41 resultados para 3 Models

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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The mycotoxin aflatoxin B1 (AFB1) is a carcinogenic food contaminant which is metabolically activated by epoxydation. The metabolism of mycotoxins via the mercapturate metabolic pathway was shown, in general, to lead to their detoxication. Mercapturic acids thus formed (S-substitued-N-acetyl-L-cysteines) may be accumulated in the kidney and either excreted in the urine or desacetylated by Acylase 1 (ACY1) to yield cysteine S-conjugates. To be toxic, the N-acetyl-L-cysteine-S-conjugates first have to undergo deacetylation by ACY 1. The specificity and rate of mercapturic acid deacetylation may determine the toxicity, however the exact deacetylation processes involved are not well known. The aim of this study was to investigate the role of ACY1 in the toxicity of some bioactive epoxides from Aflatoxin B1. We characterized the kinetic parameters of porcine kidney and human recombinant aminoacylase-1 towards some aromatic and aliphatic-derived mercapturates analogue of mycotoxin mercapturic acids and 3,4-epoxyprecocene, a bioactive epoxide derivated from aflatoxin. The deacetylation of mercapturated substrates was followed both by reverse phase HPLC and by TNBS method. Catalytic activity was discussed in a structure function relationship. Ours results indicate for the first time that aminoacylase-1 could play an important role in deacetylating mercapturate metabolites of aflatoxin analogues and this process may be in relation with their cyto- and nephrotoxicity in human. (C) 2012 Published by Elsevier Masson SAS.

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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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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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Based on astrophysical constraints derived from Chandrasekhar's mass limit for white dwarfs, we study the effects of the model on the parameters of unparticle-inspired gravity, on scales Lambda(U) > 1 TeV and d(U) approximate to 1.

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Coexistence of sympatric species is mediated by resource partitioning. Pumas occur sympatrically with jaguars throughout most of the jaguar's range but few studies have investigated space partitioning between both species. Here, camera trapping and occupancy models accounting for imperfect detection were employed in a Bayesian framework to investigate space partitioning between the jaguar and puma in Emas National Park (ENP), central Brazil. Jaguars were estimated to occupy 54.1% and pumas 39.3% of the sample sites. Jaguar occupancy was negatively correlated with distance to water and positively correlated with the amount of dense habitat surrounding the camera trap. Puma occupancy only showed a weak negative correlation with distance to water and with jaguar presence. Both species were less often present at the same site than expected under independent distributions. Jaguars had a significantly higher detection probability at cameras on roads than at off-road locations. For pumas, detection was similar on and off-road. Results indicate that both differences in habitat use and active avoidance shape space partitioning between jaguars and pumas in ENP. Considering its size, the jaguar is likely the competitively dominant of the two species. Owing to its habitat preferences, suitable jaguar habitat outside the park is probably sparse. Consequently, the jaguar population is likely largely confined to the park, while the puma population is known to extend into ENP's surroundings. (C) 2011 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.

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In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into a continuous unimodal and symmetric distribution. For each model we compute an approximation to the marginal likelihood, based on the MCMC output. From these approximations we compute Bayes factors and posterior model probabilities. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

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Background: Unstable distal femoral fractures in children are challenging lesions with restricted surgical options for adequate stabilization. Elastic nails have become popular for treating femoral shaft fractures, yet they are still challenging for using in distal fractures. The aim of this study was to test whether end caps (CAP) inserted into the nail extremity improved the mechanical stabilization of a segmental defect at the distal femoral metaphyseal-diaphyseal junction created in an artificial pediatric bone model. Methods: Two 3.5-mm titanium elastic nails (TEN) were introduced intramedullary into pediatric femur models, and a 7.0-mm-thick segmental defect was created at the distal diaphyseal-metaphyseal junction. Nondestructive 4-point bending, axial-bending, and torsion tests were conducted. After this, the end caps were inserted into the external tips of the nails and then screwed into the bone cortex. The mechanical tests were repeated. Stiffness, displacement, and torque were analyzed using the Wilcoxon nonparametric test for paired samples. Results: In the combined axial-bending tests, the TEN + CAP combination was 8.75% stiffer than nails alone (P < 0.01); in torsion tests, the TEN + CAP was 14% stiffer than nails alone (P < 0.01). In contrast, the 4-point bending test did not show differences between the methods (P = 0.91, stiffness; P = 0.51, displacement). Thus, the end caps contributed to an increase in the construct stability for torsion and axial-bending forces but not for 4-point bending forces. Conclusions: These findings indicate that end caps fitted to elastic nails may contribute to the stabilization of fractures that our model mimics (small distal fragment, bone comminution, and distal bone fragment loss).

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We extend the random permutation model to obtain the best linear unbiased estimator of a finite population mean accounting for auxiliary variables under simple random sampling without replacement (SRS) or stratified SRS. The proposed method provides a systematic design-based justification for well-known results involving common estimators derived under minimal assumptions that do not require specification of a functional relationship between the response and the auxiliary variables.

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Galectin-3 has been implicated in the tumor development via its mediation of the Wnt signaling pathway. Likewise, glycogen synthase kinase-3beta (GSK3 beta) also plays a role in the Wnt signaling pathway by controlling the levels of cytoplasmic beta-catenin. Altered GSK3 beta expression has been described in various tumors, but to date, there are no studies evaluating its expression in models of oral carcinogenesis. Additionally, it is unknown whether the absence of galectin-3 regulates the expression of GSK3 beta. To this end, Gal3-deficient (Gal3(-/-)) and wild-type (Gal3(+/+)) male mice were treated with 4NQO for 16 weeks and sacrificed at week 16 and 32. The tongues were removed, processed, and stained with H&E to detect dysplasias and carcinomas. An immunohistochemical assay was performed to determine the level of P-GSK3 beta-Ser9 expression in both groups. Carcinomas were more prevalent in Gal3(+/+) than Gal3(-/-) mice (55.5% vs. 28.5%), but no statistical difference was reached. In the dysplasias, the proportion of cells positive for P-GSK3 beta-Ser9 was slightly higher in Gal3(+/+) than Gal3(-/-) mice (63% vs. 61%). In the carcinomas, a significant difference between Gal3(+/+) and Gal3(-/-) mice was found (74% vs. 59%; p=0.02). P-GSK3 beta-Ser9-positive cells slightly decreased from the progression of dysplasias to carcinomas in Gal3(-/-) mice (61% vs. 59%; p>0.05). However, a significant increase in P-GSK3 beta-Ser9 expression was observed from dysplasias to carcinomas in Gal3(+/+) mice (63% vs. 74%; p=0.01). In conclusion, these findings suggest that fully malignant transformation of the tongue epithelium is associated with increased P-GSK3 beta-Ser9 expression in Gal3(+/+) mice, but not in Gal3(-/-) mice.

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Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

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Thiosemicarbazones are cruzain inhibitors which have been identified as potential antitrypanosomal agents. In this work, several molecular properties were calculated at the density functional theory (DFT)/B3LYP/6-311G* level for a set of 44 thiosemicarbazones. Unsupervised and supervised pattern recognition techniques (hierarchical cluster analysis, principal component analysis, kth-nearest neighbors, and soft independent modeling by class analogy) were used to obtain structureactivity relationship models, which are able to classify unknown compounds according to their activities. The chemometric analyses performed here revealed that 12 descriptors can be considered responsible for the discrimination between high and low activity compounds. Classification models were validated with an external test set, showing that predictive classifications were achieved with the selected variable set. The results obtained here are in good agreement with previous findings from the literature, suggesting that our models can be useful on further investigations on the molecular determinants for the antichagasic activity. (C) 2012 Wiley Periodicals, Inc.

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Introduction: Denosumab, a fully human anti-RANKL monoclonal antibody, reduces the incidence of skeletal-related events in patients with bone metastases from solid tumors. We present survival data for the subset of patients with lung cancer, participating in the phase 3 trial of denosumab versus zoledronic acid (ZA) in the treatment of bone metastases from solid tumors (except breast or prostate) or multiple myeloma. Methods: Patients were randomized 1:1 to receive monthly subcutaneous denosumab 120 mg or intravenous ZA 4 mg. An exploratory analysis, using Kaplan-Meier estimates and proportional hazards models, was performed for overall survival among patients with non-small-cell lung cancer (NSCLC) and SCLC. Results: Denosumab was associated with improved median overall survival versus ZA in 811 patients with any lung cancer (8.9 versus 7.7 months; hazard ratio [HR] 0.80) and in 702 patients with NSCLC (9.5 versus 8.0 months; HR 0.78) (p = 0.01, each comparison). Further analysis of NSCLC by histological type showed a median survival of 8.6 months for denosumab versus 6.4 months for ZA in patients with squamous cell carcinoma (HR 0.68; p = 0.035). Incidence of overall adverse events was balanced between treatment groups; serious adverse events occurred in 66.0% of denosumab-treated patients and 72.9% of ZA-treated patients. Cumulative incidence of osteonecrosis of the jaw was similar between groups (0.7% denosumab versus 0.8% ZA). Hypocalcemia rates were 8.6% with denosumab and 3.8% with ZA. Conclusion: In this exploratory analysis, denosumab was associated with improved overall survival compared with ZA, in patients with metastatic lung cancer.

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The main aim of this work is to investigate the 1-butyl-3-methylimidazolium tetrafluoroborate ([C4C1Im]+[BF4]-) ionic liquid (IL) adsorption on the gamma-Al2O3 (100) by density functional theory calculations to try to rationalize the adsorption as an electrostatic phenomenon. Optimized geometries and interaction energies of IL one-monolayer on the gamma-Al2O3 were obtained on high surface coverage (one cationanion pair per 94.96 nm2). A study of dispersion force was made to estimate its contribution to the adsorption. Overall, the process is ruled by electrostatic interaction between ions and surface. Adsorption of the anion [BF4]- and cation [C4C1Im]+ was also studied by Bader charge analysis and charge density difference for supported and unsupported situations. It is suggested that the IL ions have their charges maintained with significant anion cloud polarization inward to the acid aluminum sites. (c) 2012 Wiley Periodicals, Inc.

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The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.

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We consider the problem of estimating the mean and variance of the time between occurrences of an event of interest (inter-occurrences times) where some forms of dependence between two consecutive time intervals are allowed. Two basic density functions are taken into account. They are the Weibull and the generalised exponential density functions. In order to capture the dependence between two consecutive inter-occurrences times, we assume that either the shape and/or the scale parameters of the two density functions are given by auto-regressive models. The expressions for the mean and variance of the inter-occurrences times are presented. The models are applied to the ozone data from two regions of Mexico City. The estimation of the parameters is performed using a Bayesian point of view via Markov chain Monte Carlo (MCMC) methods.