977 resultados para Isa Label
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this paper, we report the development of a sensitive label-free impedimetric biosensor based on the use of affibody as bioreceptor and gold nanostructured screen-printed graphite as a sensor platform for the detection of human epidermal growth factor receptor 2 (HER2). The affisensor is realized by immobilizing a terminal cysteine-modified affibody on gold nanoparticles. The sensor was characterized by electrochemical techniques and scanning electron microscopy (SEM). Furthermore, surface plasmon resonance (SPR) technology was also applied to explore the potential of affibodies as small-molecule discriminating tools. Using optimized experimental conditions, a single-use affisensor showed a good analytical performance for HER2 detection from 0 to 40μg/L. The estimated limit of detection was 6.0μg/L. Finally, the realized affisensor was applied to human serum samples.
A label-free impedimetric immunosensor for direct determination of the textile dye Disperse Orange 1
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This article reports on smoking prevalence and associated factors in the elderly, based on a population-based cross-sectional study with multistage sampling including 1,954 individuals 60 years or older living in four areas of Sao Paulo State, Brazil. Overall smoking prevalence was 12.2%, and higher rates were associated with male gender, age 60-69 years, not belonging to an Evangelical church, lower income, low body weight, lack of leisure-time physical activity, depression/anxiety, and hypertension. There was a high prevalence of smokers among individuals with a history of stroke, cancer, and chronic obstructive pulmonary disease. The results point to the need for effective interventions in healthcare services to promote smoking cessation among the elderly, since many are unable to stop on their own, even when they have tobacco-related illnesses. Special attention should be paid to individuals that depend on the National Health System, since smoking prevalence is higher in underprivileged socioeconomic groups.
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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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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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O objetivo deste trabalho foi determinar a prevalência do hábito de fumar e os fatores associados em idosos. Estudo transversal de base populacional, com amostragem em múltiplos estágios, que envolveu 1.954 idosos com 60 anos ou mais, residentes em quatro áreas do Estado de São Paulo, Brasil. A prevalência de fumantes foi de 12,2%, sendo maior no sexo masculino, na faixa de 60 a 69 anos, nos estratos inferiores de renda, nos idosos com baixo peso corporal, nos que não praticavam atividade física de lazer, naqueles com depressão/ansiedade e que referiram não ser hipertensos, e a prevalência foi menor entre os evangélicos. Prevalências elevadas de fumantes foram observadas em idosos com história de AVC, câncer e doença pulmonar crônica. Os resultados alertam para a necessidade de intervenções eficazes dos serviços de saúde para a cessação do tabagismo em idosos, visto que muitos deles, mesmo com doenças relacionadas ao tabaco, não conseguem deixar de fumar, especialmente junto ao estrato SUS dependente, pois a prevalência do tabagismo é maior nos segmentos socioeconômicos mais desfavorecidos.
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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.
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Antibody microarrays are of great research interest because of their potential application as biosensors for high-throughput protein and pathogen screening technologies. In this active area, there is still a need for novel structures and assemblies providing insight in binding interactions such as spherical and annulus-shaped protein structures, e.g. for the utilization of curved surfaces for the enhanced protein-protein interactions and detection of antigens. Therefore, the goal of the presented work was to establish a new technique for the label-free detection of bio-molecules and bacteria on topographically structured surfaces, suitable for antibody binding.rnIn the first part of the presented thesis, the fabrication of monolayers of inverse opals with 10 μm diameter and the immobilization of antibodies on their interior surface is described. For this purpose, several established methods for the linking of antibodies to glass, including Schiff bases, EDC/S-NHS chemistry and the biotin-streptavidin affinity system, were tested. The employed methods included immunofluorescence and image analysis by phase contrast microscopy. It could be shown that these methods were not successful in terms of antibody immobilization and adjacent bacteria binding. Hence, a method based on the application of an active-ester-silane was introduced. It showed promising results but also the need for further analysis. Especially the search for alternative antibodies addressing other antigens on the exterior of bacteria will be sought-after in the future.rnAs a consequence of the ability to control antibody-functionalized surfaces, a new technique employing colloidal templating to yield large scale (~cm2) 2D arrays of antibodies against E. coli K12, eGFP and human integrin αvβ3 on a versatile useful glass surface is presented. The antibodies were swept to reside around the templating microspheres during solution drying, and physisorbed on the glass. After removing the microspheres, the formation of annuli-shaped antibody structures was observed. The preserved antibody structure and functionality is shown by binding the specific antigens and secondary antibodies. The improved detection of specific bacteria from a crude solution compared to conventional “flat” antibody surfaces and the setting up of an integrin-binding platform for targeted recognition and surface interactions of eukaryotic cells is demonstrated. The structures were investigated by atomic force, confocal and fluorescence microscopy. Operational parameters like drying time, temperature, humidity and surfactants were optimized to obtain a stable antibody structure.
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Children who experience adverse reactions to cow's milk or who have diseases predisposing them to low bone mass are often prescribed a supplementation of calcium and vitamin D(3), but adherence can be poor. Age-specific preferences for different formulations may exist and at least partially explain poor compliance.
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Intravenous immunoglobulin (IVIG) is the first-line therapy for multifocal motor neuropathy (MMN). This open-label multi-centre study (NCT00701662) assessed the efficacy, safety, and convenience of subcutaneous immunoglobulin (SCIG) in patients with MMN over 6 months, as an alternative to IVIG. Eight MMN patients (42-66 years), on stable IVIG dosing, received weekly SCIG at doses equivalent to previous IVIG using a "smooth transition protocol". Primary efficacy endpoint was the change from baseline to week 24 in muscle strength. Disability, motor function, and health-related quality of life (HRQL) endpoints were also assessed. One patient deteriorated despite dose increase and was withdrawn. Muscle strength, disability, motor function, and health status were unchanged in all seven study completers who rated home treatment as extremely good. Four experienced 18 adverse events, of which only two were moderate. This study suggests that MMN patients with stable clinical course on regular IVIG can be switched to SCIG at the same monthly dose without deterioration and with a sustained overall improvement in HRQL.