Identification of archaeal proteins that affect the exosome function in vitro

Background: The archaeal exosome is formed by a hexameric RNase PH ring and three RNA binding subunits and has been shown to bind and degrade RNA in vitro. Despite extensive studies on the eukaryotic exosome and on the proteins interacting with this complex, little information is yet available on the identification and function of archaeal exosome regulatory factors. Results: Here, we show that the proteins PaSBDS and PaNip7, which bind preferentially to poly-A and AU-rich RNAs, respectively, affect the Pyrococcus abyssi exosome activity in vitro. PaSBDS inhibits slightly degradation of a poly-rA substrate, while PaNip7 strongly inhibits the degradation of poly-A and poly-AU by the exosome. The exosome inhibition by PaNip7 appears to depend at least partially on its interaction with RNA, since mutants of PaNip7 that no longer bind RNA, inhibit the exosome less strongly. We also show that FITC-labeled PaNip7 associates with the exosome in the absence of substrate RNA. Conclusions: Given the high structural homology between the archaeal and eukaryotic proteins, the effect of archaeal Nip7 and SBDS on the exosome provides a model for an evolutionarily conserved exosome control mechanism.

Harmonic identification using parallel neural networks in single-phase systems

In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Cluster identification and characterization in the riser of a circulating fluidized bed from numerical simulation results

A methodology of identification and characterization of coherent structures mostly known as clusters is applied to hydrodynamic results of numerical simulation generated for the riser of a circulating fluidized bed. The numerical simulation is performed using the MICEFLOW code, which includes the two-fluids IIT`s hydrodynamic model B. The methodology for cluster characterization that is used is based in the determination of four characteristics, related to average life time, average volumetric fraction of solid, existing time fraction and frequency of occurrence. The identification of clusters is performed by applying a criterion related to the time average value of the volumetric solid fraction. A qualitative rather than quantitative analysis is performed mainly owing to the unavailability of operational data used in the considered experiments. Concerning qualitative analysis, the simulation results are in good agreement with literature. Some quantitative comparisons between predictions and experiment were also presented to emphasize the capability of the modeling procedure regarding the analysis of macroscopic scale coherent structures. (c) 2007 Elsevier Inc. All rights reserved.

A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

Fast experimental identification of suspension models for control design

This paper presents both the theoretical and the experimental approaches of the development of a mathematical model to be used in multi-variable control system designs of an active suspension for a sport utility vehicle (SUV), in this case a light pickup truck. A complete seven-degree-of-freedom model is successfully quickly identified, with very satisfactory results in simulations and in real experiments conducted with the pickup truth. The novelty of the proposed methodology is the use of commercial software in the early stages of the identification to speed up the process and to minimize the need for a large number of costly experiments. The paper also presents major contributions to the identification of uncertainties in vehicle suspension models and in the development of identification methods using the sequential quadratic programming, where an innovation regarding the calculation of the objective function is proposed and implemented. Results from simulations of and practical experiments with the real SUV are presented, analysed, and compared, showing the potential of the method.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm

This paper presents the design and implementation of an embedded soft sensor, i. e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called ""Limited Rules"", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

Identification of a new ligand binding domain in the al subunit of the inhibitory glycine receptor

Four discontinuous extracellular sequence domains have been proposed to form the ligand binding sites of the ligand-gated ion channel receptor superfamily. In this study, we investigated the role of 12 contiguous residues of the inhibitory glycine receptor that define the proposed loop A ligand binding domain; Using the techniques of site-directed mutagenesis and patch-clamp electrophysiology, four of the 12 residues were shown to have impaired ligand binding. Three mutants, I93A, A101H, and N102A, resulted in significant (17-44-fold) increases in the agonist EC50 values as compared with the wild-type glycine receptor, whereas Hill coefficients, I-max values, and antagonist affinity remained largely unaffected. Consideration of receptor efficacy values indicates that these residues are involved in ligand binding rather than channel activation. A fourth mutant, W94A, failed to give rise to any glycine-activated currents, although cell-surface expression was observed, suggesting that this residue may also be involved in agonist binding. These data provide the most extensive characterization of the loop A ligand binding domain available to date and define two new residue locations, Ile(93) and Asn(102), as contributing to the four-loop model of ligand binding.

Identification of initiation sites for T4 lysozyme folding using CD and NMR spectroscopy of peptide fragments

Using CD and 2D H-1 NMR spectroscopy, we have identified potential initiation sites for the folding of T4 lysozyme by examining the conformational preferences of peptide fragments corresponding to regions of secondary structure. CD spectropolarimetry showed most peptides were unstructured in water, but adopted partial helical conformations in TFE and SDS solution. This was also consistent with the H-1 NMR data which showed that the peptides were predominantly disordered in water, although in some cases, nascent or small populations of partially folded conformations could be detected. NOE patterns, coupling constants, and deviations from random coil Her chemical shift values complemented the CD data and confirmed that many of the peptides were helical in TFE and SDS micelles. In particular, the peptide corresponding to helix E in the native enzyme formed a well-defined helix in both TFE and SDS, indicating that helix E potentially forms an initiation site for T4 lysozyme folding. The data for the other peptides indicated that helices D, F, G, and H are dependent on tertiary interactions for their folding and/or stability. Overall, the results from this study, and those of our earlier studies, are in agreement with modeling and IID-deuterium exchange experiments, and support an hierarchical model of folding for T4 lysozyme.

Identification of regions within the third FnIII-like domain of the IL-5R alpha involved in IL-5 interaction

Previously, two binding sites for interleukin 5 (IL-5) were identified on the IL-5 receptor alpha chain (IL-5R alpha). They are located within the CD loop of the first fibronectin type III (FnIII)-like domain and the EF loop of the second FnIII-like domain. The first binding site was identified by exploiting the different abilities of human IL-5R alpha (hIL-5R alpha) and mouse IL-5R alpha (mIL-5R alpha) to bind hIL-5. Here we show that ovine IL-5 (oIL-5) has the ability to activate the hIL-5R alpha but not the mIL-5R alpha. By using chimeras of the mIL-5R alpha and hIL-5R alpha we demonstrate that residues within the first and third FnIII-like domains of mIL-5R alpha are responsible for this lack of activity. Furthermore, mutation of residues on hIL-5R alpha to mIL-5R alpha within the predicted DE and FG loop regions of the third FnIII domain reduces oIL-5 activity, These results show that regions of the third FnIII domain of IL-5R alpha are involved in binding, in addition to the regions in domains one and two of the IL-5R alpha that were identified in an earlier study. (C) 2000 Academic Press.

Identification of physiologically functional peptides in dairy products

A wide range of peptides produced from milk proteins have been demonstrated to produce a physiological response in model systems. These peptides may be released from intact proteins in the gastrointestinal tract by proteolytic digestion, but are also present in fermented products such as cheese and yogurt, as a result of the action of inherent proteases, such as plasmin, and/or bacterial proteases released by the starter culture. This study investigated the presence of peptides, previously reported to have bioactive properties, in commercially available yogurts and cheeses.

A model for predicting the future incidence of coronary heart disease within percentiles of coronary heart disease risk

Background We present a method (The CHD Prevention Model) for modelling the incidence of fatal and nonfatal coronary heart disease (CHD) within various CHD risk percentiles of an adult population. The model provides a relatively simple tool for lifetime risk prediction for subgroups within a population. It allows an estimation of the absolute primary CHD risk in different populations and will help identify subgroups of the adult population where primary CHD prevention is most appropriate and cost-effective. Methods The CHD risk distribution within the Australian population was modelled, based on the prevalence of CHD risk, individual estimates of integrated CHD risk, and current CHD mortality rates. Predicted incidence of first fatal and nonfatal myocardial infarction within CHD risk strata of the Australian population was determined. Results Approximately 25% of CHD deaths were predicted to occur amongst those in the top 10 percentiles of integrated CHD risk, regardless of age group or gender. It was found that while all causes survival did not differ markedly between percentiles of CHD risk before the ages of around 50-60, event-free survival began visibly to differ about 5 years earlier. Conclusions The CHD Prevention Model provides a means of predicting future CHD incidence amongst various strata of integrated CHD risk within an adult population. It has significant application both in individual risk counselling and in the identification of subgroups of the population where drug therapy to reduce CHD risk is most cost-effective. J Cardiovasc Risk 8:31-37 (C) 2001 Lippincott Williams & Wilkins.

Bayesian analysis of the error correction model

This paper presents a method for estimating the posterior probability density of the cointegrating rank of a multivariate error correction model. A second contribution is the careful elicitation of the prior for the cointegrating vectors derived from a prior on the cointegrating space. This prior obtains naturally from treating the cointegrating space as the parameter of interest in inference and overcomes problems previously encountered in Bayesian cointegration analysis. Using this new prior and Laplace approximation, an estimator for the posterior probability of the rank is given. The approach performs well compared with information criteria in Monte Carlo experiments. (C) 2003 Elsevier B.V. All rights reserved.