971 resultados para Immunologic Tests -- methods


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The effects of some composition variables on the development of multiple emulsions by one-step method were evaluated and their morphology characterized. The formulations that remained stable during the period of the test were submitted to centrifugation and thermal stress tests. The stability and the morphology of multiple droplets were affected not only by the type and concentration of the surfactants employed, but also by the water/oil ratios used. The results suggest that the formation of multiple droplets could involve a combination of transitional and catastrophic phase inversions. The results provide improved knowledge about the one-step emulsification method, a simplified process to prepare multiple emulsions when compared to the two-steps method.

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Aim of the study: The aerial parts of Baccharis dracunculifolia D.C., popularly known as ""alecrim do campo"" are used in folk medicine as anti-inflammatory. The aim of the present study was to evaluate the anti-inflammatory and antinociceptive activities of the crude hydroalcoholic extract obtained from leaves of Baccharis dracunculifolia (BdE), which have not been reported. Matetials and methods: BdE was analyzed by HPLC and in vivo evaluated (doses ranging from 50 to 400 mg/kg, p.o.) by using the acetic acid-induced abdominal constrictions, paw oedema induced by carrageenan or histamine, overt nociception models using capsaicin, glutamate or phorbol myristate acetate (PMA), formalin-induced nociception and mechanical hypernociception induced by carrageenan or complete Freund adjuvant (CFA). As positive controls it was used paracetamol in both acetic acid and formalin tests; dipyrone in capsaicin, glutamate and PMA-induced nociception; indomethacin in CFA and carrageenan-induced hypernociception models. In addition, the in vitro effects of BdE on COX-2 activity and on the activation of NF-kappa B were also evaluated. Results: BdE (50-400 mg/kg, p.o.) significantly diminished the abdominal constrictions induced by acetic acid, glutamate and CFA. Furthermore, BdE also inhibited the nociceptive responses in both phases of formalin-induced nociception. BdE, administered orally, also produced a long-lasting anti-hypernociceptive effect in the acute model of inflammatory pain induced by carrageenan. It was also observed the inhibition of COX-2 activity by BdE. Conclusion: In summary, the data reported in this work confirmed the traditional anti-inflammatory indications of Baccharis dracunculifolia leaves and provided biological evidences that Baccharis dracunculifolia, like Brazilian green propolis, possess antinociceptive and anti-inflammatory activities. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

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DHEA, a steroid hormone synthesized from cholesterol by cells of the adrenal cortex, plays an essential role in enhancing the host`s resistance to different experimental infections. Receptors for this hormone can be found in distinct immune cells (especially macrophages) that are known to be the first line defense against Trypanosoma cruzi infection. These cells operate through an indirect pathway releasing nitric oxide (NO) and cytokines such TNF-alpha and IL-12 which in turn trigger an enhancement of natural killer cells and lymphocytes which finally secrete pro and anti-inflammatory cytokines. The effects of pre- and post-infection DHEA treatment on production of IL-12, TNF alpha and NO were evaluated. T. cruzi infected macrophages post treated with DHEA displayed enhanced concentrations of TNF-alpha, IL-12 and NO. Probably, the mechanisms that induced the production of cytokines by infected cells are more efficient when the immune system has been stimulated first by parasite invasion, suggesting that the protective role of DHEA is greater when administered post infection. (C) 2011 Elsevier B.V. All rights reserved.

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P>Typing methods to evaluate isolates in relation to their phenotypical and molecular characteristics are essential in epidemiological studies. In this study, Candida albicans biotypes were determined before and after storage in order to verify their stability. Twenty C. albicans isolates were typed by Randomly Amplified Polymorphic DNA (RAPD), production of phospholipase and proteinase exoenzymes (enzymotyping) and morphotyping before and after 180 days of storage in Sabouraud dextrose agar (SDA) and sterilised distilled water. Before the storage, 19 RAPD patterns, two enzymotypes and eight morphotypes were identified. The fragment patterns obtained by RAPD, on the one hand, were not significantly altered after storage. On the other hand, the majority of the isolates changed their enzymotype and morphotype after storage. RAPD typing provided the better discriminatory index (DI) among isolates (DI = 0.995) and maintained the profile identified, thereby confirming its utility in epidemiological surveys. Based on the low reproducibility observed after storage in SDA and distilled water by morphotyping (DI = 0.853) and enzymotyping (DI = 0.521), the use of these techniques is not recommended on stored isolates.

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Specimens of the red alga Bostrychia tenella J Agardh (Rhodomelaceae, Ceramiales) were collected from the Sao Paulo coast and submitted to loom temperature solvent extraction The resulting extract was fractionated by partitioning with organic solvent The n-hexane (BT-H) and dichloromethane (BT-D) fractions showed antiprotozoal potential in biological tests with Trypanosoma cruzi and Leishmania amazonensis and presented high activity in an antifungal assay with the phytopathogenic fungi Cladosporium cladosporioides and Cladosporium sphaerospermum Chromatography methods were used to generate subfractions from BT-H (H01 to H11) and from BT-D (D01 to 019) The subtractions were analyzed by gas chromatography-mass spectrometry (GC/MS). and the substances were identified by retention index (Kovats) and by comparison to databases of commercial mass spectra The volatile compounds found in marine algae were identified as fatty acids, low molecular mass hydrocarbons, esters and steroids, some of these have been previously described in the literature based on other biological activities Moreover, uncommon substances. such as neophytadiene were also identified In a trypanocidal assay, fractions BT-H and BT-D showed IC(50) values of 168 and 19 1 mu g/mL. respectively, and were mote active than the gentian violet standard (31 mu g/ml.); subfractions H02. H03, D01 and D02 were active against L amasonensis, exhibiting IC(50) values of 1 S. 2 7, 4 4. and 4 3 mu g/mL., respectively (standard amphotericin B IC(50) = 13 mu g/mL.) All fractions showed antifungal potential this work reports the biological activity and identification of compounds by GC/MS for the marine red alga B tenella for the first time (C) 2010 Elsevier B V All lights reserved

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We have used various computational methodologies including molecular dynamics, density functional theory, virtual screening, ADMET predictions and molecular interaction field studies to design and analyze four novel potential inhibitors of farnesyltransferase (FTase). Evaluation of two proposals regarding their drug potential as well as lead compounds have indicated them as novel promising FTase inhibitors, with theoretically interesting pharmacotherapeutic profiles, when Compared to the very active and most cited FTase inhibitors that have activity data reported, which are launched drugs or compounds in clinical tests. One of our two proposals appears to be a more promising drug candidate and FTase inhibitor, but both derivative molecules indicate potentially very good pharmacotherapeutic profiles in comparison with Tipifarnib and Lonafarnib, two reference pharmaceuticals. Two other proposals have been selected with virtual screening approaches and investigated by LIS, which suggest novel and alternatives scaffolds to design future potential FTase inhibitors. Such compounds can be explored as promising molecules to initiate a research protocol in order to discover novel anticancer drug candidates targeting farnesyltransferase, in the fight against cancer. (C) 2009 Elsevier Inc. All rights reserved.

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The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

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Objective:To investigate the effects of bilateral, surgically induced functional inhibition of the subthalamic nucleus (STN) on general language, high level linguistic abilities, and semantic processing skills in a group of patients with Parkinson’s disease. Methods:Comprehensive linguistic profiles were obtained up to one month before and three months after bilateral implantation of electrodes in the STN during active deep brain stimulation (DBS) in five subjects with Parkinson’s disease (mean age, 63.2 years). Equivalent linguistic profiles were generated over a three month period for a non-surgical control cohort of 16 subjects with Parkinson’s disease (NSPD) (mean age, 64.4 years). Education and disease duration were similar in the two groups. Initial assessment and three month follow up performance profiles were compared within subjects by paired t tests. Reliability change indices (RCI), representing clinically significant alterations in performance over time, were calculated for each of the assessment scores achieved by the five STN-DBS cases and the 16 NSPD controls, relative to performance variability within a group of 16 non-neurologically impaired adults (mean age, 61.9 years). Proportions of reliable change were then compared between the STN-DBS and NSPD groups. Results:Paired comparisons within the STN-DBS group showed prolonged postoperative semantic processing reaction times for a range of word types coded for meanings and meaning relatedness. Case by case analyses of reliable change across language assessments and groups revealed differences in proportions of change over time within the STN-DBS and NSPD groups in the domains of high level linguistics and semantic processing. Specifically, when compared with the NSPD group, the STN-DBS group showed a proportionally significant (p

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The aim of this study was to examine the reliability and validity of field tests for assessing physical function in mid-aged and young-old people (55–70 y). Tests were selected that required minimal space and equipment and could be implemented in multiple field settings such as a general practitioner's office. Nineteen participants completed 2 field and 1 laboratory testing sessions. Intra-class correlations showed good reliability for the tests of upper body strength (lift and reach, R= .66), lower body strength (sit to stand, R= .80) and functional capacity (Canadian Step Test, R= .92), but not for leg power (single timed chair rise, R= .28). There was also good reliability for the balance test during 3 stances: parallel (94.7% agreement), semi-tandem (73.7%), and tandem (52.6%). Comparison of field test results with objective laboratory measures found good validity for the sit to stand (cf 1RM leg press, Pearson r= .68, p< .05), and for the step test (cf PWC140, r= −.60, p< .001), but not for the lift and reach (cf 1RM bench press, r= .43, p> .05), balance (r= −.13, −.18, .23) and rate of force development tests (r= −.28). It was concluded that the lower body strength and cardiovascular function tests were appropriate for use in field settings with mid-aged and young-old adults.

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This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.

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We propose quadrature rules for the approximation of line integrals possessing logarithmic singularities and show their convergence. In some instances a superconvergence rate is demonstrated.

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There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.