874 resultados para [JEL:E11] Macroeconomics and Monetary Economics - General Aggregative Models - Marxian
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Digital models are an alternative for carrying out analyses and devising treatment plans in orthodontics. The objective of this study was to evaluate the accuracy and the reproducibility of measurements of tooth sizes, interdental distances and analyses of occlusion using plaster models and their digital images. Thirty pairs of plaster models were chosen at random, and the digital images of each plaster model were obtained using a laser scanner (3Shape R-700, 3Shape A/S). With the plaster models, the measurements were taken using a caliper (Mitutoyo Digimatic(®), Mitutoyo (UK) Ltd) and the MicroScribe (MS) 3DX (Immersion, San Jose, Calif). For the digital images, the measurement tools used were those from the O3d software (Widialabs, Brazil). The data obtained were compared statistically using the Dahlberg formula, analysis of variance and the Tukey test (p < 0.05). The majority of the measurements, obtained using the caliper and O3d were identical, and both were significantly different from those obtained using the MS. Intra-examiner agreement was lowest when using the MS. The results demonstrated that the accuracy and reproducibility of the tooth measurements and analyses from the plaster models using the caliper and from the digital models using O3d software were identical.
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The genetically determined muscular dystrophies are caused by mutations in genes coding for muscle proteins. Differences in the phenotypes are mainly the age of onset and velocity of progression. Muscle weakness is the consequence of myofiber degeneration due to an imbalance between successive cycles of degeneration/regeneration. While muscle fibers are lost, a replacement of the degraded muscle fibers by adipose and connective tissues occurs. Major investigation points are to elicit the involved pathophysiological mechanisms to elucidate how each mutation can lead to a specific degenerative process and how the regeneration is stimulated in each case. To answer these questions, we used four mouse models with different mutations causing muscular dystrophies, Dmd (mdx) , SJL/J, Large (myd) and Lama2 (dy2J) /J, and compared the histological changes of regeneration and fibrosis to the expression of genes involved in those processes. For regeneration, the MyoD, Myf5 and myogenin genes related to the proliferation and differentiation of satellite cells were studied, while for degeneration, the TGF-beta 1 and Pro-collagen 1 alpha 2 genes, involved in the fibrotic cascade, were analyzed. The result suggests that TGF-beta 1 gene is activated in the dystrophic process in all the stages of degeneration, while the activation of the expression of the pro-collagen gene possibly occurs in mildest stages of this process. We also observed that each pathophysiological mechanism acted differently in the activation of regeneration, with distinctions in the induction of proliferation of satellite cells, but with no alterations in stimulation to differentiation. Dysfunction of satellite cells can, therefore, be an important additional mechanism of pathogenesis in the dystrophic muscle.
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This paper presents the offorts to calculate the geoid model for Brazil. It is limited by 6 degrees N and 35 degrees S in latitude and 30 degrees W and 75 degrees W in longitude. The terrestrial gravity data for the continent have been updated by means of the most recent surveys in Brazil and in the neighbour countries. The complete Bouguer and Helmert gravity anomalies have been derived through the Canadian package SHGEO. The short wavelength component was estimated via FFT. The geopotential model EGM2008 was used as a reference field restricted to degree and order 150. The model was validated over 844 GPS observations on Bench Marks of the spirit leveling network. The height anomalies plus a topography dependent correction term derived from EGM2008 (degree 2190 and order 2159), GO_CONS_GCF_2_DIR_R2 (degree and order 240), GOCO02S (degree and order 250), EIGEN 51C (degree and order 359) and EIGEN 6C (degree and order 1420), geoidal height derived from MAPGEO2004 (old official geoid model in Brazil) have also been compared to the GPS points on Bench Marks.
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In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo et al. [22] by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a possible autocorrelation among measurements taken throughout the same experimental unit. Moreover, to avoid the possible influence of outlying observations or to take into account the non-normal symmetric tails of the data, we assume elliptical contours for the joint distribution of random effects and errors, which allows us to attribute different weights to the observations. We propose an iterative algorithm to obtain the maximum-likelihood estimates for the parameters and derive the local influence curvatures for some specific perturbation schemes. The motivation for this work comes from a pharmacokinetic indomethacin data set, which was analysed previously by Bocheng and Xuping [1] under normality.
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We derive asymptotic expansions for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of dispersion models, under a sequence of Pitman alternatives. The asymptotic distributions of these statistics are obtained for testing a subset of regression parameters and for testing the precision parameter. Based on these nonnull asymptotic expansions, the power of all four tests, which are equivalent to first order, are compared. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2012 Elsevier B.V. All rights reserved.
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Ethnopharmacological relevance:Anadenantheracolubrina (Vell.) Brenan,popularlyknownas “angico”, is a plantthathasbeenwidelyusedinfolkmedicineduetoitsanti-inflammatory property.Toevaluatethe pharmacological activitiesofthisplant,studieswereperformedonitsantinociceptiveandanti- inflammatoryproperties. Materials andmethods: The AEof Anadenantheracolubrina, madefromthebark,wasusedinrodentsvia oral route(p.o.),at100,200,and400mg/kginclassicalmodelsofnociception(aceticacid-induced writhing andhot-platetest)andinflammation evokedbycarrageenan(e.g.,pawedema,peritonitis,and synovitis). Results: The aceticacid-inducedabdominalwrithesinmiceweresignificantly reduced(Po0.001)by oral treatmentwiththeextract(100,200,and400mg/kg),buttheextractdidnotsignificantly increase the latencyinthenociceptivehot-platetest. Anadenantheracolubrina aqueousextractreduced significantly theedemaand,besides,diminishedthemieloperoxidaseactivity(200and400mg/kg, Po0.01).Thecarrageenan-inducedperitonitiswassignificantly reduced(Po0.05) bytheaqueous extractat100,200,and400mg/kg.Theaqueousextract(200mg/kg)reducesthesynovialleukocyte infiltration oncarrageenan-inducedsynovitisinrats(Po0.01),butfailedtosignificantly affectjoint swelling andimpairedmobility. Conclusions: Weshowforthe first timethattheanti-inflammatory andperipheralantinociceptive activities of Anadenantheracolubrina are consistent,atleastinpart,withtheuseofthisplantinpopular medicine practices.
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Paracoccidoides brasiliensis adhesion to lung epithelial cells is considered an essential event for the establishment of infection and different proteins participate in this process. One of these proteins is a 30 kDa adhesin, pI 4.9 that was described as a laminin ligand in previous studies, and it was more highly expressed in more virulent P. brasiliensis isolates. This protein may contribute to the virulence of this important fungal pathogen. Using Edman degradation and mass spectrometry analysis, this 30 kDa adhesin was identified as a 14-3-3 protein. These proteins are a conserved group of small acidic proteins involved in a variety of processes in eukaryotic organisms. However, the exact function of these proteins in some processes remains unknown. Thus, the goal of the present study was to characterize the role of this protein during the interaction between the fungus and its host. To achieve this goal, we cloned, expressed the 14-3-3 protein in a heterologous system and determined its subcellular localization in in vitro and in vivo infection models. Immunocytochemical analysis revealed the ubiquitous distribution of this protein in the yeast form of P. brasiliensis, with some concentration in the cytoplasm. Additionally, this 14-3-3 protein was also present in P. brasiliensis cells at the sites of infection in C57BL/6 mice intratracheally infected with P. brasiliensis yeast cells for 72 h (acute infections) and 30 days (chronic infection). An apparent increase in the levels of the 14-3-3 protein in the cell wall of the fungus was also noted during the interaction between P. brasiliensis and A549 cells, suggesting that this protein may be involved in host-parasite interactions, since inhibition assays with the protein and this antibody decreased P. brasiliensis adhesion to A549 epithelial cells. Our data may lead to a better understanding of P. brasiliensis interactions with host tissues and paracoccidioidomycosis pathogenesis.
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Analyzing and modeling relationships between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects in chemical datasets is a challenging task for scientific researchers in the field of cheminformatics. Therefore, (Q)SAR model validation is essential to ensure future model predictivity on unseen compounds. Proper validation is also one of the requirements of regulatory authorities in order to approve its use in real-world scenarios as an alternative testing method. However, at the same time, the question of how to validate a (Q)SAR model is still under discussion. In this work, we empirically compare a k-fold cross-validation with external test set validation. The introduced workflow allows to apply the built and validated models to large amounts of unseen data, and to compare the performance of the different validation approaches. Our experimental results indicate that cross-validation produces (Q)SAR models with higher predictivity than external test set validation and reduces the variance of the results. Statistical validation is important to evaluate the performance of (Q)SAR models, but does not support the user in better understanding the properties of the model or the underlying correlations. We present the 3D molecular viewer CheS-Mapper (Chemical Space Mapper) that arranges compounds in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kinds of features, like structural fragments as well as quantitative chemical descriptors. Comprehensive functionalities including clustering, alignment of compounds according to their 3D structure, and feature highlighting aid the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. Even though visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allows for the investigation of model validation results are still lacking. We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. New functionalities in CheS-Mapper 2.0 facilitate the analysis of (Q)SAR information and allow the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. Our approach reveals if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org.
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http://www.ncbi.nlm.nih.gov/pubmed/20864016
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Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.