996 resultados para Pathway Semantics Algorithm (PSA)


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Non-alcoholic fatty liver disease (NAFLD) encompasses the whole spectrum of steatosis, nonalcoholic steatohepatitis (NASH), and NASH-related cirrhosis (NASH/Cir). Although molecular advances have been made in this field, the pathogenesis of NAFLD is not completely understood. The gene expression profiling associated to NASH/Cir was assessed, in an attempt to better characterize the pathways involved in its etiopathogenesis. Methods: In the first step, we used cDNA microarray to evaluate the gene expression profiles in normal liver (n=3) and NASH/Cir samples (n=3) by GeneSifter (TM) analysis to identify differentially expressed genes and biological pathways. Second, tissue microarray was used to determine immunohistochemical expression of phosphorylated mTOR and 4E-BP1 in 11 normal liver samples, 10 NASH/Cir samples and in 37 samples of cirrhosis of other etiologies to further explore the involvement of the mTOR pathway evidenced by the gene expression analysis. Results: 138 and 106 genes were, respectively, up and down regulated in NASH/Cir in comparison to normal liver. Among the 9 pathways identified as significantly modulated in NASH/Cir, the participation of the mTOR pathway was confirmed, since expression of cytoplasmic and membrane phospho-mTOR were higher in NASH/Cir in comparison to cirrhosis of other etiologies and to normal liver. Conclusions: Recent findings have suggested a role for the cellular ""nutrient sensor"" mTOR in NAFLD and the present study corroborates the participation of this pathway in NASH/Cir. Phospho-mTOR evaluation might be of clinical utility as a potential marker for identification of NASH/Cir in cases mistakenly considered as cryptogenic cirrhosis owing to paucity of clinical data.

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Purpose: To evaluate the expression of NF-kappa B pathway genes in total bone marrow samples obtained from MM at diagnosis using real-time quantitative PCR and to evaluate its possible correlation with disease clinical features and survival. Material and methods: Expression of eight genes related to NF-kappa B pathway (NFKB1, IKB, RANK, RANKL, OPG, IL6, VCAM1 and ICAM1) were studied in 53 bone marrow samples from newly diagnosed MM patients and in seven normal controls, using the Taqman system. Genes were considered overexpressed when tumor expression level was at least four times higher than that observed in normal samples. Results: The percentages of overexpression of the eight genes were: NFKB1 0%, IKB 22.6%, RANK 15.1%, RANKL 31.3%, OPG 7.5%, IL6 39.6%, VCAM1 10% and ICAM1 26%. We found association between IL6 expression level and International Staging System (ISS) (p = 0.01), meaning that MM patients with high ISS scores have more chance of overexpression of IL6. The mean value of ICAM1 relative expression was also associated with the ISS score (p = 0.02). Regarding OS, cases with IL6 overexpression present worse evolution than cases with IL6 normal expression (p = 0.04). Conclusion: We demonstrated that total bone marrow aspirates can be used as a source of material for gene expression studies in MM. In this context, we confirmed that IL6 overexpression was significantly associated with worse survival and we described that it is associated with high ISS scores. Also, ICAM1 was overexpressed in 26% of cases and its level was associated with ISS scores.

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The aim of the present study was to examine the impact of polymorphisms in prostate-specific antigen (PSA) and androgen-related genes (AR, CYP17, and CYP19) on prostate cancer (PCa) risk in selected high-risk patients who underwent prostate biopsy. Blood samples and prostate tissues were obtained for DNA analysis. Single-nucleotide polymorphisms in the 50-untranslated regions (UTRs) of the PSA (substitution A > G at position -158) and CYP17 (substitution T > C at 50-UTR) genes were detected by polymerase chain reaction (PCR)-restriction fragment length polymorphism assays. The CAG and TTTA repeats in the AR and CYP19 genes, respectively, were genotyped by PCR-based GeneScan analysis. Patients with the GG genotype of the PSA gene had a higher risk of PCa than those with the AG or AA genotype (OR = 3.79, p = 0.00138). The AA genotype was associated with lower PSA levels (6.44 +/- 1.64 ng/mL) compared with genotypes having at least one G allele (10.44 +/- 10.06 ng/mL) (p = 0.0687, 95% CI - 0.3146 to 8.315, unpaired t-test). The multivariate analysis confirmed the association between PSA levels and PSA genotypes (AA vs. AG+GG; chi(2) = 0.0482) and CYP19 (short alleles homozygous vs. at least one long allele; chi(2) = 0.0110) genotypes. Genetic instability at the AR locus leading to somatic mosaicism was detected in one PCa patient by comparing the length of AR CAG repeats in matched peripheral blood and prostate biopsy cores. Taken together, these findings suggest that the PSA genotype should be a clinically relevant biomarker to predict the PCa risk.

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This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

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Context. B[e] supergiants are luminous, massive post-main sequence stars exhibiting non-spherical winds, forbidden lines, and hot dust in a disc-like structure. The physical properties of their rich and complex circumstellar environment (CSE) are not well understood, partly because these CSE cannot be easily resolved at the large distances found for B[e] supergiants (typically greater than or similar to 1 kpc). Aims. From mid-IR spectro-interferometric observations obtained with VLTI/MIDI we seek to resolve and study the CSE of the Galactic B[e] supergiant CPD-57 degrees 2874. Methods. For a physical interpretation of the observables (visibilities and spectrum) we use our ray-tracing radiative transfer code (FRACS), which is optimised for thermal spectro-interferometric observations. Results. Thanks to the short computing time required by FRACS (<10 s per monochromatic model), best-fit parameters and uncertainties for several physical quantities of CPD-57 degrees 2874 were obtained, such as inner dust radius, relative flux contribution of the central source and of the dusty CSE, dust temperature profile, and disc inclination. Conclusions. The analysis of VLTI/MIDI data with FRACS allowed one of the first direct determinations of physical parameters of the dusty CSE of a B[e] supergiant based on interferometric data and using a full model-fitting approach. In a larger context, the study of B[e] supergiants is important for a deeper understanding of the complex structure and evolution of hot, massive stars.

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beta-Hydroxy-beta-methylbutyrate (HM beta) supplementation is used to treat cancer, sepsis and exercise-induced muscle damage. However, its effects on animal and human health and the consequences of this treatment in other tissues (e. g., fat and liver) have not been examined. The purpose of this study was to evaluate the effects of HM beta supplementation on skeletal muscle hypertrophy and the expression of proteins involved in insulin signalling. Rats were treated with HM beta (320 mg/kg body weight) or saline for one month. The skeletal muscle hypertrophy and insulin signalling were evaluated by western blotting, and hormonal concentrations were evaluated using ELISAs. HM beta supplementation induced muscle hypertrophy in the extensor digitorum longus (EDL) and soleus muscles and increased serum insulin levels, the expression of the mammalian target of rapamycin (mTOR) and phosphorylation of p70S6K in the EDL muscle. Expression of the insulin receptor was increased only in liver. Thus, our results suggest that HM beta supplementation can be used to increase muscle mass without adverse health effects.

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The purpose of the present study was to evaluate the effects of 8 weeks of strength and power training on the expression of genes related to the canonical WNT pathway and beta-catenin protein levels in physically active men. Twenty-five subjects (27.4 +/- A 4.6 years) were balanced based on their relative maximum strength in the squat exercise (squat 1RM/body mass) and randomly assigned to strength training (ST) (n = 10), power training (PT) (n = 10), and control (C) (n = 5) groups. The ST and the PT groups performed high and low intensity squats, respectively, thrice a week, for 8 weeks. Muscle biopsies from the vastus lateralis muscle were collected before and after the training period. Relative strength and power increased similarly in both ST and PT groups (P < 0.001). Fiber cross-sectional area also increased similarly in both ST and PT groups. Gene expression and beta-catenin protein expression levels were assessed by real-time PCR and Western blot. Certain genes were up-regulated in the ST group (WNT1: 6.4-fold, P < 0.0001; SFRP1: 3.3-fold, P < 0.0001 and LEF1: 7.3-fold, P < 0.0001) and also in the PT group (WNT1: 24.9-fold, P < 0.0001; SFRP1: 2.7-fold, P < 0.0001; LEF1: 34.1-fold, P < 0.0001 and Cyclin D1: 7.7-fold, P < 0.001). In addition, the expression of key WNT pathway genes was substantially more responsive to PT than to ST (WNT1: P < 0.0001; LEF1: P < 0.0001 and Cyclin D1: P < 0.001). Finally, the total beta-catenin protein content increased only in the PT group (P < 0.05). Our data indicate that a PT regimen triggers greater responses in key elements of the WNT pathway.

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Cardiomyocyte hypertrophy occurs in response to a variety of physiological and pathological stimuli. While pathological hypertrophy in heart failure is usually coupled with depressed contractile function, physiological hypertrophy associates with increased contractility. In the present study, we explored whether 8 weeks of moderate intensity exercise training would lead to a cardiac anti-remodelling effect in an experimental model of heart failure associated with a deactivation of a pathological (calcineurin/NFAT, CaMKII/HDAC) or activation of a physiological (Akt-mTOR) hypertrophy signalling pathway. The cardiac dysfunction, exercise intolerance, left ventricle dilatation, increased heart weight and cardiomyocyte hypertrophy from mice lacking alpha(2A) and alpha(2C) adrenoceptors (alpha(2A)/alpha(2C)ARKO mice) were associated with sympathetic hyperactivity induced heart failure. The relative contribution of Ca(2+)-calmodulin high-affinity (calcineurin/NFAT) and low-affinity (CaMKII/HDAC) targets to pathological hypertrophy of alpha(2A)/alpha(2C)ARKO mice was verified. While nuclear calcineurin B, NFATc3 and GATA-4 translocation were significantly increased in alpha(2A)/alpha(2C)ARKO mice, no changes were observed in CaMKII/HDAC activation. As expected, cyclosporine treatment decreased nuclear translocation of calcineurin/NFAT in alpha(2A)/alpha(2C)ARKO mice, which was associated with improved ventricular function and a pronounced anti-remodelling effect. The Akt/mTOR signalling pathway was not activated in alpha(2A)/alpha(2C)ARKO mice. Exercise training improved cardiac function and exercise capacity in alpha(2A)/alpha(2C)ARKO mice and decreased heart weight and cardiomyocyte width paralleled by diminished nuclear NFATc3 and GATA-4 translocation as well as GATA-4 expression levels. When combined, these findings support the notion that deactivation of calcineurin/NFAT pathway-induced pathological hypertrophy is a preferential mechanism by which exercise training leads to the cardiac anti-remodelling effect in heart failure.

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The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

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The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

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In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

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The general flowshop scheduling problem is a production problem where a set of n jobs have to be processed with identical flow pattern on in machines. In permutation flowshops the sequence of jobs is the same on all machines. A significant research effort has been devoted for sequencing jobs in a flowshop minimizing the makespan. This paper describes the application of a Constructive Genetic Algorithm (CGA) to makespan minimization on flowshop scheduling. The CGA was proposed recently as an alternative to traditional GA approaches, particularly, for evaluating schemata directly. The population initially formed only by schemata, evolves controlled by recombination to a population of well-adapted structures (schemata instantiation). The CGA implemented is based on the NEH classic heuristic and a local search heuristic used to define the fitness functions. The parameters of the CGA are calibrated using a Design of Experiments (DOE) approach. The computational results are compared against some other successful algorithms from the literature on Taillard`s well-known standard benchmark. The computational experience shows that this innovative CGA approach provides competitive results for flowshop scheduling; problems. (C) 2007 Elsevier Ltd. All rights reserved.

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This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

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This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

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This paper presents a free software tool that supports the next-generation Mobile Communications, through the automatic generation of models of components and electronic devices based on neural networks. This tool enables the creation, training, validation and simulation of the model directly from measurements made on devices of interest, using an interface totally oriented to non-experts in neural models. The resulting model can be exported automatically to a traditional circuit simulator to test different scenarios.