Health related quality of life in patients with refractory chronic heart failure undergoing cardiac resynchronization: type of therapeutic response

The benefits of cardiac resynchronization therapy (CRT) in the health-related quality of life (HRQL) are largely demonstrated in selected patients with severe congestive heart failure (CHF). However, the differences between responders and non-responders, with regard to the effect of CRT in the various dimensions that constitute HRQL are still a matter of discussion. Objective: To evaluate the impact of CRT on the HRQL of patients with CHF refractory to optimal pharmacological therapy, within 6 months after CRT. Methods: 43 patients, submitted to successful implantation of CRT, were evaluated in hospital just before intervention and in the outpatient clinic within 6 months after CRT. HRQL was analyzed based on the Kansas City Cardiomyopathy Questionnaire (KCCQ). Patients were classified as super-responders (ejection fraction of left ventricle - LVEF - ≥45% post-CRT), n=15, responders (sustained improvement in functional class and LVEF increased by 15%), n=19, and non-responders (no clinical or LVEF improvement), n=9. Results: In the group of super-responders, CRT was associated with an improvement in HRQL for the various fields and sums assessed (ρ<0.05); in responders, CRT has been associated with an improvement of HRQL in the various fields and sums, except in the self-efficacy dimension (ρ<0.05); in non-responders, CRT was not associated with improvement of HRQL. Conclusion: In a population with severe CHF undergoing CRT, the patients with clinical and echocardiographic positive response, obtained a favorable impact in all dimensions of HRQL, while the group without response to CRT showed no improvement. These data reinforces the importance of HRQL as a multidimensional tool for assessment of benefits in clinical practice.

Evaluating the quality of life in patients with refractory chronic heart failure undergoing cardiac resynchronization regarding the type of therapeutic response

The benefits of cardiac resynchronization therapy (CRT) in the quality of life have been largely demonstrated in selected patients with severe congestive heart failure (CHF). However, the differences between responders and non-responders, with regard to the effect of CRT in the various dimensions of quality of life is still a matter of discussion. Objective: to evaluate the impact of CRT on the quality of life of patients with CHF refractory to optimal pharmacological therapy, within 6 months after CRT.

Synthesis, characterization and redox behaviour of benzoyldiazenido- and oxorhenium complexes bearing N,N- and S,S-type ligands

The reactions of [ReCl2{eta(2)-N2C(O)Ph}(PPh3)(2)](1) with 2-aminopyrimidine (H(2)Npyrm), 2,2'-bipyridine (bpy) and tetraethylthiuram disulfide (tds), in MeOH upon reflux, lead to the new eta(1)-(benzoyldiazenido)-rhenium(III) complexes [ReCl{eta(1)-N2C(O)Ph}(HNpyrm)(PPh3)(2)](2)and [ReCl2{eta(1)-N2C(O)Ph}(bpy)(PPh3)] (3), and the known oxo(diethyldithiocarbamato)dirhenium(v)complex [Re2O2(mu O){Et2NC(S)S}(4)](4), respectively. The Et2NC(S)S ligands in 4 result from S-S bond rupture of tds molecules. The obtained compounds have been characterized by IR, H-1, P-31{H-1} and C-13{H-1} NMR spectroscopies, FAB(+)-MS, elemental and single-crystal X-ray diffraction (for 2 and 4)analyses. Complex 2 represents the first structurally characterized Re compound derived from 2-aminopyrimidine. Besides, the redox behaviour of 2-4 in CH2Cl2 solution has been studied by cyclic voltammetry, and the Lever electrochemical ligand parameter (E-L)has been estimated, for the first time, for HNpyrm. The electrochemical results are discussed in terms of electronic properties of the Re centres and the ligands.

A soft origin for CKM-type CP violation

We present a two-Higgs-doublet model, with a Z(3) symmetry, in which CP violation originates solely in a soft (dimension-2) coupling in the scalar potential, and reveals itself solely in the CKM (quark mixing) matrix. In particular, in the mass basis the Yukawa interactions of the neutral scalars are all real. The model has only eleven parameters to fit the six quark masses and the four independent CKM-matrix observables. We find regions of parameter space in which the flavour-changing neutral couplings are so suppressed that they allow the scalars to be no heavier than a few hundred GeV. (C) 2011 Elsevier B.V. All rights reserved.

Chromatographic behaviour of monoclonal antibodies against wild-type amidase from Pseudomonasaeruginosa on immobilized metal chelates

The aim of this work was to devise a one-step purification procedure for monoclonal antibodies (MAbs) of IgG class by immobilized metal affinity chromatography (IMAC). Therefore, several stationary phases were prepared containing immobilized metal chelates in order to study the chromatographic behaviour of MAbs against wild-type amidase from Pseudomonas aeruginosa. Such MAbs adsorbed to Cu(II), Ni(II), Zn(II) and Co(II)-IDA agarose columns. The increase in ligand concentration and the use of longer spacer arms and higher pH values resulted in higher adsorption of MAbs into immobilized metal chelates. The dynamic binding capacity and the maximum binding capacity were 1.33 +/- 0.015 and 3.214 +/- 0.021 mg IgG/mL of sedimented commercial matrix, respectively. A K(D) of 4.53 x 10(-7) M was obtained from batch isotherm measurements. The combination of tailor-made stationary phases of IMAC and the correct selection of adsorption conditions permitted a one-step purification procedure to be devised for MAbs of IgG class. Culture supernatants containing MAbs were purified by IMAC on commercial-Zn(II) and EPI-30-IDA-Zn(II) Sepharose 6B columns and by affinity chromatography on Protein A-Sepharose CL-4B. This MAb preparation revealed on SDS-PAGE two protein bands with M(r) of 50 and 22 kDa corresponding to the heavy and light chains, respectively. Copyright (C) 2011 John Wiley & Sons, Ltd.

Structural characterization and immunogenicity in wild-type and immune tolerant mice of degraded recombinant human interferon Alpha2b

Purpose: This study was conducted to study the influence of protein structure on the immunogenicity in wild-type and immune tolerant mice of well-characterized degradation products of recombinant human interferon alpha2b (rhIFNα2b). Methods: RhIFNα2b was degraded by metal-catalyzed oxidation (M), cross-linking with glutaraldehyde (G), oxidation with hydrogen peroxide (H), and incubation in a boiling water bath (B). The products were characterized with UV absorption, circular dichroism and fluorescence spectroscopy, gel permeation chromatography, reverse-phase high-pressure liquid chromatography, sodium dodecyl sulfate polyacrylamide gel electrophoresis, Western blotting, and mass spectrometry. The immunogenicity of the products was evaluated in wild-type mice and in transgenic mice immune tolerant for hIFNα2. Serum antibodies were detected by enzyme-linked immunosorbent assay or surface plasmon resonance. Results: M-rhIFNα2b contained covalently aggregated rhIFNα2b with three methionines partly oxidized to methionine sulfoxides. G-rhIFNα2b contained covalent aggregates and did not show changes in secondary structure. H-rhIFNα2b was only chemically changed with four partly oxidized methionines. B-rhIFNα2b was largely unfolded and heavily aggregated. Nontreated (N) rhIFNα2b was immunogenic in the wild-type mice but not in the transgenic mice, showing that the latter were immune tolerant for rhIFNα2b. The anti-rhIFNα2b antibody levels in the wild-type mice depended on the degradation product: M-rhIFNα2b > H-rhIFNα2b ∼ N-rhIFNα2b ≫ B-rhIFNα2b; G-rhIFNα2b did not induce anti-rhIFNα2b antibodies. In the transgenic mice, only M-rhIFNα2b could break the immune tolerance. Conclusions: RhIFNα2b immunogenicity is related to its structural integrity. Moreover, the immunogenicity of aggregated rhIFNα2b depends on the structure and orientation of the constituent protein molecules and/or on the aggregate size.

Influence of ventilation type in volatile organic compounds exposure: poultry case

Agricultural workers especially poultry farmers are at increased risk of occupational respiratory diseases. Epidemiological studies showed increased prevalence of respiratory symptoms and adverse changes in pulmonary function parameters in poultry workers. In poultry production volatile organic compounds (VOCs) presence can be due to some compounds produced by molds that are volatile and are released directly into the air. These are known as microbial volatile organic compounds (MVOCs). Because these compounds often have strong and/or unpleasant odors, they can be the source of odors associated with molds. MVOC's are products of the microorganisms primary and secondary metabolism and are composed of low molecular weight alcohols, aldehydes, amines, ketones, terpenes, aromatic and chlorinated hydrocarbons, and sulfur-based compounds, all of which are variations of carbon-based molecules.

Flavored asymmetries for type II seesaw leptogenesis

A novel contribution to the leptonic CP asymmetries in type II seesaw leptogenesis scenarios is obtained for the cases in which flavor effects are relevant for the dynamics of leptogenesis. In the so-called flavored leptogenesis regime, the interference between the tree-level amplitude of the scalar triplet decaying into two leptons and the one-loop wave function correction with leptons in the loop, leads to a new nonvanishing CP asymmetry contribution. The latter conserves total lepton number but violates lepton flavor. Cases in which this novel contribution may be dominant in the generation of the baryon asymmetry are briefly discussed.

A numerical analysis of generalized Boussinesq-type equation using continuos/discontinuous FEM

An improved class of Boussinesq systems of an arbitrary order using a wave surface elevation and velocity potential formulation is derived. Dissipative effects and wave generation due to a time-dependent varying seabed are included. Thus, high-order source functions are considered. For the reduction of the system order and maintenance of some dispersive characteristics of the higher-order models, an extra O(mu 2n+2) term (n ??? N) is included in the velocity potential expansion. We introduce a nonlocal continuous/discontinuous Galerkin FEM with inner penalty terms to calculate the numerical solutions of the improved fourth-order models. The discretization of the spatial variables is made using continuous P2 Lagrange elements. A predictor-corrector scheme with an initialization given by an explicit RungeKutta method is also used for the time-variable integration. Moreover, a CFL-type condition is deduced for the linear problem with a constant bathymetry. To demonstrate the applicability of the model, we considered several test cases. Improved stability is achieved.

Marx-Type solid-state bipolar modulator topologies: Performance comparison

The operation of generalized Marx-type solid-state bipolar modulators is discussed and compared with simplified Marx-derived circuits, to evaluate their capability to deal with various load conditions. A comparative analysis on the number of switches per cell, fiber optic trigger count, losses, and switch hold-off voltages has been made. A circuit topology is obtained as a compromise in terms of operating performance, trigger simplicity, and switching losses. A five-stage laboratory prototype of this circuit has been assembled using 1200 V insulated gate bipolar transistors (IGBTs) and diodes, operating with 1000 V dc input voltage and 1 kHz frequency, giving 5 kV bipolar pulses, with 2.5 mu s pulse width and 5 mu s relaxation time into resistive, capacitive, and inductive loads.

Soliton-type and other travelling wave solutions for an improved class of nonlinear sixth-order Boussinesq equations

An improved class of nonlinear bidirectional Boussinesq equations of sixth order using a wave surface elevation formulation is derived. Exact travelling wave solutions for the proposed class of nonlinear evolution equations are deduced. A new exact travelling wave solution is found which is the uniform limit of a geometric series. The ratio of this series is proportional to a classical soliton-type solution of the form of the square of a hyperbolic secant function. This happens for some values of the wave propagation velocity. However, there are other values of this velocity which display this new type of soliton, but the classical soliton structure vanishes in some regions of the domain. Exact solutions of the form of the square of the classical soliton are also deduced. In some cases, we find that the ratio between the amplitude of this wave and the amplitude of the classical soliton is equal to 35/36. It is shown that different families of travelling wave solutions are associated with different values of the parameters introduced in the improved equations.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.