complexity algorithm for intrusion detection in the presence of clutter arising from wind-blown vegetation, using Passive Infra-Red (PIR) sensors in a Wireless Sensor Network (WSN). The algorithm is based on a combination of Haar Transform (HT) and Support-Vector-Machine (SVM) based training and was field tested in a network setting comprising of 15-20 sensing nodes. Also contained in this paper is a closed-form expression for the signal generated by an intruder moving at a constant velocity. It is shown how this expression can be exploited to determine the direction of motion information and the velocity of the intruder from the signals of three well-positioned sensors.

Solution structure of Am2766: A highly hydrophobic d-conotoxin from Conus amadis that inhibits inactivation of brain voltage gated sodium channels

The three-dimensional (3D) NMR solution structure (MeOH) of the highly hydrophobic δ-conotoxin δ-Am2766 from the molluscivorous snail Conus amadis has been determined. Fifteen converged structures were obtained on the basis of 262 distance constraints, 25 torsion-angle constraints, and ten constraints based on disulfide linkages and H-bonds. The root-mean-square deviations (rmsd) about the averaged coordinates of the backbone (N, Cα, C) and (all) heavy atoms were 0.62±0.20 and 1.12±0.23 Å, respectively. The structures determined are of good stereochemical quality, as evidenced by the high percentage (100%) of backbone dihedral angles that occupy favorable and additionally allowed regions of the Ramachandran map. The structure of δ-Am2766 consists of a triple-stranded antiparallel β-sheet, and of four turns. The three disulfides form the classical ‘inhibitory cysteine knot’ motif. So far, only one tertiary structure of a δ-conotoxin has been reported; thus, the tertiary structure of δ-Am2766 is the second such example.Another Conus peptide, Am2735 from C. amadis, has also been purified and sequenced. Am2735 shares 96% sequence identity with δ-Am2766. Unlike δ-Am2766, Am2735 does not inhibit the fast inactivation of Na+ currents in rat brain Nav1.2 Na+ channels at concentrations up to 200 nM.

In-Network Computation in Random Wireless Networks: A PAC Approach to Constant Refresh Rates with Lower Energy Costs

We propose a method to compute a probably approximately correct (PAC) normalized histogram of observations with a refresh rate of Theta(1) time units per histogram sample on a random geometric graph with noise-free links. The delay in computation is Theta(root n) time units. We further extend our approach to a network with noisy links. While the refresh rate remains Theta(1) time units per sample, the delay increases to Theta(root n log n). The number of transmissions in both cases is Theta(n) per histogram sample. The achieved Theta(1) refresh rate for PAC histogram computation is a significant improvement over the refresh rate of Theta(1/log n) for histogram computation in noiseless networks. We achieve this by operating in the supercritical thermodynamic regime where large pathways for communication build up, but the network may have more than one component. The largest component however will have an arbitrarily large fraction of nodes in order to enable approximate computation of the histogram to the desired level of accuracy. Operation in the supercritical thermodynamic regime also reduces energy consumption. A key step in the proof of our achievability result is the construction of a connected component having bounded degree and any desired fraction of nodes. This construction may also prove useful in other communication settings on the random geometric graph.

Communication pathways from the anti-codon region to the aminoacylation site in Methionyl tRNA Synthetase: Molecular dynamics simulations and the structure network analysis

The enzymes of the family of tRNA synthetases perform their functions with high precision by synchronously recognizing the anticodon region and the aminoacylation region, which are separated by ?70 in space. This precision in function is brought about by establishing good communication paths between the two regions. We have modeled the structure of the complex consisting of Escherichia coli methionyl-tRNA synthetase (MetRS), tRNA, and the activated methionine. Molecular dynamics simulations have been performed on the modeled structure to obtain the equilibrated structure of the complex and the cross-correlations between the residues in MetRS have been evaluated. Furthermore, the network analysis on these simulated structures has been carried out to elucidate the paths of communication between the activation site and the anticodon recognition site. This study has provided the detailed paths of communication, which are consistent with experimental results. Similar studies also have been carried out on the complexes (MetRS + activated methonine) and (MetRS + tRNA) along with ligand-free native enzyme. A comparison of the paths derived from the four simulations clearly has shown that the communication path is strongly correlated and unique to the enzyme complex, which is bound to both the tRNA and the activated methionine. The details of the method of our investigation and the biological implications of the results are presented in this article. The method developed here also could be used to investigate any protein system where the function takes place through long-distance communication.

Metabolome based reaction graphs of M.tuberculosis and M.leprae: A comparative network analysis

Background. Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. Methodology/Principal Findings. Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. Conclusions. We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension.

Neural network approach for the two-dimensional assignment problem

A neural network approach for solving the two-dimensional assignment problem is proposed. The design of the neural network is discussed and simulation results are presented. The neural network obtains 10-15% lower cost placements on the examples considered, than the adjacent pairwise exchange method.