Síntese estendida: uma investigação histórico-filosófica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Uma pesquisa didático-epistemológica na formação inicial em ciências biológicas: como a evolução forjou a grande quantidade de criaturas que habitam o nosso planeta?

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Influence of time evolution in the modulus of elasticity of concrete reinforced by carbon fibers

The modulus of elasticity is an important property for the behavior analysis of concrete structures. This research evaluated the strain difference between concrete specimens with and without the application of laminate carbon fiber composites as well as the variation time, in months, of the axial strength compression and modulus of elasticity. Through the experimental results, it is concluded that increases in compressive strength and modulus of elasticity are more significant in the specimens without reinforcement.

The Impact of Software Evolution on Code Coverage Information

Many tools and techniques for addressing software maintenance problems rely on code coverage information. Often, this coverage information is gathered for a specific version of a software system, and then used to perform analyses on subsequent versions of that system without being recalculated. As a software system evolves, however, modifications to the software alter the software’s behavior on particular inputs, and code coverage information gathered on earlier versions of a program may not accurately reflect the coverage that would be obtained on later versions. This discrepancy may affect the success of analyses dependent on code coverage information. Despite the importance of coverage information in various analyses, in our search of the literature we find no studies specifically examining the impact of software evolution on code coverage information. Therefore, we conducted empirical studies to examine this impact. The results of our studies suggest that even relatively small modifications can greatly affect code coverage information, and that the degree of impact of change on coverage may be difficult to predict.

Influence of landscape evolution on the distribution of floristic patterns in northern Amazonia revealed by delta 13C data

The Amazonian lowlands include large patches of open vegetation which contrast sharply with the rainforest, and the origin of these patches has been debated. This study focuses on a large area of open vegetation in northern Brazil, where d13C and, in some instances, C/N analyses of the organic matter preserved in late Quaternary sediments were used to achieve floristic reconstructions over time. The main goal was to determine when the modern open vegetation started to develop in this area. The variability in d13C data derived from nine cores ranges from -32.2 to -19.6 parts per thousand, but with nearly 60% of data above -26.5 parts per thousand. The most enriched values were detected only in ecotone and open vegetated areas. The development of open vegetation communities was asynchronous, varying between estimated ages of 6400 and 3000 cal a BP. This suggests that the origin of the studied patches of open vegetation might be linked to sedimentary dynamics of a late Quaternary megafan system. As sedimentation ended, this vegetation type became established over the megafan surface. In addition, the data presented here show that the presence of C4 plants must be used carefully as a proxy to interpret dry paleoclimatic episodes in Amazonian areas. Copyright (c) 2012 John Wiley & Sons, Ltd.

A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data

In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a user-defined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity

Assessing the gain of biological data integration in gene networks inference

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.

Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Non-linear magnetohydrodynamic simulations of density evolution in Tore Supra sawtoothing plasmas

The plasma density evolution in sawtooth regime on the Tore Supra tokamak is analyzed. The density is measured using fast-sweeping X-mode reflectometry which allows tomographic reconstructions. There is evidence that density is governed by the perpendicular electric flows, while temperature evolution is dominated by parallel diffusion. Postcursor oscillations sometimes lead to the formation of a density plateau, which is explained in terms of convection cells associated with the kink mode. A crescent-shaped density structure located inside q = 1 is often visible just after the crash and indicates that some part of the density withstands the crash. 3D full MHD nonlinear simulations with the code XTOR-2F recover this structure and show that it arises from the perpendicular flows emerging from the reconnection layer. The proportion of density reinjected inside the q = 1 surface is determined, and the implications in terms of helium ash transport are discussed. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4766893]

THE CONVERSION OF THE ATLANTIC FOREST IN ANTHROPOGENIC LANDSCAPES: LESSONS FOR THE CONSERVATION OF BIOLOGICAL DIVERSITY OF TROPICAL FORESTS

The Brazilian Atlantic forest has been an excellent laboratory for investigations regarding tropical forest ecology and the fragility of tropical ecosystems in face of human disturbances. In this article, we present a synthesis about the spatial distribution of Atlantic forest biodiversity and forest response to human disturbances, as well as the ongoing conservation efforts based on a review of several investigations in this biota. In general, studies have documented an uneven distribution of biodiversity throughout the Atlantic forest region, revealing alarming rates of habitat loss at low altitudes, while protected areas concentrate at higher altitudes. It has been suggested that the remaining forest habitat is moving towards an early-successional systems across human-modified landscapes. Such regressive forest succession increases the threats for several animals and plant groups. Based on these findings, we propose seven guidelines in order to enhance the provision of ecosystem services and the conservation value of human-modified landscapes, reducing the species extinction risk in the Atlantic forest and in other irreplaceable tropical biotas.

Size distributions and temporal variations of biological aerosol particles in the Amazon rainforest characterized by microscopy and real-time UV-APS fluorescence techniques during AMAZE-08

As a part of the AMAZE-08 campaign during the wet season in the rainforest of central Amazonia, an ultraviolet aerodynamic particle sizer (UV-APS) was operated for continuous measurements of fluorescent biological aerosol particles (FBAP). In the coarse particle size range (> 1 mu m) the campaign median and quartiles of FBAP number and mass concentration were 7.3x10(4) m(-3) (4.0-13.2x10(4) m(-3)) and 0.72 mu g m(-3) (0.42-1.19 mu g m(-3)), respectively, accounting for 24% (11-41%) of total particle number and 47% (25-65%) of total particle mass. During the five-week campaign in February-March 2008 the concentration of coarse-mode Saharan dust particles was highly variable. In contrast, FBAP concentrations remained fairly constant over the course of weeks and had a consistent daily pattern, peaking several hours before sunrise, suggesting observed FBAP was dominated by nocturnal spore emission. This conclusion was supported by the consistent FBAP number size distribution peaking at 2.3 mu m, also attributed to fungal spores and mixed biological particles by scanning electron microscopy (SEM), light microscopy and biochemical staining. A second primary biological aerosol particle (PBAP) mode between 0.5 and 1.0 mu m was also observed by SEM, but exhibited little fluorescence and no true fungal staining. This mode may have consisted of single bacterial cells, brochosomes, various fragments of biological material, and small Chromalveolata (Chromista) spores. Particles liquid-coated with mixed organic-inorganic material constituted a large fraction of observations, and these coatings contained salts likely from primary biological origin. We provide key support for the suggestion that real-time laser-induce fluorescence (LIF) techniques using 355 nm excitation provide size-resolved concentrations of FBAP as a lower limit for the atmospheric abundance of biological particles in a pristine environment. We also show some limitations of using the instrument for ambient monitoring of weakly fluorescent particles < 2 mu m. Our measurements confirm that primary biological particles, fungal spores in particular, are an important fraction of supermicron aerosol in the Amazon and that may contribute significantly to hydrological cycling, especially when coated by mixed inorganic material.

Thoughts on the diversity of convergent evolution of bioluminescence on earth

The widespread independent evolution of analogous bioluminescent systems is one of the most impressive and diverse examples of convergent evolution on earth. There are roughly 30 extant bioluminescent systems that have evolved independently on Earth, with each system likely having unique enzymes responsible for catalysing the bioluminescent reaction. Bioluminescence is a chemical reaction involving a luciferin molecule and a luciferase or photoprotein that results in the emission of light. Some independent systems utilize the same luciferin, such as the use of tetrapyrrolic compounds by krill and dinoflagellates, and the wide use of coelenterazine by marine organisms, while the enzymes involved are unique. One common thread among all the different bioluminescent systems is the requirement of molecular oxygen. Bioluminescence is found in most forms of life, especially marine organisms. Bioluminescence in known to benefit the organism by: attraction, repulsion, communication, camouflage, and illumination. The marine ecosystem is significantly affected by bioluminescence, the only light found in the pelagic zone and below is from bioluminescent organisms. Transgenic bioluminescent organisms have revolutionized molecular research, medicine and the biotechnology industry. The use of bioluminescence in studying molecular pathways and disease allows for non-invasive and real-time analysis. Bioluminescence-based assays have been developed for several analytes by coupling luminescence to many enzyme-catalysed reactions. Received 17 February 2012, accepted 27 March 2012, first published online 2 May 2012

World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for Biological Treatment of Schizophrenia, Part 1: Update 2012 on the acute treatment of schizophrenia and the management of treatment resistance

These updated guidelines are based on a first edition of the World Federation of Societies of Biological Psychiatry Guidelines for Biological Treatment of Schizophrenia published in 2005. For this 2012 revision, all available publications pertaining to the biological treatment of schizophrenia were reviewed systematically to allow for an evidence-based update. These guidelines provide evidence-based practice recommendations that are clinically and scientifically meaningful and these guidelines are intended to be used by all physicians diagnosing and treating people suffering from schizophrenia. Based on the first version of these guidelines, a systematic review of the MEDLINE/PUBMED database and the Cochrane Library, in addition to data extraction from national treatment guidelines, has been performed for this update. The identified literature was evaluated with respect to the strength of evidence for its efficacy and then categorised into six levels of evidence (A-F; Bandelow et al. 2008b, World J Biol Psychiatry 9: 242). This first part of the updated guidelines covers the general descriptions of antipsychotics and their side effects, the biological treatment of acute schizophrenia and the management of treatment-resistant schizophrenia.