11 resultados para Label fusion

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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In this work, we investigated the properties of a fusogenic cationic lipid, diC14-amidine, and show that this lipid possesses per se the capacity to adopt either an interdigitated structure (below and around its transition temperature) or a lamellar structure (above the transition temperature). To provide experimental evidence of this lipid bilayer organization, phospholipids spin-labeled at different positions of the hydrocarbon chain were incorporated into the membrane and their electron spin resonance (ESR) spectra were recorded at different temperatures. For comparison, similar experiments were performed with dimyristoyl phosphatidylcholine, a zwitterionic lipid (DMPC) which adopts a bilayer organization over a broad temperature range. Lipid mixing between diC14-amidine and asolectin liposomes was more efficient below (10-15 degrees C) than above the transition temperature (above 25 degrees C). This temperature-dependent "fusogenic" activity of diC14-amidine liposomes is opposite to what has been observed so far for peptides or virus-induced fusion. Altogether, our data suggest that interdigitatiori is a highly fusogenic state and that interdigitation-mediated fusion occurs via an unusual temperature-dependent mechanism that remains to be deciphered.

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Turbulence is one of the key problems of classical physics, and it has been the object of intense research in the last decades in a large spectrum of problems involving fluids, plasmas, and waves. In order to review some advances in theoretical and experimental investigations on turbulence a mini-symposium on this subject was organized in the Dynamics Days South America 2010 Conference. The main goal of this mini-symposium was to present recent developments in both fundamental aspects and dynamical analysis of turbulence in nonlinear waves and fusion plasmas. In this paper we present a summary of the works presented at this mini-symposium. Among the questions to be addressed were the onset and control of turbulence and spatio-temporal chaos. (C) 2011 Elsevier B. V. All rights reserved.

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XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. Most of them make use of techniques for finding the edit distance between tree structures, XML documents being commonly modeled as Ordered Labeled Trees. Yet, a thorough investigation of current approaches led us to identify several similarity aspects, i.e., sub-tree related structural and semantic similarities, which are not sufficiently addressed while comparing XML documents. In this paper, we provide an integrated and fine-grained comparison framework to deal with both structural and semantic similarities in XML documents (detecting the occurrences and repetitions of structurally and semantically similar sub-trees), and to allow the end-user to adjust the comparison process according to her requirements. Our framework consists of four main modules for (i) discovering the structural commonalities between sub-trees, (ii) identifying sub-tree semantic resemblances, (iii) computing tree-based edit operations costs, and (iv) computing tree edit distance. Experimental results demonstrate higher comparison accuracy with respect to alternative methods, while timing experiments reflect the impact of semantic similarity on overall system performance.

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Metronidazole is a BCS (Biopharmaceutics Classification System) class 1 drug, traditionally considered the choice drug in the infections treatment caused by protozoa and anaerobic microorganisms. This study aimed to evaluate bioequivalence between 2 different marketed 250 mg metronidazole immediate release tablets. A randomized, open-label, 2 x 2 crossover study was performed in healthy Brazilian volunteers under fasting conditions with a 7-day washout period. The formulations were administered as single oral dose and blood was sampled over 48 h. Metronidazole plasma concentrations were determined by a liquid chromatography mass spectrometry (LC-MS/MS) method. The plasma concentration vs. time profile was generated for each volunteer and the pharmacokinetic parameters C-max, T-max, AUC(0-t), AUC(0-infinity), k(e), and t(1/2) were calculated using a noncompartmental model. Bioequivalence between pharmaceutical formulations was determined by calculating 90% CIs (Confidence Intervall) for the ratios of C-max, AUC(0-t), and AUC(0-infinity) values for test and reference using log-transformed data. 22 healthy volunteers (11 men, 11 women; mean (SD) age, 28 (6.5) years [range, 21-45 years]; mean (SD) weight, 66 (9.3) kg [range, 51-81 kg]; mean (SD) height, 169 (6.5) cm [range, 156-186 cm]) were enrolled in and completed the study. The 90% CIs for C-max (0.92-1.06), AUC(0-t) (0.97-1.02), and AUC(0-infinity) (0.97-1.03) values for the test and reference products fitted in the interval of 0.80-1.25 proposed by most regulatory agencies, including the Brazilian agency ANVISA. No clinically significant adverse effects were reported. After pharmacokinetics analysis, it concluded that test 250 mg metronidazole formulation is bioequivalent to the reference product according to the Brazilian agency requirements.

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We consider the influence of breakup channels on the complete fusion of weakly bound systems in terms of dynamic polarization potentials. It is argued that the enhancement of the cross section at sub-barrier energies may be consistent with recent experimental observations that nucleon transfer, often leading to breakup, is dominant compared to direct breakup. The main trends of the experimental complete fusion cross sections are analyzed in the framework of the DPP approach. The qualitative conclusions are supported by CDCC calculations including a sequential breakup channel, the one neutron stripping of Li-7 followed by the breakup of Li-6.

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Acute promyelocytic leukemia (APL) is characterized by the presence of the t(15;17) and PML-RARa rearrangement, with good response to treatment with retinoids. However, few cases of variant APL involving alternative chromosomal aberrations have been reported, including t(11;17)(q23;q21) (Wells et al. in Nat Genet 17:109-113, 1; Arnould et al. in Hum Mol Genet 8:1741-1749, 2) t(5;17)(q35;q12-21), t(11;17)(q13;q21) (Grimwade et al in Blood 96:1297-1308, 3) and der(17) (Rego et al. in Blood (ASH Annual Meeting Abstracts)114:Abstract 6, 4), whereby RARa is fused to the PLZF, NPM, NuMA, and STAT5b genes, respectively, have been described. These cases are characterized by distinct morphology, clinical presentation, and in respect to PLZF, a lack of differentiation response to retinoids leading to the need of different approaches concerning diagnostic methods and therapeutics. This paper describes two cases of APL associated with the PLZF-RARA fusion gene enrolled in the IC-APL trial that is a non-randomized, multicenter study conducted in Brazil, Mexico, Chile and Uruguay with the aim to improve the treatment outcome of APL patients in developing countries. These cases, although rare, offer a challenge to its early recognition and proper conduction.

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The low efficiency of gene transfer is a recurrent problem in DNA vaccine development and gene therapy studies using non-viral vectors such as plasmid DNA (pDNA). This is mainly due to the fact that during their traffic to the target cell's nuclei, plasmid vectors must overcome a series of physical, enzymatic and diffusional barriers. The main objective of this work is the development of recombinant proteins specifically designed for pDNA delivery, which take advantage of molecular motors like dynein, for the transport of cargos from the periphery to the centrosome of mammalian cells. A DNA binding sequence was fused to the N-terminus of the recombinant human dynein light chain LC8. Expression studies indicated that the fusion protein was correctly expressed in soluble form using E. coli BL21(DE3) strain. As expected, gel permeation assays found the purified protein mainly present as dimers, the functional oligomeric state of LC8. Gel retardation assays and atomic force microscopy proved the ability of the fusion protein to interact and condense pDNA. Zeta potential measurements indicated that LC8 with DNA binding domain (LD4) has an enhanced capacity to interact and condense pDNA, generating positively charged complexes. Transfection of cultured HeLa cells confirmed the ability of the LD4 to facilitate pDNA uptake and indicate the involvement of the retrograde transport in the intracellular trafficking of pDNA: LD4 complexes. Finally, cytotoxicity studies demonstrated a very low toxicity of the fusion protein vector, indicating the potential for in vivo applications. The study presented here is part of an effort to develop new modular shuttle proteins able to take advantage of strategies used by viruses to infect mammalian cells, aiming to provide new tools for gene therapy and DNA vaccination studies. (C) 2012 Elsevier B.V. All rights reserved.

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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.

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A 36 year-old man after tests for assessing male infertility was diagnosed with primary infertility, bilateral cryptorchidism, non-obstructive azoospermia and discontinuous splenogonadal fusion. Carcinoma in situ was found in his left testicle, which was intra-abdominal and associated with splenogonadal fusion. To our knowledge, this is the fourth case of splenogonadal fusion associated with testicular cancer reported. One should always bear in mind the possibility of this association for the left cryptorchid testicle.

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OBJECTIVE: To evaluate tools for the fusion of images generated by tomography and structural and functional magnetic resonance imaging. METHODS: Magnetic resonance and functional magnetic resonance imaging were performed while a volunteer who had previously undergone cranial tomography performed motor and somatosensory tasks in a 3-Tesla scanner. Image data were analyzed with different programs, and the results were compared. RESULTS: We constructed a flow chart of computational processes that allowed measurement of the spatial congruence between the methods. There was no single computational tool that contained the entire set of functions necessary to achieve the goal. CONCLUSION: The fusion of the images from the three methods proved to be feasible with the use of four free-access software programs (OsiriX, Register, MRIcro and FSL). Our results may serve as a basis for building software that will be useful as a virtual tool prior to neurosurgery.

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Hierarchical multi-label classification is a complex classification task where the classes involved in the problem are hierarchically structured and each example may simultaneously belong to more than one class in each hierarchical level. In this paper, we extend our previous works, where we investigated a new local-based classification method that incrementally trains a multi-layer perceptron for each level of the classification hierarchy. Predictions made by a neural network in a given level are used as inputs to the neural network responsible for the prediction in the next level. We compare the proposed method with one state-of-the-art decision-tree induction method and two decision-tree induction methods, using several hierarchical multi-label classification datasets. We perform a thorough experimental analysis, showing that our method obtains competitive results to a robust global method regarding both precision and recall evaluation measures.