40 resultados para NETWORK ANALYSIS
Resumo:
Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.
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ABSTRACT The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation.
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To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR,MAPK14, BCL2L1, KRT18,PTPN6, CASP3, TGFBR2,AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.
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The genomic sequences of the Envelope-Non-Structural protein 1 junction region (E/NS1) of 84 DEN-1 and 22 DEN-2 isolates from Brazil were determined. Most of these strains were isolated in the period from 1995 to 2001 in endemic and regions of recent dengue transmission in São Paulo State. Sequence data for DEN-1 and DEN-2 utilized in phylogenetic and split decomposition analyses also include sequences deposited in GenBank from different regions of Brazil and of the world. Phylogenetic analyses were done using both maximum likelihood and Bayesian approaches. Results for both DEN-1 and DEN-2 data are ambiguous, and support for most tree bipartitions are generally poor, suggesting that E/NS1 region does not contain enough information for recovering phylogenetic relationships among DEN-1 and DEN-2 sequences used in this study. The network graph generated in the split decomposition analysis of DEN-1 does not show evidence of grouping sequences according to country, region and clades. While the network for DEN-2 also shows ambiguities among DEN-2 sequences, it suggests that Brazilian sequences may belong to distinct subtypes of genotype III.
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Objectives: Evaluate the production and the research collaborative network on Leishmaniasis in South America. Methods: A bibliometric research was carried out using SCOPUS database. The analysis unit was original research articles published from 2000 to 2011, that dealt with leishmaniasis and that included at least one South American author. The following items were obtained for each article: journal name, language, year of publication, number of authors, institutions, countries, and others variables. Results: 3,174 articles were published, 2,272 of them were original articles. 1,160 different institutional signatures, 58 different countries and 398 scientific journals were identified. Brazil was the country with more articles (60.7%) and Oswaldo Cruz Foundation (FIOCRUZ) had 18% of Brazilian production, which is the South American nucleus of the major scientific network in Leishmaniasis. Conclusions: South American scientific production on Leishmaniasis published in journals indexed in SCOPUS is focused on Brazilian research activity. It is necessary to strengthen the collaboration networks. The first step is to identify the institutions with higher production, in order to perform collaborative research according to the priorities of each country.
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Liver transplantation is now the standard treatment for end-stage liver disease. Given the shortage of liver donors and the progressively higher number of patients waiting for transplantation, improvements in patient selection and optimization of timing for transplantation are needed. Several solutions have been suggested, including increasing the donor pool; a fair policy for allocation, not permitting variables such as age, gender, and race, or third-party payer status to play any role; and knowledge of the natural history of each liver disease for which transplantation is offered. To observe ethical rules and distributive justice (guarantee to every citizen the same opportunity to get an organ), the "sickest first" policy must be used. Studies have demonstrated that death has no relationship with waiting time, but rather with the severity of liver disease at the time of inclusion. Thus, waiting time is no longer part of the United Network for Organ Sharing distribution criteria. Waiting time only differentiates between equally severely diseased patients. The authors have analyzed the waiting list mortality and 1-year survival for patients of the State of São Paulo, from July 1997 through January 2001. Only the chronological criterion was used. According to "Secretaria de Estado da Saúde de São Paulo" data, among all waiting list deaths, 82.2% occurred within the first year, and 37.6% within the first 3 months following inclusion. The allocation of livers based on waiting time is neither fair nor ethical, impairs distributive justice and human rights, and does not occur in any other part of the world.
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Culture forms of four strains of Endotrypanum (E. schaudinni and E. monterogeii) were processed for transmission electron microscopy and analyzed at the ultrastructural level. Quantitative data about some cytoplasmic organelles were obeined by stereology. All culture forms were promastigotes. In their cytoplasm four different organelles could be found: lipid inclusions (0,2-0,4 µm in diameter), mebrane-bounded vacuoles (0.10-0,28 µm in diameter), glycosomes (0,2-0,3 µm in diameter), and the mitochondrion. The kenetoplast appears as a thin band, except for the strain IM201, which possesses a broader structure, and possibly is not a member of this genus. Clusters of virus-like particles were seen in the cytoplasm of the strain LV88. The data obtained show that all strains have the typical morphological feature of the trypanosomatids. Only strain IM201 could be differentiated from the others, due to its larger kenetoplast-DNA network and its large mitochondrial and glycosomal relative volume. The morphometrical data did not allow the differentiation between E. schaudinni (strains IM217 and M6226) and E. monterogeii (strain LV88).
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Recently we cloned and sequenced the first eight Trypanosoma cruzi polymorphic microsatellite loci and studied 31 clones and strains to obtain valuable information about the population structure of the parasite. We have now studied 23 further strains, increasing from 11 to 31 the number of strains obtained from patients with chronic Chagas disease. This expanded set of 54 strains and clones analyzed with the eight microsatellites markers confirmed the previously observed diploidy, clonal population organization and very high polymorphism of T. cruzi. Moreover, this new study disclosed two new features of the population genetic structure of T. cruzi. The first was the discovery that, similarly to what we had previously shown for strains isolated from insect vectors, mammals and humans with acute disease, isolates from patients in the chronic phase of Chagas disease could also be multiclonal, albeit at a reduced proportion. Second, when we used parsimony to display the genetic relationship among the clonal lineages in an unrooted Wagner network we observed, like before, a good correlation of the tree topography with the classification in three clusters on the basis of single locus analysis of the ribosomal RNA genes. However, a significant new finding was that now the strains belonging to cluster 2 split in two distant sub-clusters. This observation suggests that the evolutionary history of T. cruzi may be more complex than we previously thought.
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We previously reported that alloxan-induced diabetes results in reduction in the number and reactivity of mast cells at different body sites. In this study, the influence of diabetes on thymic mast cells was investigated. Thymuses from diabetic rats showed marked alterations including shrinkage, thymocyte depletion, and increase in the extracellular matrix network, as compared to those profiles seen in normal animals. Nevertheless, we noted that the number and reactivity of mast cells remained unchanged. These findings indicate that although diabetes leads to critical alterations in the thymus, the local mast cell population is refractory to its effect. This suggests that thymic mast cells are under a different regulation as compared to those located in other tissues.
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The number of sequences generated by genome projects has increased exponentially, but gene characterization has not followed at the same rate. Sequencing and analysis of full-length cDNAs is an important step in gene characterization that has been used nowadays by several research groups. In this work, we have selected Schistosoma mansoni clones for full-length sequencing, using an algorithm that investigates the presence of the initial methionine in the parasite sequence based on the positions of alignment start between two sequences. BLAST searches to produce such alignments have been performed using parasite expressed sequence tags produced by Minas Gerais Genome Network against sequences from the database Eukaryotic Cluster of Orthologous Groups (KOG). This procedure has allowed the selection of clones representing 398 proteins which have not been deposited as S. mansoni complete CDS in any public database. Dedicated sequencing of 96 of such clones with reads from both 5' and 3' ends has been performed. These reads have been assembled using PHRAP, resulting in the production of 33 full-length sequences that represent novel S. mansoni proteins. These results shall contribute to construct a more complete view of the biology of this important parasite.
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Nuclear internal transcribed spacer 2 (ITS2) rDNA sequences were used for a molecular phylogenetics analysis of five Onchocerca species. The sister species of the human parasite O. volvulus was found to be the cattle parasite O. ochengi and not O. gibsoni, contrary to chromosomal evidence. The genetic differentiation of two African populations (representing the two African strains) and a Brazilian population of O. volvulus was also studied. Phylogenetic and network reconstruction did not show any clustering of ITS2 alleles on geographic or strain grounds. Furthermore, population genetics tests showed no indication of population differentiation but suggested gene flow among the three populations.
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Objective: To build a theoretical model to configure the network social support experience of people involved in home care. Method: A quantitative approach research, utilizing the Grounded Theory method. The simultaneous data collection and analysis allowed the interpretation of the phenomenon meaning The network social support of people involved in home care. Results: The population passive posture in building their well-being was highlighted. The need of a shared responsibility between the involved parts, population and State is recognized. Conclusion: It is suggested for nurses to be stimulated to amplify home care to attend the demands of caregivers; and to elaborate new studies with different populations, to validate or complement the proposed theoretical model.
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Exploratory and descriptive study based on quantitative and qualitative methods that analyze the phenomenon of violence against adolescents based on gender and generational categories. The data source was reports of violence from the Curitiba Protection Network from 2010 to 2012 and semi-structured interviews with 16 sheltered adolescents. Quantitative data were analyzed using SPSS software version 20.0 and the qualitative data were subjected to content analysis. The adolescents were victims of violence in the household and outside of the family environment, as victims or viewers of violence. The violence was experienced at home, mostly toward girls, with marked overtones of gender violence. More than indicating the magnitude of the issue, this study can give information to help qualify the assistance given to victimized people and address how to face this issue.
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Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.
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Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q²) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.