984 resultados para tool-soil interaction


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We studied the behavior of virgin queens of the stingless bee species Schwarziana quadripunctata, Paratrigona lineata and Tetragona clavipes, investigating internal nest activities, including the cell provisioning and oviposition process. We made direct observation of queen behavior, with the aid of video filming. Forty-four virgin queens of S. quadripunctata were observed; one was larger and more attractive than the others. Miniature queens were more abundant than normal-size queens; both were found in prison chambers. Agonistic behavior between virgin and physogastric queens of P. lineata was observed during attempts at queen supersedure. After the disappearance of the physogastric queen and the appearance of a virgin queen in T. clavipes nests, the brood cells were sealed with pollen alone, but no egg. In all three species, the presence of one or more virgin queens appeared to make the colonies nervous, even though constant production of virgin queens is vital to the survival of the colony and is part of the colony cycle in these bees.

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We show that carbon nanotubes (CNTs) with high density of defects can present a strong electronic interaction with nanoparticles of Pt-Ru with average particle size of 3.5 +/- 0.8 nm. Depending on the Pt-Ru loading on the CNTs, CO and methanol oxidation reactions suggest there is a charge transfer between Pt-Ru that in turn provokes a decrease in the electronic interaction taking place between Ru and Pt in the PtRu alloy. The CO stripping potentials were observed at about 0.65 and 0.5 V for Pt-Ru/CNT electrodes with Pt-Ru loadings of 10 and 20, and 30 wt %, respectively. (C) 2008 The Electrochemical Society. [DOI: 10.1149/1.2990222] All rights reserved.

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Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. Results: We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. Conclusions: ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

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Background: The Borg Scale may be a useful tool for heart failure patients to self-monitor and self-regulate exercise on land or in water (hydrotherapy) by maintaining the heart rate (HR) between the anaerobic threshold and respiratory compensation point. Methods and Results: Patients performed a cardiopulmonary exercise test to determine their anaerobic threshold/respiratory compensation points. The percentage of the mean HR during the exercise session in relation to the anaerobic threshold HR (%EHR-AT), in relation to the respiratory compensation point (%EHR-RCP), in relation to the peak HR by the exercise test (%EHR-Peak) and in relation to the maximum predicted HR (%EHR-Predicted) was calculated. Next, patients were randomized into the land or water exercise group. One blinded investigator instructed the patients in each group to exercise at a level between ""relatively easy and slightly tiring"". The mean HR throughout the 30-min exercise session was recorded. The %EHR-AT and %EHR-Predicted did not differ between the land and water exercisegroups, but they differed in the %EHR-RCP (95 +/- 7 to 86 +/- 7. P<0.001) and in the %EHR-Peak (85 +/- 8 to 78 +/- 9, P=0.007). Conclusions: Exercise guided by the Borg scale maintains the patient's HR between the anaerobic threshold and respiratory compensation point (ie, in the exercise training zone). (Circ J 2009; 73: 1871-1876)

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Background: Genetic polymorphisms of the TCF7L2 gene are strongly associated with large increments in type 2 diabetes risk in different populations worldwide. In this study, we aimed to confirm the effect of the TCF7L2 polymorphism rs7903146 on diabetes risk in a Brazilian population and to assess the use of this genetic marker in improving diabetes risk prediction in the general population. Methods: We genotyped the single nucleotide polymorphisms (SNP) rs7903146 of the TCF7L2 gene in 560 patients with known coronary disease enrolled in the MASS II (Medicine, Angioplasty, or Surgery Study) Trial and in 1,449 residents of Vitoria, in Southeast Brazil. The associations of this gene variant to diabetes risk and metabolic characteristics in these two different populations were analyzed. To access the potential benefit of using this marker for diabetes risk prediction in the general population we analyzed the impact of this genetic variant on a validated diabetes risk prediction tool based on clinical characteristics developed for the Brazilian general population. Results: SNP rs7903146 of the TCF7L2 gene was significantly associated with type 2 diabetes in the MASS-II population (OR = 1.57 per T allele, p = 0.0032), confirming, in the Brazilian population, previous reports of the literature. Addition of this polymorphism to an established clinical risk prediction score did not increased model accuracy (both area under ROC curve equal to 0.776). Conclusion: TCF7L2 rs7903146 T allele is associated with a 1.57 increased risk for type 2 diabetes in a Brazilian cohort of patients with known coronary heart disease. However, the inclusion of this polymorphism in a risk prediction tool developed for the general population resulted in no improvement of performance. This is the first study, to our knowledge, that has confirmed this recent association in a South American population and adds to the great consistency of this finding in studies around the world. Finally, confirming the biological association of a genetic marker does not guarantee improvement on already established screening tools based solely on demographic variables.

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Introduction: Laparoscopic liver resections are becoming a common procedure, and bleeding remains the major concern during parenchymal transection. Total vascular inflow occlusion can be performed, but ischemic reperfusion injuries can lead to postoperative morbidity. On the other hand, hemihepatic inflow occlusion, leading to hemiliver ischemia, decreases the amount of liver parenchyma submitted to reperfusion damage and offers the advantage of reduced blood loss. Objective: The aim of this work was to describe our experience with laparoscopic the half-Pringle maneuver for segmentar or nonanatomic liver resctions. Patients and Methods: Eight patients submitted to laparoscopic liver resection in a single tertiary center. Results: There were 5 women and 3 men with a mean age of 40.2 years (range, 26-54). Mean tumor size was 4.1 cm (range, 2.6-6.0), and mean hospital stay was 3.1 days (1-5). There were 3 liver adenomas, 2 hepatocellular carcinomas, 1 metastatic melanoma, 1 metastatic colorectal carcinoma, and 1 peripheral colangiocarcinoma. No postoperative complications or mortalities were observed. Conclusions: Results demonstrate that laparoscopic liver resection with the half-Pringle maneuver is feasible and safe and may be included in the technical armamentarium of laparoscopic liver resections for a selected group of patients.

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Background: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. Methods/Principal Findings: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of ""what if'' situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. Conclusion/Significance: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.

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Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

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Melanoma is a highly aggressive and therapy resistant tumor for which the identification of specific markers and therapeutic targets is highly desirable. We describe here the development and use of a bioinformatic pipeline tool, made publicly available under the name of EST2TSE, for the in silico detection of candidate genes with tissue-specific expression. Using this tool we mined the human EST (Expressed Sequence Tag) database for sequences derived exclusively from melanoma. We found 29 UniGene clusters of multiple ESTs with the potential to predict novel genes with melanoma-specific expression. Using a diverse panel of human tissues and cell lines, we validated the expression of a subset of three previously uncharacterized genes (clusters Hs.295012, Hs.518391, and Hs.559350) to be highly restricted to melanoma/melanocytes and named them RMEL1, 2 and 3, respectively. Expression analysis in nevi, primary melanomas, and metastatic melanomas revealed RMEL1 as a novel melanocytic lineage-specific gene up-regulated during melanoma development. RMEL2 expression was restricted to melanoma tissues and glioblastoma. RMEL3 showed strong up-regulation in nevi and was lost in metastatic tumors. Interestingly, we found correlations of RMEL2 and RMEL3 expression with improved patient outcome, suggesting tumor and/or metastasis suppressor functions for these genes. The three genes are composed of multiple exons and map to 2q12.2, 1q25.3, and 5q11.2, respectively. They are well conserved throughout primates, but not other genomes, and were predicted as having no coding potential, although primate-conserved and human-specific short ORFs could be found. Hairpin RNA secondary structures were also predicted. Concluding, this work offers new melanoma-specific genes for future validation as prognostic markers or as targets for the development of therapeutic strategies to treat melanoma.

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We introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and from biomass burning aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostics include the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between the simulated biomass burning aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM(2.5)) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosondes and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained.

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Background: Bayesian mixing models have allowed for the inclusion of uncertainty and prior information in the analysis of trophic interactions using stable isotopes. Formulating prior distributions is relatively straightforward when incorporating dietary data. However, the use of data that are related, but not directly proportional, to diet (such as prey availability data) is often problematic because such information is not necessarily predictive of diet, and the information required to build a reliable prior distribution for all prey species is often unavailable. Omitting prey availability data impacts the estimation of a predator's diet and introduces the strong assumption of consumer ultrageneralism (where all prey are consumed in equal proportions), particularly when multiple prey have similar isotope values. Methodology: We develop a procedure to incorporate prey availability data into Bayesian mixing models conditional on the similarity of isotope values between two prey. If a pair of prey have similar isotope values (resulting in highly uncertain mixing model results), our model increases the weight of availability data in estimating the contribution of prey to a predator's diet. We test the utility of this method in an intertidal community against independently measured feeding rates. Conclusions: Our results indicate that our weighting procedure increases the accuracy by which consumer diets can be inferred in situations where multiple prey have similar isotope values. This suggests that the exchange of formalism for predictive power is merited, particularly when the relationship between prey availability and a predator's diet cannot be assumed for all species in a system.

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Background: Reactivation of p53 by either gene transfer or pharmacologic approaches may compensate for loss of p19Arf or excess mdm2 expression, common events in melanoma and glioma. In our previous work, we constructed the pCLPG retroviral vector where transgene expression is controlled by p53 through a p53-responsive promoter. The use of this vector to introduce p19Arf into tumor cells that harbor p53wt should yield viral expression of p19Arf which, in turn, would activate the endogenous p53 and result in enhanced vector expression and tumor suppression. Since nutlin-3 can activate p53 by blocking its interaction with mdm2, we explored the possibility that the combination of p19Arf gene transfer and nutlin-3 drug treatment may provide an additive benefit in stimulating p53 function. Methods: B16 (mouse melanoma) and C6 (rat glioma) cell lines, which harbor p53wt, were transduced with pCLPGp19 and these were additionally treated with nutlin-3 or the DNA damaging agent, doxorubicin. Viral expression was confirmed by Western, Northern and immunofluorescence assays. p53 function was assessed by reporter gene activity provided by a p53-responsive construct. Alterations in proliferation and viability were measured by colony formation, growth curve, cell cycle and MTT assays. In an animal model, B16 cells were treated with the pCLPGp19 virus and/or drugs before subcutaneous injection in C57BL/6 mice, observation of tumor progression and histopathologic analyses. Results: Here we show that the functional activation of endogenous p53wt in B16 was particularly challenging, but accomplished when combined gene transfer and drug treatments were applied, resulting in increased transactivation by p53, marked cell cycle alteration and reduced viability in culture. In an animal model, B16 cells treated with both p19Arf and nutlin-3 yielded increased necrosis and decreased BrdU marking. In comparison, C6 cells were quite susceptible to either treatment, yet p53 was further activated by the combination of p19Arf and nutlin-3. Conclusions: To the best of our knowledge, this is the first study to apply both p19Arf and nutlin-3 for the stimulation of p53 activity. These results support the notion that a p53 responsive vector may prove to be an interesting gene transfer tool, especially when combined with p53- activating agents, for the treatment of tumors that retain wild-type p53.

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We investigate the effect of an interaction between dark energy and dark matter upon the dynamics of galaxy clusters. This effect is computed through the Layser-Irvine equation, which describes how an astrophysical system reaches virial equilibrium and was modified to include the dark interactions. Using observational data from almost 100 purportedly relaxed galaxy clusters we put constraints on the strength of the couplings in the dark sector. We compare our results with those from other observations and find that a positive (in the sense of energy flow from dark energy to dark matter) nonvanishing interaction is consistent with the data within several standard deviations.

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We propose a field theory model for dark energy and dark matter in interaction. Comparing the classical solutions of the field equations with the observations of the CMB shift parameter, baryonic acoustic oscillations, lookback time, and the Gold supernovae sample, we observe a possible interaction between dark sectors with energy decay from dark energy into dark matter. The observed interaction provides an alleviation to the coincidence problem.

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Cosmological analyses based on currently available observations are unable to rule out a sizeable coupling between dark energy and dark matter. However, the signature of the coupling is not easy to grasp, since the coupling is degenerate with other cosmological parameters, such as the dark energy equation of state and the dark matter abundance. We discuss possible ways to break such degeneracy. Based on the perturbation formalism, we carry out the global fitting by using the latest observational data and get a tight constraint on the interaction between dark sectors. We find that the appropriate interaction can alleviate the coincidence problem.