Solvation in aqueous binary mixtures: consequences of the hydrophobic character of the ionic liquids and the solvatochromic probes

Information on the solvation in mixtures of water, W, and the ionic liquids, ILs, 1-allyl-3-R-imidazolium chlorides; R = methyl, 1-butyl, and 1-hexyl, has been obtained from the responses of the following solvatochromic probes: 2,6-dibromo-4-[(E)-2-(1-R-pyridinium-4-yl)ethenyl] phenolate, R = methyl, MePMBr2; 1-octyl, OcPMBr(2), and the corresponding quinolinium derivative, MeQMBr(2). A model developed for solvation in binary mixtures of W and molecular solvents has been extended to the present mixtures. Our objective is to assess the relevance to solvation of hydrogen-bonding and the hydrophobic character of the IL and the solvatochromic probe. Plots of the medium empirical polarity, E-T(probe) versus its composition revealed non-ideal behavior, attributed to preferential solvation by the IL and, more efficiently, by the IL-W hydrogen-bonded complex. The deviation from linearity increases as a function of increasing number of carbon atoms in the alkyl group of the IL, and is larger than that observed for solvation by W plus molecular solvents (1-propanol and 2-(1-butoxy)ethanol) that are more hydrophobic than the ILs investigated. This enhanced deviation is attributed to the more organized structure of the ILs proper, which persists in their aqueous solutions. MeQMBr(2) is more susceptible to solvent lipophilicity than OcPMBr(2), although the former probe is less lipophilic. This enhanced susceptibility agrees with the important effect of annelation on the contributions of the quinonoid and zwitterionic limiting structures to the ground and excited states of the probe, hence on its response to both medium composition and lipophilicity of the IL.

STABLE PIECEWISE POLYNOMIAL VECTOR FIELDS

Let N = {y > 0} and S = {y < 0} be the semi-planes of R-2 having as common boundary the line D = {y = 0}. Let X and Y be polynomial vector fields defined in N and S, respectively, leading to a discontinuous piecewise polynomial vector field Z = (X, Y). This work pursues the stability and the transition analysis of solutions of Z between N and S, started by Filippov (1988) and Kozlova (1984) and reformulated by Sotomayor-Teixeira (1995) in terms of the regularization method. This method consists in analyzing a one parameter family of continuous vector fields Z(epsilon), defined by averaging X and Y. This family approaches Z when the parameter goes to zero. The results of Sotomayor-Teixeira and Sotomayor-Machado (2002) providing conditions on (X, Y) for the regularized vector fields to be structurally stable on planar compact connected regions are extended to discontinuous piecewise polynomial vector fields on R-2. Pertinent genericity results for vector fields satisfying the above stability conditions are also extended to the present case. A procedure for the study of discontinuous piecewise vector fields at infinity through a compactification is proposed here.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

SK-HEP cells and lentiviral vector for production of human recombinant factor VIII

Hemophilia A is caused by a deficiency in coagulation factor VIII. Recombinant factor VIII can be used as an alternative although it is unavailable for most patients. Here, we describe the production of a human recombinant B-domain-deleted FVIII (rBDDFVIII) by the human cell line SK-HEP-1, modified by a lentiviral vector rBDDFVIII was produced by recombinant SK-HEP cells (rSK-HEP) at 1.5-2.1 IU/10(6) in 24 h. The recombinant factor had increased in vitro stability when compared to commercial pdFVIII. The functionality of rBDDFVIII was shown by its biological activity and by tail-clip challenge in hemophilia A mice. The rSK-HEP cells grew in a scalable system and produced active rBDDFVIII, indicating that this platform production can be optimized to meet the commercial production scale needs.

ENERGY AND VOLUME OF VECTOR FIELDS ON SPHERICAL DOMAINS

We present a "boundary version" for theorems about minimality of volume and energy functionals on a spherical domain of an odd-dimensional Euclidean sphere.

Present bounds on new neutral vector resonances from electroweak gauge boson pair production at the LHC

Several extensions of the standard model predict the existence of new neutral spin-1 resonances associated with the electroweak symmetry breaking sector. Using the data from ATLAS (with integrated luminosity of L = 1.02 fb(-1)) and CMS (with integrated luminosity of L = 1.55 fb(-1)) on the production of W+W- pairs through the process pp --> l(+)l(-)' is not an element of(T), we place model independent bounds on these new vector resonances masses, couplings, and widths. Our analyses show that the present data exclude new neutral vector resonances with masses up to 1-2.3 TeV depending on their couplings and widths. We also demonstrate how to extend our analysis framework to different models with a specific example.

Binary and ternary inclusion complexes of dapsone in cyclodextrins and polymers: preparation, characterization and evaluation

Dapsone (DAP) is a synthetic sulfone drug with bacteriostatic activity, mainly against Mycobacterium leprae. In this study we have investigated the interactions of DAP with cyclodextrins, 2-hydroxypropyl-beta-cyclodextrin (HP beta CD) and beta-cyclodextrin (beta CD), in the presence and absence of water-soluble polymers, in order to improve its solubility and bioavailability. Solid systems DAP/HP beta CD and DAP/beta CD, in the presence or absence of polyvinylpyrrolidone (PVP K30) or hydroxypropyl methylcellulose (HPMC), were prepared. The binary and ternary systems were evaluated and characterized by SEM, DSC, XRD and NMR analysis as well as phase solubility assays, in order to investigate the interactions between DAP and the excipients in aqueous solution. This study revealed that inclusion complexes of DAP and cyclodextrins (HP beta CD and beta CD) can be produced in order to improve DAP solubility and bioavailability in the presence or absence of polymers (PVP K30 and HPMC). The more stable inclusion complex was obtained with HP beta CD, and consequently HP beta CD was more efficient in improving DAP solubility than beta CD, and the addition of polymers had no influence on DAP solubility or on the stability of the DAP/CDs complexes.

Mosquitoes in degraded and preserved areas of the Atlantic Forest and potential for vector-borne disease risk in the municipality of Sao Paulo, Brazil

In order to assess the epidemiological potential of the Culicidae species in remaining areas of the Brazilian Atlantic Forest, specimens of this family were collected in wild and anthropic environments. A total of 9,403 adult mosquitoes was collected from May, 2009 to June, 2010. The most prevalent among species collected in the wild environment were Anopheles (Kerteszia) cruzii, the Melanoconion section of Culex (Melanoconion), and Aedes serratus, while the most common in the anthropic site were Coquillettidia chrysonotum/albifera, Culex (Culex) Coronator group, and An. (Ker.) cruzii. Mosquito richness was similar between environments, although the abundance of individuals from different species varied. When comparing diversity patterns between environments, anthropic sites exhibited higher richness and evenness, suggesting that environmental stress increased the number of favorable niches for culicids, promoting diversity. Increased abundance of opportunistic species in the anthropic environment enhances contact with culicids that transmit vector-borne diseases.

Effect of contact and systemic insecticides on the sharpshooter Bucephalogonia xanthophis (Hemiptera: cicadellidae), a vector of Xylella fastidiosa in citrus

The knockdown and toxic effects of insecticides of different chemical groups and modes of action registered for citrus in Brazil were investigated for effective control of Bucephalogonia xanthophis, a sharpshooter vector of Xylella fastidiosa in citrus. The active ingredients dimethoate (1.2 mL/1.2L), imidacloprid (0.24 mL/1.2L) and lambda-cyhalothrin (0.24 mL/1.2L), as well as a control (water), were sprayed onto branches of potted-citrus nursery trees to evaluate the effect of residual contact. The insects were confined on sprayed branches by using sleeve cages, in groups of 10 per branch (5 branches/treatment). Lambdacyhalothrin showed a knockdown effect on B. xanthophis (>70% mortality within 2 h of exposure), and the residues were effective for approximately one wk. Imidacloprid, lambdacyhalothrin and dimethoate suppressed the vector populations for up to 3 wk after application, when the insects were exposed to sprayed plants for at least 24 h. In another experiment, 2 neonicotinoid insecticides (thiamethoxam and imidacloprid) were applied by soil drench to potted nursery trees, in order to study their systemic effect, i.e., mortality by ingestion on sharpshooter adults. Thiamethoxam and imidacloprid effectively controlled the vectors at all concentrations tested, when the insects were exposed to treated plants for 24 h (>80% mortality) or 48 h (near 100% mortality). The knockdown effect of thiamethoxam and lambda-cyhalothrin might be particularly important to prevent vector transmission of X. fastidiosa in citrus groves.

Light vector meson production in pp collisions at root s=7 TeV ALICE Collaboration

The ALICE experiment has measured low-mass dimuon production in pp collisions at root s = 7 TeV in the dimuon rapidity region 2.5 < y < 4. The observed dimuon mass spectrum is described as a superposition of resonance decays (eta, rho, omega, eta', phi) into muons and semi-leptonic decays of charmed mesons. The measured production cross sections for omega and phi are sigma(omega)(1 < p(t) < 5 GeV/c. 2.5 < y < 4) = 5.28 +/- 0.54(stat) +/- 0.49(syst) mb and sigma(phi)(1 < p(t) < 5 GeV/c. 2.5 < y < 4) = 0.940 +/- 0.084(stat) +/- 0.076(syst) mb. The differential cross sections d(2)sigma/dy dp(t) are extracted as a function of p(t) for omega and phi. The ratio between the rho and omega cross section is obtained. Results for the phi are compared with other measurements at the same energy and with predictions by models. (C) 2012 CERN. Published by Elsevier B.V. All rights reserved.

Incorporating label dependency into the binary relevance framework for multi-label classification

In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single-label classification problems. The binary relevance approach is one of these methods, where the multi-label learning task is decomposed into several independent binary classification problems, one for each label in the set of labels, and the final labels for each example are determined by aggregating the predictions from all binary classifiers. However, this approach fails to consider any dependency among the labels. Aiming to accurately predict label combinations, in this paper we propose a simple approach that enables the binary classifiers to discover existing label dependency by themselves. An experimental study using decision trees, a kernel method as well as Naive Bayes as base-learning techniques shows the potential of the proposed approach to improve the multi-label classification performance.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

Abstract Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.

Serial bone marrow transplantation reveals in vivo expression of the pCLPG retroviral vector

Abstract Background Gene therapy in the hematopoietic system remains promising, though certain aspects of vector design, such as transcriptional control elements, continue to be studied. Our group has developed a retroviral vector where transgene expression is controlled by p53 with the intention of harnessing the dynamic and inducible nature of this tumor suppressor and transcription factor. We present here a test of in vivo expression provided by the p53-responsive vector, pCLPG. For this, we used a model of serial transplantation of transduced bone marrow cells. Results We observed, by flow cytometry, that the eGFP transgene was expressed at higher levels when the pCLPG vector was used as compared to the parental pCL retrovirus, where expression is directed by the native MoMLV LTR. Expression from the pCLPG vector was longer lasting, but did decay along with each sequential transplant. The detection of eGFP-positive cells containing either vector was successful only in the bone marrow compartment and was not observed in peripheral blood, spleen or thymus. Conclusions These findings indicate that the p53-responsive pCLPG retrovirus did offer expression in vivo and at a level that surpassed the non-modified, parental pCL vector. Our results indicate that the pCLPG platform may provide some advantages when applied in the hematopoietic system.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Influence of the substitutional solute on the mechanical properties of Ti-Nb binary alloys for biomedical use

Titanium alloys are widely used in the manufacture of biomedical implants because they possess an excellent combination of physical properties and outstanding biocompatibility. Today, the most widely used alloy is Ti-6Al-4V, but some studies have reported adverse effects with the long-term presence of Al and V in the body, without mentioning that the elasticity modulus value of this alloy is far superior to the bone. Thus, there is a need to develop new Ti-based alloys without Al and V that have a lower modulus, greater biocompatibility, and similar mechanical strength. In this paper, we investigated the effect of Nb as a substitutional solute on the mechanical properties of Ti-Nb alloys, prepared in an arc-melting furnace and characterized by density, X-ray diffraction, optical microscopy, hardness and elasticity modulus measurements. The X-ray and microscopy measurements show a predominance of the α phase. The microhardness values showed a tendency to increase with the concentration of niobium in the alloy. Regarding the elasticity modulus, it was observed a nonlinear behavior with respect to the concentration of niobium. This behavior is associated with the presence of the α phase.