Improved renal function after kidney transplantation is associated with heme oxygenase-1 polymorphism

Heme oxygenase-1 (HO-1) has a microsatellite polymorphism based on the number of guanosine-thymidine nucleotide repeats (GT) repeats that regulates expression levels and could have an impact on organ survival post-injury. We correlated HO-1 polymorphism with renal graft function. The HO-1 gene was sequenced (N = 181), and the allelic repeats were divided into subclasses: short repeats (S) (< 27 repeats) and long repeats (L) (>= 27 repeats). A total of 47.5% of the donors carried the S allele. The allograft function was statistically improved six months, two and three yr after transplantation in patients receiving kidneys from donors with an S allele. For the recipients carrying the S allele (50.3%), the allograft function was also better throughout the follow-up, but reached statistical significance only three yr after transplantation (p = 0.04). Considering only those patients who had chronic allograft nephropathy (CAN; 74 of 181), allograft function was also better in donors and in recipients carrying the S allele, two and three yr after transplantation (p = 0.03). Recipients of kidney transplantation from donors carrying the S allele presented better function even in the presence of CAN.

Disruption of the circadian clock within the cardiomyocyte influences myocardial contractile function, metabolism, and gene expression

Virtually every mammalian cell, including cardiomyocytes, possesses an intrinsic circadian clock. The role of this transcriptionally based molecular mechanism in cardiovascular biology is poorly understood. We hypothesized that the circadian clock within the cardiomyocyte influences diurnal variations in myocardial biology. We, therefore, generated a cardiomyocyte-specific circadian clock mutant (CCM) mouse to test this hypothesis. At 12 wk of age, CCM mice exhibit normal myocardial contractile function in vivo, as assessed by echocardiography. Radiotelemetry studies reveal attenuation of heart rate diurnal variations and bradycardia in CCM mice (in the absence of conduction system abnormalities). Reduced heart rate persisted in CCM hearts perfused ex vivo in the working mode, highlighting the intrinsic nature of this phenotype. Wild-type, but not CCM, hearts exhibited a marked diurnal variation in responsiveness to an elevation in workload (80 mmHg plus 1 mu M epinephrine) ex vivo, with a greater increase in cardiac power and efficiency during the dark (active) phase vs. the light (inactive) phase. Moreover, myocardial oxygen consumption and fatty acid oxidation rates were increased, whereas cardiac efficiency was decreased, in CCM hearts. These observations were associated with no alterations in mitochondrial content or structure and modest mitochondrial dysfunction in CCM hearts. Gene expression microarray analysis identified 548 and 176 genes in atria and ventricles, respectively, whose normal diurnal expression patterns were altered in CCM mice. These studies suggest that the cardiomyocyte circadian clock influences myocardial contractile function, metabolism, and gene expression.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

A geometric mass-preserving redistancing scheme for the level set function

In this paper we describe and evaluate a geometric mass-preserving redistancing procedure for the level set function on general structured grids. The proposed algorithm is adapted from a recent finite element-based method and preserves the mass by means of a localized mass correction. A salient feature of the scheme is the absence of adjustable parameters. The algorithm is tested in two and three spatial dimensions and compared with the widely used partial differential equation (PDE)-based redistancing method using structured Cartesian grids. Through the use of quantitative error measures of interest in level set methods, we show that the overall performance of the proposed geometric procedure is better than PDE-based reinitialization schemes, since it is more robust with comparable accuracy. We also show that the algorithm is well-suited for the highly stretched curvilinear grids used in CFD simulations. Copyright (C) 2010 John Wiley & Sons, Ltd.

Low-energy nuclear reactions with double-solenoid based radioactive nuclear beam

The University of Notre Dame, USA (Becchetti et al, Nucl. Instrum. Metho ds Res. A505, 377 (2003)) and later the University of Sao Paulo, Brazil (Lichtenthaler et al, Eur. Phys. J. A25, S-01, 733 (2005)) adopted a system based on superconducting solenoids to produce low-energy radioactive nuclear beams. In these systems the solenoids act as thick lenses to collect, select, and focus the secondary beam into a scattering chamb er. Many experiments with radioactive light particle beams (RNB) such as (6)He, (7)Be, (8)Li, (8)B have been performed at these two facilities. These low-energy RNB have been used to investigate low-energy reactions such as elastic scattering, transfer and breakup, providing useful information on the structure of light nuclei near the drip line and on astrophysics. Total reaction cross-sections, derived from elastic scattering analysis, have also been investigated for light system as a function of energy and the role of breakup of weakly bound or exotic nuclei is discussed.

The spectrum of an open vertex model based on the U(q)[SU(2)] algebra at roots of unity

We study the exact solution of an N-state vertex model based on the representation of the U(q)[SU(2)] algebra at roots of unity with diagonal open boundaries. We find that the respective reflection equation provides us one general class of diagonal K-matrices having one free-parameter. We determine the eigenvalues of the double-row transfer matrix and the respective Bethe ansatz equation within the algebraic Bethe ansatz framework. The structure of the Bethe ansatz equation combine a pseudomomenta function depending on a free-parameter with scattering phase-shifts that are fixed by the roots of unity and boundary variables. (C) 2010 Elsevier B.V. All rights reserved.

Performance Improvement of Tomographic Image Reconstruction Based on DSP Processors

This paper presents the use of a multiprocessor architecture for the performance improvement of tomographic image reconstruction. Image reconstruction in computed tomography (CT) is an intensive task for single-processor systems. We investigate the filtered image reconstruction suitability based on DSPs organized for parallel processing and its comparison with the Message Passing Interface (MPI) library. The experimental results show that the speedups observed for both platforms were increased in the same direction of the image resolution. In addition, the execution time to communication time ratios (Rt/Rc) as a function of the sample size have shown a narrow variation for the DSP platform in comparison with the MPI platform, which indicates its better performance for parallel image reconstruction.

Magnetic resonance and conductivity study of gelatin-based proton conductor polymer electrolytes

This work report results from proton nuclear magnetic resonance (NMR), continuous-wave (CW-EPR) and pulsed electron paramagnetic resonance (P-EPR) and complex impedance spectroscopy of gelatin-based polymer gel electrolytes containing acetic acid. cross-linked with formaldehyde and plasticized with glycerol. Ionic conductivity of 2 x 10(-5) S/cm was obtained at room temperature for samples prepared with 33 wt% of acetic acid. Proton ((1)H) line shapes and spin-lattice relaxation times were measured as a function of temperature. The NMR results show that the proton mobility is dependent on acetic acid content in the plasticized polymer gel electrolytes. The CW-EPR spectra, which were carried out in samples doped with copper perchlorate, indicate the presence of the paramagnetic Cu(2+) ions in axially distorted sites. The P-EPR technique, known as electron spin echo envelope modulation (ESEEM), was employed to show the involvement of both, hydrogen and nitrogen atoms, in the copper complexation of the gel electrolyte. (C) 2009 Elsevier Ltd. All rights reserved.

Fragment-Based QSAR and Molecular Modeling Studies on a Series of Discodermolide Analogs as Microtubule-Stabilizing Anticancer Agents

Inhibition of microtubule function is an attractive rational approach to anticancer therapy. Although taxanes are the most prominent among the microtubule-stabilizers, their clinical toxicity, poor pharmacokinetic properties, and resistance have stimulated the search for new antitumor agents having the same mechanism of action. Discodermolide is an example of nontaxane natural product that has the same mechanism of action, demonstrating superior antitumor efficacy and therapeutic index. The extraordinary chemical and biological properties have qualified discodermolide as a lead structure for the design of novel anticancer agents with optimized therapeutic properties. In the present work, we have employed a specialized fragment-based method to develop robust quantitative structure - activity relationship models for a series of synthetic discodermolide analogs. The generated molecular recognition patterns were combined with three-dimensional molecular modeling studies as a fundamental step on the path to understanding the molecular basis of drug-receptor interactions within this important series of potent antitumoral agents.

NMR and conductivity study of gelatin-based polymer electrolytes

Nuclear Magnetic Resonance spectroscopy (NMR) and complex impedance spectroscopy have been used to study gelatin-based polymer electrolytes plasticized with glycerol and containing lithium perchlorate. The studied samples were prepared with salt concentration of 7.9 wt% and 10.3 wt%. Ionic conductivity of about 10(-5) S/cm was obtained at room temperature for both samples. Lithium (Li-7) and proton (H-1) lineshapes and spin-lattice relaxation times were measured as a function of temperature. The Li-7 NMR relaxation results indicate that the ionic mobility in this system is comparable to those found in other plasticized polymer electrolytes.

A WAVELET-BASED SPEAKER VERIFICATION ALGORITHM

This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

Statistical coupling analysis of aspartic proteinases based on crystal structures of the Trichoderma reesei enzyme and its complex with pepstatin A

The crystal structures of an aspartic proteinase from Trichoderma reesei (TrAsP) and of its complex with a competitive inhibitor, pepstatin A, were solved and refined to crystallographic R-factors of 17.9% (R(free)=21.2%) at 1.70 angstrom resolution and 15.81% (R(free) = 19.2%) at 1.85 angstrom resolution, respectively. The three-dimensional structure of TrAsP is similar to structures of other members of the pepsin-like family of aspartic proteinases. Each molecule is folded in a predominantly beta-sheet bilobal structure with the N-terminal and C-terminal domains of about the same size. Structural comparison of the native structure and the TrAsP-pepstatin complex reveals that the enzyme undergoes an induced-fit, rigid-body movement upon inhibitor binding, with the N-terminal and C-terminal lobes tightly enclosing the inhibitor. Upon recognition and binding of pepstatin A, amino acid residues of the enzyme active site form a number of short hydrogen bonds to the inhibitor that may play an important role in the mechanism of catalysis and inhibition. The structures of TrAsP were used as a template for performing statistical coupling analysis of the aspartic protease family. This approach permitted, for the first time, the identification of a network of structurally linked residues putatively mediating conformational changes relevant to the function of this family of enzymes. Statistical coupling analysis reveals coevolved continuous clusters of amino acid residues that extend from the active site into the hydrophobic cores of each of the two domains and include amino acid residues from the flap regions, highlighting the importance of these parts of the protein for its enzymatic activity. (C) 2008 Elsevier Ltd. All rights reserved.

Exact penalties for variational inequalities with applications to nonlinear complementarity problems

In this paper, we present a new reformulation of the KKT system associated to a variational inequality as a semismooth equation. The reformulation is derived from the concept of differentiable exact penalties for nonlinear programming. The best theoretical results are presented for nonlinear complementarity problems, where simple, verifiable, conditions ensure that the penalty is exact. We close the paper with some preliminary computational tests on the use of a semismooth Newton method to solve the equation derived from the new reformulation. We also compare its performance with the Newton method applied to classical reformulations based on the Fischer-Burmeister function and on the minimum. The new reformulation combines the best features of the classical ones, being as easy to solve as the reformulation that uses the Fischer-Burmeister function while requiring as few Newton steps as the one that is based on the minimum.

Regression analysis of mean quality-adjusted survival time based on pseudo-observations

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.