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

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.

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.

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.

Genome Sequence of the Bacterioplanktonic, Mixotrophic Vibrio campbellii Strain PEL22A, Isolated in the Abrolhos Bank

Vibrio campbellii PEL22A was isolated from open ocean water in the Abrolhos Bank. The genome of PEL22A consists of 6,788,038 bp (the GC content is 45%). The number of coding sequences (CDS) is 6,359, as determined according to the Rapid Annotation using Subsystem Technology (RAST) server. The number of ribosomal genes is 80, of which 68 are tRNAs and 12 are rRNAs. V. campbellii PEL22A contains genes related to virulence and fitness, including a complete proteorhodopsin cluster, complete type II and III secretion systems, incomplete type I, IV, and VI secretion systems, a hemolysin, and CTX Phi.

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.

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.

Effects of enamel matrix derivative and transforming growth factor-β1 on human osteoblastic cells

Abstract Background Extracellular matrix proteins are key factors that influence the regenerative capacity of tissues. The objective of the present study was to evaluate the effects of enamel matrix derivative (EMD), TGF-β1, and the combination of both factors (EMD+TGF-β1) on human osteoblastic cell cultures. Methods Cells were obtained from alveolar bone of three adult patients using enzymatic digestion. Effects of EMD, TGF-β1, or a combination of both were analyzed on cell proliferation, bone sialoprotein (BSP), osteopontin (OPN) and alkaline phosphatase (ALP) immunodetection, total protein synthesis, ALP activity and bone-like nodule formation. Results All treatments significantly increased cell proliferation compared to the control group at 24 h and 4 days. At day 7, EMD group showed higher cell proliferation compared to TGF-β1, EMD + TGF-β1 and the control group. OPN was detected in the majority of the cells for all groups, whereas fluorescence intensities for ALP labeling were greater in the control than in treated groups; BSP was not detected in all groups. All treatments decreased ALP levels at 7 and 14 days and bone-like nodule formation at 21 days compared to the control group. Conclusions The exposure of human osteoblastic cells to EMD, TGF-β1 and the combination of factors in vitro supports the development of a less differentiated phenotype, with enhanced proliferative activity and total cell number, and reduced ALP activity levels and matrix mineralization.