17 resultados para data movement problem

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Background: Several studies in Drosophila have shown excessive movement of retrogenes from the X chromosome to autosomes, and that these genes are frequently expressed in the testis. This phenomenon has led to several hypotheses invoking natural selection as the process driving male-biased genes to the autosomes. Metta and Schlotterer (BMC Evol Biol 2010, 10:114) analyzed a set of retrogenes where the parental gene has been subsequently lost. They assumed that this class of retrogenes replaced the ancestral functions of the parental gene, and reported that these retrogenes, although mostly originating from movement out of the X chromosome, showed female-biased or unbiased expression. These observations led the authors to suggest that selective forces (such as meiotic sex chromosome inactivation and sexual antagonism) were not responsible for the observed pattern of retrogene movement out of the X chromosome. Results: We reanalyzed the dataset published by Metta and Schlotterer and found several issues that led us to a different conclusion. In particular, Metta and Schlotterer used a dataset combined with expression data in which significant sex-biased expression is not detectable. First, the authors used a segmental dataset where the genes selected for analysis were less testis-biased in expression than those that were excluded from the study. Second, sex-biased expression was defined by comparing male and female whole-body data and not the expression of these genes in gonadal tissues. This approach significantly reduces the probability of detecting sex-biased expressed genes, which explains why the vast majority of the genes analyzed (parental and retrogenes) were equally expressed in both males and females. Third, the female-biased expression observed by Metta and Schltterer is mostly found for parental genes located on the X chromosome, which is known to be enriched with genes with female-biased expression. Fourth, using additional gonad expression data, we found that autosomal genes analyzed by Metta and Schlotterer are less up regulated in ovaries and have higher chance to be expressed in meiotic cells of spermatogenesis when compared to X-linked genes. Conclusions: The criteria used to select retrogenes and the sex-biased expression data based on whole adult flies generated a segmental dataset of female-biased and unbiased expressed genes that was unable to detect the higher propensity of autosomal retrogenes to be expressed in males. Thus, there is no support for the authors' view that the movement of new retrogenes, which originated from X-linked parental genes, was not driven by selection. Therefore, selection-based genetic models remain the most parsimonious explanations for the observed chromosomal distribution of retrogenes.

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Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

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The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

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Introduction: Cytokines and chemokines regulate bone remodeling during orthodontic tooth movement. CC chemokine ligand 2 (CCL2) is involved in osteoclast recruitment and activity, and its expression is increased in periodontal tissues under mechanical loading. In this study, we investigated whether the CC chemokine receptor 2 (CCR2)-CCL2 axis influences orthodontic tooth movement. Methods: A coil spring was placed in CCR2-deficient (CCR2(-/-)), wild-type, vehicle-treated, and P8A-treated (CCL2 analog) mice. In a histopathologic analysis, the amounts of orthodontic tooth movement and numbers of osteoclasts were determined. The expression of mediators involved in bone remodeling was evaluated by real-time polymerase chain reaction. Results: Orthodontic tooth movement and the number of TRAP-positive cells were significantly decreased in CCR2(-/-) and P8A-treated mice in relation to wild-type and vehicle-treated mice, respectively. The expressions of RANKL, RANK, and osteoblasts markers (COL-1 and OCN) were lower in CCR2(-/-) than in wild-type mice. No significant difference was found in osteoprotegerin levels between the groups. Conclusions: These data suggested a reduction of osteoclast and osteoblast activities in the absence of CCR2. The CCR2-CCL2 axis is positively associated with osteoclast recruitment, bone resorption, and orthodontic tooth movement. Therefore, blockage of the CCR2-CCL2 axis might be used in the future for modulating the extent of orthodontic tooth movement. (Am J Orthod Dentofacial Orthop 2012;141:153-60)

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Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

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The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

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Objectives: The Brazilian public health system does not provide electroconvulsive therapy (ECT), which is limited to a few academic services. National mental health policies are against ECT. Our objectives were to analyze critically the public policies toward ECT and present the current situation using statistics from the Institute of Psychiatry of the University of Sao Paulo (IPq-HCFMUSP) and summary data from the other 13 ECT services identified in the country. Methods: Data regarding ECT treatment at the IPq-HCFMUSP were collected from January 2009 to June 2010 (demographical, number of sessions, and diagnoses). All the data were analyzed using SPSS 19, Epic Info 2000, and Excel. Results: During this period, 331 patients were treated at IPq-HCFMUSP: 221 (67%) were from Sao Paulo city, 50 (15.2%) from Sao Paulo's metropolitan area, 39 (11.8%) from Sao Paulo's countryside, and 20 (6.1%) from other states; 7352 ECT treatments were delivered-63.0% (4629) devoted entirely via the public health system (although not funded by the federal government); the main diagnoses were a mood disorder in 86.4% and schizophrenia in 7.3% of the cases. Conclusions: There is an important lack of public assistance for ECT, affecting mainly the poor and severely ill patients. The university services are overcrowded and cannot handle all the referrals. The authors press for changes in the mental health policies.

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When a physical activity professional is teaching a motor skill, he evaluates the movement's learner and considers which interventions could be done at the moment. However, many times the instructor does not have such resources which could help him/her to evaluate the learner movement. The skill acquisition process could be facilitated if instructors could have an instrument that identifies errors, prioritizing information to be given to the learner. Considering that the specialized literature presents a lack of information about such tool, the purpose of this study was to develop, and to determine the objectivity and reliability of an instrument to assess the movement quality of the basketball free throw shooting. The checklist was developed and evaluated by basketball experts. Additionally, the checklist was used to assess 10 trials (edited video) from four individuals in different learning stages. Data were organized by the critical error and the error sum appointed by the experts in two different occasions (one week interval). Contrasting both evaluations, and also, contrasting different experts assessments, in sum and critical error, it was observed an average error of 16.9%. It was concluded that the checklist to assess the basketball free throw is reliable, and could help instructors to make a qualitative analysis. Moreover, the checklist may allow instructors to make assumptions on the motor learning process.

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Introduction: This research project examined influence of the doctors' speciality on primary health care (PHC) problem solving in Belo Horizonte (BH) Brazil, comparing homeopathic with family health doctors (FH), from the management's and the patients' viewpoint. In BH, both FH and homeopathic doctors work in PHC. The index of resolvability (IR) is used to compare resolution of problems by doctors. Methods: The present research compared IR, using official data from the Secretariat of Health and test requests made by the doctors and 482 structured interviews with patients. A total of 217,963 consultations by 14 homeopaths and 67 FH doctors between 1 July 2006 and 30 June 2007 were analysed. Results: The results show significant differences greater problem resolution by homeopaths compared to FH doctors. Conclusion: In BH, the medical speciality, homeopathy or FH, has an impact on problem solving, both from the managers' and the patients' point of view. Homeopaths request fewer tests and have better IR compared with FH doctors. Specialisation in homeopathy is an independent positive factor in problem solving at PHC level in BH, Brazil. Homeopathy (2012) 101, 44-50.

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During orthodontic tooth movement (OTM), alveolar bone is resorbed by osteoclasts in compression sites (CS) and is deposited by osteoblasts in tension sites (TS). The aim of this study was to develop a standardized OTM protocol in mice and to investigate the expression of bone resorption and deposition markers in CS and TS. An orthodontic appliance was placed in C57BL6/J mice. To define the ideal orthodontic force, the molars of the mice were subjected to forces of 0.1 N, 0.25 N, 0.35 N and 0.5 N. The expression of mediators that are involved in bone remodeling at CS and TS was analyzed using a Real-Time PCR. The data revealed that a force of 0.35 N promoted optimal OTM and osteoclast recruitment without root resorption. The levels of TNF-alpha, RANKL, MMP13 and OPG were all altered in CS and TS. Whereas TNF-a and Cathepsin K exhibited elevated levels in CS. RUNX2 and OCN levels were higher in TS. Our results suggest that 0.35 N is the ideal force for OTM in mice and has no side effects. Moreover, the expression of bone remodeling markers differed between the compression and the tension areas, potentially explaining the distinct cellular migration and differentiation patterns in each of these sites. (C) 2012 Elsevier Ltd. All rights reserved.

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Introduction: The aim of the present work was to evaluate the resistance to flexural fatigue of Reciproc R25 nickel-titanium files, 25 mm, used in continuous rotation motion or reciprocation motion, in dynamic assays device. Methods: Thirty-six Reciproc R25 files were divided into 2 groups (n = 18) according to kinematics applied, continuous rotary (group CR) and reciprocation motion (group RM). The files were submitted to dynamic assays device moved by an electric engine with 300 rpm of speed that permitted the reproduction of pecking motion. The files run on a ring's groove of temperate steel, simulating instrumentation of a curved root canal with 400 and 5 mm of curvature radius. The fracture of file was detected by sensor of device, and the time was marked. The data were analyzed statistically by Student's t test, with level of significance of 95%. Results: The instruments moved by reciprocating movement reached significantly higher numbers of cycles before fracture (mean, 1787.78 cycles) when compared with instruments moved by continuous rotary (mean, 816.39 cycles). Conclusions: The results showed that the reciprocation motion improves flexural fatigue resistance in nickel-titanium instrument Reciproc R25 when compared with continuous rotation movement. (J Endod 2012;38:684-687)

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Phycodnaviruses have a significant role in modulating the dynamics of phytoplankton, thereby influencing community structure and succession, nutrient cycles and potentially atmospheric composition because phytoplankton fix about half the carbon dioxide (CO2) on the planet, and some algae release dimethylsulphoniopropionate when lysed by viruses. Despite their ecological importance and widespread distribution, relatively little is known about the evolutionary history, phylogenetic relationships and phylodynamics of the Phycodnaviruses from freshwater environments. Herein we provide novel data on Phycodnaviruses from the largest river system on earth-the Amazon Basin-that were compared with samples from different aquatic systems from several places around the world. Based on phylogenetic inference using DNA polymerase (pol) sequences we show the presence of distinct populations of Phycodnaviridae. Preliminary coarse-grained phylodynamics and phylogeographic inferences revealed a complex dynamics characterized by long-term fluctuations in viral population sizes, with a remarkable worldwide reduction of the effective population around 400 thousand years before the present (KYBP), followed by a recovery near to the present time. Moreover, we present evidence for significant viral gene flow between freshwater environments, but crucially almost none between freshwater and marine environments. The ISME Journal (2012) 6, 237-247; doi: 10.1038/ismej.2011.93; published online 28 July 2011

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Determination of the utility harmonic impedance based on measurements is a significant task for utility power-quality improvement and management. Compared to those well-established, accurate invasive methods, the noninvasive methods are more desirable since they work with natural variations of the loads connected to the point of common coupling (PCC), so that no intentional disturbance is needed. However, the accuracy of these methods has to be improved. In this context, this paper first points out that the critical problem of the noninvasive methods is how to select the measurements that can be used with confidence for utility harmonic impedance calculation. Then, this paper presents a new measurement technique which is based on the complex data-based least-square regression, combined with two techniques of data selection. Simulation and field test results show that the proposed noninvasive method is practical and robust so that it can be used with confidence to determine the utility harmonic impedances.

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Abstract Background The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.

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Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.