Influence of cerebral ischemia and post-ischemic reperfusion on mitochondrial oxidative phosphorylation

Unilateral ischemia in the right cerebral hemisphere of the rat was induced by ligation of the right common carotid artery coupled with controlled hemorrhage to produce hypotension (25±8 mm/Hg). Where indicated after 30 min of ischemia, the withdrawn blood was reinfused to restore arterial pressure to normal. Mitochondria isolated from the ipsilateral hemisphere after 30 min of ischemia showed significantly lower respiratory rates than the organelles isolated from the contralateral side. Oxidation of NAD+-linked substrates was more sensitive to inhibition in ischemia (30%) than was of ferrocytochromec (12%), succinate oxidation being intermediate. The activities of membrane-bound dehydrogenases (both NADH and succinate-linked) were also significantly lowered. Ischemia did not affect the cytochrome content of mitochondria. Respiratory activity (NAD+-linked) of mitochondria isolated from the ipsilateral hemisphere was twice as sensitive to inhibition by fatty acid as was of preparations from the contralateral side. Mitochondria isolated from cerebral cortex after 90 min of post-ischemic reperfusion showed no significant improvement in the rate of substrate oxidation. Adenine nucleotide translocase activity and energy-dependent Ca2+ uptake, both of which decreased significantly in mitochondria isolated from the ischemic brain, showed little recovery, on reperfusion. These observations suggested the strong possibility that the deleterious effects of ischemia on mitochondrial respiratory function might be mediated by free fatty acids that are known to accumulate in large amounts in ischemic tissues. The pattern of inhibition of ATPase activity was consistent with this view.

A Kalman filter based strategy for linear structural system identification based on multiple static and dynamic test data

The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

Isobaric electrical resistance along the critical line in nickel: An experimental test of universality

High-precision measurement of the electrical resistance of nickel along its critical line, a first attempt of this kind, as a function of pressure to 47.5 kbar is reported. Our analysis yields the values of the critical exponents α=α’=-0.115±0.005 and the amplitude ratios ‖A/A’‖=1.17±0.07 and ‖D/D’‖=1.2±0.1. These values are in close agreement with those predicted by renormalization-group (RG) theory. Moreover, this investigation provides an unambiguous experimental verification to one of the key consequences of RG theory that the critical exponents and amplitudes ratios are insensitive to pressure variation in nickel, a Heisenberg ferromagnet.

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.

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.

Role of lipid peroxidation in impairment of mitochondrial function at complex I by methyl isocyanate treatment of rats in vivo

The subcutaneous administration of methyl isocyanate (MIC) in 1.0 LD50 dose in rats caused a significant effect on hepatic mitochondrial function only at complex I region of the respiratory chain. MIC administration at 1.0 LD50 dose also resulted in significant increases in malondialdehyde and ferrous ion concentration in liver mitochondria. It is suggested that the augmented lipid peroxidation in hepatic mitochondria, catalyzed by iron, possibly mobilized from intracellular stores leads to the inhibition of enzymes of mitochondrial respiration at complex I region, in vivo, in rats receiving a lethal dose of MIC subcutaneously.

Direct Evaluation Of Transient Stability Improvement With Static Var Compensators Using A Structure Preserving Energy Function

The ability of Static Var Compensators (SVCs) to rapidly and continuously control reactive power in response to changing system conditions can result in the improvement of system stability and also increase the power transfer in the transmission system. This paper concerns the application of strategically located SVCs to enhance the transient stability limits and the direct evaluation of the effect of these SVCs on transient stability using a Structure Preserving Energy Function (SPEF). The SVC control system can be modelled from the steady- state control characteristic to accurately simulate its effect on transient stability. Treating the SVC as a voltage-dependent reactive power load leads to the derivation of a path-independent SPEF for the SVC. Case studies on a 10-machine test system using multiple SVCs illustrate the effects of SVCs on transient stability and its accurate prediction.

V-Transform: “An Enhanced Polynomial Coefficient Based DC Test for Non-linear Analog Circuits

Abstract—DC testing of parametric faults in non-linear analog circuits based on a new transformation, entitled, V-Transform acting on polynomial coefficient expansion of the circuit function is presented. V-Transform serves the dual purpose of monotonizing polynomial coefficients of circuit function expansion and increasing the sensitivity of these coefficients to circuit parameters. The sensitivity of V-Transform Coefficients (VTC) to circuit parameters is up to 3x-5x more than sensitivity of polynomial coefficients. As a case study, we consider a benchmark elliptic filter to validate our method. The technique is shown to uncover hitherto untestable parametric faults whose sizes are smaller than 10 % of the nominal values. I.

Hypoxia-Mediated Impairment of the Mitochondrial Respiratory Chain Inhibits the Bactericidal Activity of Macrophages

In infected tissues oxygen tensions are low. As innate immune cells have to operate under these conditions, we analyzed the ability of macrophages (M phi) to kill Escherichia coli or Staphylococcus aureus in a hypoxic microenvironment. Oxygen restriction did not promote intracellular bacterial growth but did impair the bactericidal activity of the host cells against both pathogens. This correlated with a decreased production of reactive oxygen intermediates (ROI) and reactive nitrogen intermediates. Experiments with phagocyte NADPH oxidase (PHOX) and inducible NO synthase (NOS2) double-deficient M phi revealed that in E. coli- or S. aureus-infected cells the reduced antibacterial activity during hypoxia was either entirely or partially independent of the diminished PHOX and NOS2 activity. Hypoxia impaired the mitochondrial activity of infected M phi. Inhibition of the mitochondrial respiratory chain activity during normoxia (using rotenone or antimycin A) completely or partially mimicked the defective antibacterial activity observed in hypoxic E. coli-or S. aureus-infected wild-type M phi, respectively. Accordingly, inhibition of the respiratory chain of S. aureus-infected, normoxic PHOX-/- NOS2(-/-) M phi further raised the bacterial burden of the cells, which reached the level measured in hypoxic PHOX-/- NOS2(-/-) M phi cultures. Our data demonstrate that the reduced killing of S. aureus or E. coli during hypoxia is not simply due to a lack of PHOX and NOS2 activity but partially or completely results from an impaired mitochondrial antibacterial effector function. Since pharmacological inhibition of the respiratory chain raised the generation of ROI but nevertheless phenocopied the effect of hypoxia, ROI can be excluded as the mechanism underlying the antimicrobial activity of mitochondria.

Dynamic Site Characterization and Correlation of Shear Wave Velocity with Standard Penetration Test `N' Values for the City of Agartala, Tripura State, India

Seismic site characterization is the basic requirement for seismic microzonation and site response studies of an area. Site characterization helps to gauge the average dynamic properties of soil deposits and thus helps to evaluate the surface level response. This paper presents a seismic site characterization of Agartala city, the capital of Tripura state, in the northeast of India. Seismically, Agartala city is situated in the Bengal Basin zone which is classified as a highly active seismic zone, assigned by Indian seismic code BIS-1893, Indian Standard Criteria for Earthquake Resistant Design of Structures, Part-1 General Provisions and Buildings. According to the Bureau of Indian Standards, New Delhi (2002), it is the highest seismic level (zone-V) in the country. The city is very close to the Sylhet fault (Bangladesh) where two major earthquakes (M (w) > 7) have occurred in the past and affected severely this city and the whole of northeast India. In order to perform site response evaluation, a series of geophysical tests at 27 locations were conducted using the multichannel analysis of surface waves (MASW) technique, which is an advanced method for obtaining shear wave velocity (V (s)) profiles from in situ measurements. Similarly, standard penetration test (SPT-N) bore log data sets have been obtained from the Urban Development Department, Govt. of Tripura. In the collected data sets, out of 50 bore logs, 27 were selected which are close to the MASW test locations and used for further study. Both the data sets (V (s) profiles with depth and SPT-N bore log profiles) have been used to calculate the average shear wave velocity (V (s)30) and average SPT-N values for the upper 30 m depth of the subsurface soil profiles. These were used for site classification of the study area recommended by the National Earthquake Hazard Reduction Program (NEHRP) manual. The average V (s)30 and SPT-N classified the study area as seismic site class D and E categories, indicating that the city is susceptible to site effects and liquefaction. Further, the different data set combinations between V (s) and SPT-N (corrected and uncorrected) values have been used to develop site-specific correlation equations by statistical regression, as `V (s)' is a function of SPT-N value (corrected and uncorrected), considered with or without depth. However, after considering the data set pairs, a probabilistic approach has also been presented to develop a correlation using a quantile-quantile (Q-Q) plot. A comparison has also been made with the well known published correlations (for all soils) available in the literature. The present correlations closely agree with the other equations, but, comparatively, the correlation of shear wave velocity with the variation of depth and uncorrected SPT-N values provides a more suitable predicting model. Also the Q-Q plot agrees with all the other equations. In the absence of in situ measurements, the present correlations could be used to measure V (s) profiles of the study area for site response studies.

De novo inference of protein function from coarse-grained dynamics

Inference of molecular function of proteins is the fundamental task in the quest for understanding cellular processes. The task is getting increasingly difficult with thousands of new proteins discovered each day. The difficulty arises primarily due to lack of high-throughput experimental technique for assessing protein molecular function, a lacunae that computational approaches are trying hard to fill. The latter too faces a major bottleneck in absence of clear evidence based on evolutionary information. Here we propose a de novo approach to annotate protein molecular function through structural dynamics match for a pair of segments from two dissimilar proteins, which may share even <10% sequence identity. To screen these matches, corresponding 1 mu s coarse-grained (CG) molecular dynamics trajectories were used to compute normalized root-mean-square-fluctuation graphs and select mobile segments, which were, thereafter, matched for all pairs using unweighted three-dimensional autocorrelation vectors. Our in-house custom-built forcefield (FF), extensively validated against dynamics information obtained from experimental nuclear magnetic resonance data, was specifically used to generate the CG dynamics trajectories. The test for correspondence of dynamics-signature of protein segments and function revealed 87% true positive rate and 93.5% true negative rate, on a dataset of 60 experimentally validated proteins, including moonlighting proteins and those with novel functional motifs. A random test against 315 unique fold/function proteins for a negative test gave >99% true recall. A blind prediction on a novel protein appears consistent with additional evidences retrieved therein. This is the first proof-of-principle of generalized use of structural dynamics for inferring protein molecular function leveraging our custom-made CG FF, useful to all. (C) 2014 Wiley Periodicals, Inc.

Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.