6 resultados para Separate analysis

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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This study describes the enantioselective analysis of unbound and total concentrations of tramadol and its main metabolites O-desmethyltramadol (M1) and N-desmethyltramadol (M2) in human plasma. Sample preparation was preceded by an ultrafiltration step to separate the unbound drug. Both the ultrafiltrate and plasma samples were submitted to liquid/liquid extraction with methyl t-butyl ether. Separation was performed on a Chiralpak (R) AD column and tandem mass spectrometry consisting of an electrospray ionization source, positive ion mode and multiple reaction monitoring was used as the detection system. Linearity was observed in the following ranges: 0.2-600 and 0.5-250 ng/mL for analysis of total and unbound concentrations of the tramadol enantiomers, respectively, and 0.1-300 and 0.25-125 ng/mL for total and unbound concentrations of the M1 and M2 enantiomers, respectively. The lower limits of quantitation were 0.2 and 0.5 ng/mL for analysis of total and unbound concentration of each tramadol enantiomer, respectively, and 0.1 and 0.25 ng/mL for total and unbound concentrations of M1 and M2 enantiomers, respectively. Intra- and interassay reproducibility and inaccuracy did not exceed 15%. Clinical application of the method to patients with neuropathic pain showed plasma accumulation of (+)-tramadol and (+)-M2 after a single oral dose of racemic tramadol. Fractions unbound of tramadol, M1 or M2 were not enantioselective in the patients investigated. (C) 2011 Elsevier B.V. All rights reserved.

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In this paper, a novel method for power quality signal decomposition is proposed based on Independent Component Analysis (ICA). This method aims to decompose the power system signal (voltage or current) into components that can provide more specific information about the different disturbances which are occurring simultaneously during a multiple disturbance situation. The ICA is originally a multichannel technique. However, the method proposes its use to blindly separate out disturbances existing in a single measured signal (single channel). Therefore, a preprocessing step for the ICA is proposed using a filter bank. The proposed method was applied to synthetic data, simulated data, as well as actual power system signals, showing a very good performance. A comparison with the decomposition provided by the Discrete Wavelet Transform shows that the proposed method presented better decoupling for the analyzed data. (C) 2012 Elsevier Ltd. All rights reserved.

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A computational pipeline combining texture analysis and pattern classification algorithms was developed for investigating associations between high-resolution MRI features and histological data. This methodology was tested in the study of dentate gyrus images of sclerotic hippocampi resected from refractory epilepsy patients. Images were acquired using a simple surface coil in a 3.0T MRI scanner. All specimens were subsequently submitted to histological semiquantitative evaluation. The computational pipeline was applied for classifying pixels according to: a) dentate gyrus histological parameters and b) patients' febrile or afebrile initial precipitating insult history. The pipeline results for febrile and afebrile patients achieved 70% classification accuracy, with 78% sensitivity and 80% specificity [area under the reader observer characteristics (ROC) curve: 0.89]. The analysis of the histological data alone was not sufficient to achieve significant power to separate febrile and afebrile groups. Interesting enough, the results from our approach did not show significant correlation with histological parameters (which per se were not enough to classify patient groups). These results showed the potential of adding computational texture analysis together with classification methods for detecting subtle MRI signal differences, a method sufficient to provide good clinical classification. A wide range of applications of this pipeline can also be used in other areas of medical imaging. Magn Reson Med, 2012. (c) 2012 Wiley Periodicals, Inc.

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Abstract Background The integrity of DNA molecules is fundamental for maintaining life. The DNA repair proteins protect organisms against genetic damage, by removal of DNA lesions or helping to tolerate them. DNA repair genes are best known from the gamma-proteobacterium Escherichia coli, which is the most understood bacterial model. However, genome sequencing raises questions regarding uniformity and ubiquity of these DNA repair genes and pathways, reinforcing the need for identifying genes and proteins, which may respond to DNA damage in other bacteria. Results In this study, we employed a bioinformatic approach, to analyse and describe the open reading frames potentially related to DNA repair from the genome of the alpha-proteobacterium Caulobacter crescentus. This was performed by comparison with known DNA repair related genes found in public databases. As expected, although C. crescentus and E. coli bacteria belong to separate phylogenetic groups, many of their DNA repair genes are very similar. However, some important DNA repair genes are absent in the C. crescentus genome and other interesting functionally related gene duplications are present, which do not occur in E. coli. These include DNA ligases, exonuclease III (xthA), endonuclease III (nth), O6-methylguanine-DNA methyltransferase (ada gene), photolyase-like genes, and uracil-DNA-glycosylases. On the other hand, the genes imuA and imuB, which are involved in DNA damage induced mutagenesis, have recently been described in C. crescentus, but are absent in E. coli. Particularly interesting are the potential atypical phylogeny of one of the photolyase genes in alpha-proteobacteria, indicating an origin by horizontal transfer, and the duplication of the Ada orthologs, which have diverse structural configurations, including one that is still unique for C. crescentus. Conclusion The absence and the presence of certain genes are discussed and predictions are made considering the particular aspects of the C. crescentus among other known DNA repair pathways. The observed differences enlarge what is known for DNA repair in the Bacterial world, and provide a useful framework for further experimental studies in this organism.

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Abstract Background Heavy metal Resistance-Nodulation-Division (HME-RND) efflux systems help Gram-negative bacteria to keep the intracellular homeostasis under high metal concentrations. These proteins constitute the cytoplasmic membrane channel of the tripartite RND transport systems. Caulobacter crescentus NA1000 possess two HME-RND proteins, and the aim of this work was to determine their involvement in the response to cadmium, zinc, cobalt and nickel, and to analyze the phylogenetic distribution and characteristic signatures of orthologs of these two proteins. Results Expression assays of the czrCBA operon showed significant induction in the presence of cadmium and zinc, and moderate induction by cobalt and nickel. The nczCBA operon is highly induced in the presence of nickel and cobalt, moderately induced by zinc and not induced by cadmium. Analysis of the resistance phenotype of mutant strains showed that the ΔczrA strain is highly sensitive to cadmium, zinc and cobalt, but resistant to nickel. The ΔnczA strain and the double mutant strain showed reduced growth in the presence of all metals tested. Phylogenetic analysis of the C. crescentus HME-RND proteins showed that CzrA-like proteins, in contrast to those similar to NczA, are almost exclusively found in the Alphaproteobacteria group, and the characteristic protein signatures of each group were highlighted. Conclusions The czrCBA efflux system is involved mainly in response to cadmium and zinc with a secondary role in response to cobalt. The nczCBA efflux system is involved mainly in response to nickel and cobalt, with a secondary role in response to cadmium and zinc. CzrA belongs to the HME2 subfamily, which is almost exclusively found in the Alphaproteobacteria group, as shown by phylogenetic analysis. NczA belongs to the HME1 subfamily which is more widespread among diverse Proteobacteria groups. Each of these subfamilies present distinctive amino acid signatures.

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Introduction: Enterococcus faecalis is a member of the mammalian gastrointestinal microbiota but has been considered a leading cause of hospital-acquired infections. In the oral cavity, it is commonly detected from root canals of teeth with failed endodontic treatment. However, little is known about the virulence and genetic relatedness among E. faecalis isolates from different clinical sources. This study compared the presence of enterococcal virulence factors among root canal strains and clinical isolates from hospitalized patients to identify virulent clusters of E. faecalis. Methods: Multilocus sequence typing analysis was used to determine genetic lineages of 40 E. faecalis clinical isolates from different sources. Virulence clusters were determined by evaluating capsule (cps) locus polymorphisms, pathogenicity island gene content, and antibiotic resistance genes by polymerase chain reaction. Results: The clinical isolates from hospitalized patients formed a phylogenetically separate group and were mostly grouped in the clonal complex 2, which is a known virulent cluster of E. faecalis that has caused infection outbreaks globally. The clonal complex 2 group comprised capsule-producing strains harboring multiple antibiotic resistance and pathogenicity island genes. On the other hand, the endodontic isolates were more diverse and harbored few virulence and antibiotic resistance genes. In particular, although more closely related to isolates from hospitalized patients, capsuleproducing E. faecalis strains from root canals did not carry more virulence/antibiotic genes than other endodontic isolates. Conclusions: E. faecalis isolates from endodontic infections have a genetic and virulence profile different from pathogenic clusters of hospitalized patients’ isolates, which is most likely due to niche specialization conferred mainly by variable regions in the genome.