160 resultados para bayesian hierarchical models


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The aim of this study was to determine the reproducibility, reliability and validity of measurements in digital models compared to plaster models. Fifteen pairs of plaster models were obtained from orthodontic patients with permanent dentition before treatment. These were digitized to be evaluated with the program Cécile3 v2.554.2 beta. Two examiners measured three times the mesiodistal width of all the teeth present, intercanine, interpremolar and intermolar distances, overjet and overbite. The plaster models were measured using a digital vernier. The t-Student test for paired samples and interclass correlation coefficient (ICC) were used for statistical analysis. The ICC of the digital models were 0.84 ± 0.15 (intra-examiner) and 0.80 ± 0.19 (inter-examiner). The average mean difference of the digital models was 0.23 ± 0.14 and 0.24 ± 0.11 for each examiner, respectively. When the two types of measurements were compared, the values obtained from the digital models were lower than those obtained from the plaster models (p < 0.05), although the differences were considered clinically insignificant (differences < 0.1 mm). The Cécile digital models are a clinically acceptable alternative for use in Orthodontics.

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Com o objetivo de comparar a satisfação das mulheres com a experiência do parto em três modelos assistenciais, foi realizada pesquisa descritiva, com abordagem quantitativa, em dois hospitais públicos de São Paulo, um promovendo o modelo "Típico" e o outro com um centro de parto intra-hospitalar (modelo "CPNIH") e um peri-hospitalar (modelo "CPNPH"). A amostra foi constituída por 90 puérperas, 30 de cada modelo. A comparação entre os resultados referentes à satisfação das mulheres com o atendimento prestado pelos profissionais de saúde, com a qualidade da assistência e os motivos de satisfação e insatisfação, com a indicação ou recomendação dos serviços recebidos, com a sensação de segurança no processo e com as sugestões de melhorias, mostrou que o modelo CPHPH foi o melhor avaliado, vindo em seguida o CPNIH e por último o Típico. Conclui-se que o modelo peri-hospitalar de assistência ao parto deveria receber maior apoio do SUS, por se constituir em serviço em que as mulheres se mostram satisfeitas com a atenção recebida

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Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

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Strawberries represent the main source of ellagic acid derivatives in the Brazilian diet, corresponding to more than 50% of all phenolic compounds found in the fruit. There is a particular interest in the determination of the ellagic acid content in fruits because of possible chemopreventive benefits. In the present study, the potential health benefits of purified ellagitannins from strawberries were evaluated in relation to the antiproliferative activity and in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension. Therefore, a comparison among ellagic acid, purified ellagitannins, and a strawberry extract was done to evaluate the possible synergistic effects of phenolics. In relation to the antiproliferative activity, it was observed that ellagic acid had the highest percentage inhibition of cell proliferation. The strawberry extract had lower efficacy in inhibiting the cell proliferation, indicating that in the case of this fruit there is no synergism. Purified ellagitannins had high alpha-amylase and ACE inhibitory activities. However, these compounds had low alpha-glucosidase inhibitory activity. These results suggested that the ellagitannins and ellagic acid have good potential for the management of hyperglycemia and hypertension linked to type 2 diabetes. However, further studies with animal and human models are needed to advance the in vitro assay-based biochemical rationale from this study.

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Local food diversity and traditional crops are essential for cost-effective management of the global epidemic of type 2 diabetes and associated complications of hypertension. Water and 12% ethanol extracts of native Peruvian fruits such as Lucuma (Pouteria lucuma), Pacae (Inga feuille), Papayita arequipena (Carica pubescens), Capuli (Prunus capuli), Aguaymanto (Physalis peruviana), and Algarrobo (Prosopis pallida) were evaluated for total phenolics, antioxidant activity based on 2, 2-diphenyl-1-picrylhydrazyl radical scavenging assay, and functionality such as in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension linked to type 2 diabetes. The total phenolic content ranged from 3.2 (Aguaymanto) to 11.4 (Lucuma fruit) mg/g of sample dry weight. A significant positive correlation was found between total phenolic content and antioxidant activity for the ethanolic extracts. No phenolic compound was detected in Lucuma (fruit and powder) and Pacae. Aqueous extracts from Lucuma and Algarrobo had the highest alpha-glucosidase inhibitory activities. Papayita arequipena and Algarrobo had significant ACE inhibitory activities reflecting antihypertensive potential. These in vitro results point to the excellent potential of Peruvian fruits for food-based strategies for complementing effective antidiabetes and antihypertension solutions based on further animal and clinical studies.

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Commonly consumed carbohydrate sweeteners derived from sugar cane, palm, and corn (syrups) were investigated to determine their potential to inhibit key enzymes relevant to Type 2 diabetes and hypertension based on the total phenolic content and antioxidant activity using in vitro models. Among sugar cane derivatives, brown sugars showed higher antidiabetes potential than white sugars; nevertheless, no angiotensin I-converting enzyme (ACE) inhibition was detected in both sugar classes. Brown sugar from Peru and Mauritius (dark muscovado) had the highest total phenolic content and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity, which correlated with a moderate inhibition of yeast alpha-glucosidase without showing a significant effect on porcine pancreatic alpha-amylase activity. In addition, chlorogenic acid quantified by high-performance liquid chromatography was detected in these sugars (128 +/- 6 and 144 +/- 2 mu g/g of sample weight, respectively). Date sugar exhibited high alpha-glucosidase, alpha-amylase, and ACE inhibitory activities that correlated with high total phenolic content and antioxidant activity. Neither phenolic compounds or antioxidant activity was detected in corn syrups, indicating that nonphenolic factors may be involved in their significant ability to inhibit alpha-glucosidase, alpha-amylase, and ACE. This study provides a strong biochemical rationale for further in vivo studies and useful information to make better dietary sweetener choices for Type 2 diabetes and hypertension management.

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Large-conductance Ca(2+)-activated K(+) channels (BK) play a fundamental role in modulating membrane potential in many cell types. The gating of BK channels and its modulation by Ca(2+) and voltage has been the subject of intensive research over almost three decades, yielding several of the most complicated kinetic mechanisms ever proposed. A large number of open and closed states disposed, respectively, in two planes, named tiers, characterize these mechanisms. Transitions between states in the same plane are cooperative and modulated by Ca(2+). Transitions across planes are highly concerted and voltage-dependent. Here we reexamine the validity of the two-tiered hypothesis by restricting attention to the modulation by Ca(2+). Large single channel data sets at five Ca(2+) concentrations were simultaneously analyzed from a Bayesian perspective by using hidden Markov models and Markov-chain Monte Carlo stochastic integration techniques. Our results support a dramatic reduction in model complexity, favoring a simple mechanism derived from the Monod-Wyman-Changeux allosteric model for homotetramers, able to explain the Ca(2+) modulation of the gating process. This model differs from the standard Monod-Wyman-Changeux scheme in that one distinguishes when two Ca(2+) ions are bound to adjacent or diagonal subunits of the tetramer.

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We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

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Hardy-Weinberg Equilibrium (HWE) is an important genetic property that populations should have whenever they are not observing adverse situations as complete lack of panmixia, excess of mutations, excess of selection pressure, etc. HWE for decades has been evaluated; both frequentist and Bayesian methods are in use today. While historically the HWE formula was developed to examine the transmission of alleles in a population from one generation to the next, use of HWE concepts has expanded in human diseases studies to detect genotyping error and disease susceptibility (association); Ryckman and Williams (2008). Most analyses focus on trying to answer the question of whether a population is in HWE. They do not try to quantify how far from the equilibrium the population is. In this paper, we propose the use of a simple disequilibrium coefficient to a locus with two alleles. Based on the posterior density of this disequilibrium coefficient, we show how one can conduct a Bayesian analysis to verify how far from HWE a population is. There are other coefficients introduced in the literature and the advantage of the one introduced in this paper is the fact that, just like the standard correlation coefficients, its range is bounded and it is symmetric around zero (equilibrium) when comparing the positive and the negative values. To test the hypothesis of equilibrium, we use a simple Bayesian significance test, the Full Bayesian Significance Test (FBST); see Pereira, Stern andWechsler (2008) for a complete review. The disequilibrium coefficient proposed provides an easy and efficient way to make the analyses, especially if one uses Bayesian statistics. A routine in R programs (R Development Core Team, 2009) that implements the calculations is provided for the readers.

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Background: MicroRNAs (miRNAs) are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs. The expression of numerous brain-specific miRNAs with a high degree of temporal and spatial specificity suggests that miRNAs play an important role in gene regulation in health and disease. Here we investigate the time course gene expression profile of miR-1, -16, and -206 in mouse dorsal root ganglion (DRG), and spinal cord dorsal horn under inflammatory and neuropathic pain conditions as well as following acute noxious stimulation. Results: Quantitative real-time polymerase chain reaction analyses showed that the mature form of miR-1, -16 and -206, is expressed in DRG and the dorsal horn of the spinal cord. Moreover, CFA-induced inflammation significantly reduced miRs-1 and -16 expression in DRG whereas miR-206 was downregulated in a time dependent manner. Conversely, in the spinal dorsal horn all three miRNAs monitored were upregulated. After sciatic nerve partial ligation, miR-1 and -206 were downregulated in DRG with no change in the spinal dorsal horn. On the other hand, axotomy increases the relative expression of miR-1, -16, and 206 in a time-dependent fashion while in the dorsal horn there was a significant downregulation of miR-1. Acute noxious stimulation with capsaicin also increased the expression of miR-1 and -16 in DRG cells but, on the other hand, in the spinal dorsal horn only a high dose of capsaicin was able to downregulate miR-206 expression. Conclusions: Our results indicate that miRNAs may participate in the regulatory mechanisms of genes associated with the pathophysiology of chronic pain as well as the nociceptive processing following acute noxious stimulation. We found substantial evidence that miRNAs are differentially regulated in DRG and the dorsal horn of the spinal cord under different pain states. Therefore, miRNA expression in the nociceptive system shows not only temporal and spatial specificity but is also stimulus-dependent.

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The effect of genetic and non-genetic factors for carcass, breast meat and leg weights, and yields of a commercial broiler line were investigated using the restricted maximum likelihood method, considering four different animal models, including or excluding maternal genetic effect with covariance between direct and maternal genetic effects, and maternal permanent environmental effect. The likelihood ratio test was used to determine the most adequate model for each trait. For carcass, breast, and leg weight, and for carcass and breast yield, maternal genetic and permanent environmental effects as well as the covariance between direct and maternal genetic effects were significant. The estimates of direct and maternal heritability were 0.17 and 0.04 for carcass weight, 0.26 and 0.06 for breast weight, 0.22 and 0.02 for leg weight, 0.32 and 0.02 for carcass yield, and 0.52 and 0.04 for breast yield, respectively. For leg yield, maternal permanent environmental effect was important, in addition to direct genetic effects. For that trait, direct heritability and maternal permanent environmental variance as a proportion of the phenotypic variance were 0.43 and 0.02, respectively. The results indicate that ignoring maternal effects in the models, even though they were of small magnitude (0.02 to 0.06), tended to overestimate direct genetic variance and heritability for all traits.

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Using the solutions of the gap equations of the magnetic-color-flavor-locked (MCFL) phase of paired quark matter in a magnetic field, and taking into consideration the separation between the longitudinal and transverse pressures due to the field-induced breaking of the spatial rotational symmetry, the equation of state of the MCFL phase is self-consistently determined. This result is then used to investigate the possibility of absolute stability, which turns out to require a field-dependent ""bag constant"" to hold. That is, only if the bag constant varies with the magnetic field, there exists a window in the magnetic field vs bag constant plane for absolute stability of strange matter. Implications for stellar models of magnetized (self-bound) strange stars and hybrid (MCFL core) stars are calculated and discussed.

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The mass function of cluster-size halos and their redshift distribution are computed for 12 distinct accelerating cosmological scenarios and confronted to the predictions of the conventional flat Lambda CDM model. The comparison with Lambda CDM is performed by a two-step process. First, we determine the free parameters of all models through a joint analysis involving the latest cosmological data, using supernovae type Ia, the cosmic microwave background shift parameter, and baryon acoustic oscillations. Apart from a braneworld inspired cosmology, it is found that the derived Hubble relation of the remaining models reproduces the Lambda CDM results approximately with the same degree of statistical confidence. Second, in order to attempt to distinguish the different dark energy models from the expectations of Lambda CDM, we analyze the predicted cluster-size halo redshift distribution on the basis of two future cluster surveys: (i) an X-ray survey based on the eROSITA satellite, and (ii) a Sunayev-Zeldovich survey based on the South Pole Telescope. As a result, we find that the predictions of 8 out of 12 dark energy models can be clearly distinguished from the Lambda CDM cosmology, while the predictions of 4 models are statistically equivalent to those of the Lambda CDM model, as far as the expected cluster mass function and redshift distribution are concerned. The present analysis suggests that such a technique appears to be very competitive to independent tests probing the late time evolution of the Universe and the associated dark energy effects.

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Context. The distribution of chemical abundances and their variation with time are important tools for understanding the chemical evolution of galaxies. In particular, the study of chemical evolution models can improve our understanding of the basic assumptions made when modelling our Galaxy and other spirals. Aims. We test a standard chemical evolution model for spiral disks in the Local Universe and study the influence of a threshold gas density and different efficiencies in the star formation rate (SFR) law on radial gradients of abundance, gas, and SFR. The model is then applied to specific galaxies. Methods. We adopt a one-infall chemical evolution model where the Galactic disk forms inside-out by means of infall of gas, and we test different thresholds and efficiencies in the SFR. The model is scaled to the disk properties of three Local Group galaxies (the Milky Way, M31 and M33) by varying its dependence on the star formation efficiency and the timescale for the infall of gas onto the disk. Results. Using this simple model, we are able to reproduce most of the observed constraints available in the literature for the studied galaxies. The radial oxygen abundance gradients and their time evolution are studied in detail. The present day abundance gradients are more sensitive to the threshold than to other parameters, while their temporal evolutions are more dependent on the chosen SFR efficiency. A variable efficiency along the galaxy radius can reproduce the present day gas distribution in the disk of spirals with prominent arms. The steepness in the distribution of stellar surface density differs from massive to lower mass disks, owing to the different star formation histories. Conclusions. The most massive disks seem to have evolved faster (i.e., with more efficient star formation) than the less massive ones, thus suggesting a downsizing in star formation for spirals. The threshold and the efficiency of star formation play a very important role in the chemical evolution of spiral disks. For instance, an efficiency varying with radius can be used to regulate the star formation. The oxygen abundance gradient can steepen or flatten in time depending on the choice of this parameter.