Trends in morbid obesity and in bariatric surgeries covered by the Brazilian public health system

Background Obesity is an increasingly serious public health problem on a global level. Morbid obesity, defined as a body mass index greater than 40 kg/m2, is associated with increased mortality and a high burden of obesity-related morbidities. Methods To study the prevalence of morbid obesity in Brazil, three national anthropometric surveys were reanalyzed. Data about bariatric surgeries were obtained from the Ministry of Health Hospital Information System, which is available online. Results A 255% rise in the prevalence of morbid obesity was observed, starting at 0.18% in 1975-1976 and growing to 0.33% in 1989 and 0.64% in 2002-2003. There was a higher rate in the South in the first two surveys, but the prevalence in the Southeast rose steadily, reaching 0.77% in 2002-2003 and overtaking the South. Since 1999, the Brazilian Unified Health System has covered surgical treatment for morbid obesity. From 2000 to 2006, there was a sixfold increase in the number of surgeries, which topped the 2,500 mark in 2006. The geographic distribution of these surgeries is heavily concentrated in the Southeast, the most developed region of Brazil, where there is also the highest prevalence of morbid obesity. This was followed by the Southern region. Conclusions The figures for the rise in morbid obesity in Brazil are startling, especially the increase among men. This is a situation that calls for further study, alongside measures to encourage the adoption of healthy lifestyles. Preventive measures aimed at slowing down or reversing the obesity epidemic are urgently required

AtPIN: Arabidopsis thaliana Protein Interaction Network

Background: Protein-protein interactions (PPIs) constitute one of the most crucial conditions to sustain life in living organisms. To study PPI in Arabidopsis thaliana we have developed AtPIN, a database and web interface for searching and building interaction networks based on publicly available protein-protein interaction datasets. Description: All interactions were divided into experimentally demonstrated or predicted. The PPIs in the AtPIN database present a cellular compartment classification (C(3)) which divides the PPI into 4 classes according to its interaction evidence and subcellular localization. It has been shown in the literature that a pair of genuine interacting proteins are generally expected to have a common cellular role and proteins that have common interaction partners have a high chance of sharing a common function. In AtPIN, due to its integrative profile, the reliability index for a reported PPI can be postulated in terms of the proportion of interaction partners that two proteins have in common. For this, we implement the Functional Similarity Weight (FSW) calculation for all first level interactions present in AtPIN database. In order to identify target proteins of cytosolic glutamyl-tRNA synthetase (Cyt-gluRS) (AT5G26710) we combined two approaches, AtPIN search and yeast two-hybrid screening. Interestingly, the proteins glutamine synthetase (AT5G35630), a disease resistance protein (AT3G50950) and a zinc finger protein (AT5G24930), which has been predicted as target proteins for Cyt-gluRS by AtPIN, were also detected in the experimental screening. Conclusions: AtPIN is a friendly and easy-to-use tool that aggregates information on Arabidopsis thaliana PPIs, ontology, and sub-cellular localization, and might be a useful and reliable strategy to map protein-protein interactions in Arabidopsis. AtPIN can be accessed at http://bioinfo.esalq.usp.br/atpin.

Novel Primate-Specific Genes, RMEL 1, 2 and 3, with Highly Restricted Expression in Melanoma, Assessed by New Data Mining Tool

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.

The structure and dynamics of Abell 1942

Aims. We present a dynamical analysis of the galaxy cluster Abell 1942 based on a set of 128 velocities obtained at the European Southern Observatory. Methods. Data on individual galaxies are presented and the accuracy of the determined velocities as some properties of the cluster are discussed. We have also made use of publicly available Chandra X-ray data. Results. We obtained an improved mean redshift value z = 0.22513 +/- 0.0008 and velocity dispersion sigma = 908(139)(+147) km s(-1). Our analysis indicates that inside a radius of similar to 1.5 h(70)(-1) Mpc (similar to 7 arcmin) the cluster is well relaxed, without any remarkable features and the X-ray emission traces the galaxy distribution fairly well. Two possible optical substructures are seen at similar to 5 arcmin from the centre in the northwest and the southwest directions, but are not confirmed by the velocity field. These clumps are, however, kinematically bound to the main structure of Abell 1942. X-ray spectroscopic analysis of Chandra data resulted in a temperature kT = 5.5+/-0.5 keV and metal abundance Z = 0.33 +/- 0.15 Z(circle dot). The velocity dispersion corresponding to this temperature using the T(X-sigma) scaling relation is in good agreement with the measured galaxy velocities. Our photometric redshift analysis suggests that the weak lensing signal observed to the south of the cluster and previously attributed to a ""dark clump"" is produced by background sources, possibly distributed as a filamentary structure.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

In silico analysis of candidate genes involved in light sensing and signal transduction pathways in soybean

Several aspects of photoperception and light signal transduction have been elucidated by studies with model plants. However, the information available for economically important crops, such as Fabaceae species, is scarce. In order to incorporate the existing genomic tools into a strategy to advance soybean research, we have investigated publicly available expressed sequence tag ( EST) sequence databases in order to identify Glycine max sequences related to genes involved in light-regulated developmental control in model plants. Approximately 38,000 sequences from open-access databases were investigated, and all bona fide and putative photoreceptor gene families were found in soybean sequence databases. We have identified G. max orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses, although some important Arabidopsis phytochrome-signaling components are absent. Moreover, soybean and Arabidopsis gene-family homologs appear to have undergone a distinct expansion process in some cases. We propose a working model of light perception, signal transduction and response-eliciting in G. max, based on the identified key components from Arabidopsis. These results demonstrate the power of comparative genomics between model systems and crop species to elucidate several aspects of plant physiology and metabolism.

Trends in Morbid Obesity and in Bariatric Surgeries Covered by the Brazilian Public Health System

Obesity is an increasingly serious public health problem on a global level. Morbid obesity, defined as a body mass index greater than 40 kg/m(2), is associated with increased mortality and a high burden of obesity-related morbidities. To study the prevalence of morbid obesity in Brazil, three national anthropometric surveys were reanalyzed. Data about bariatric surgeries were obtained from the Ministry of Health Hospital Information System, which is available online. A 255% rise in the prevalence of morbid obesity was observed, starting at 0.18% in 1975-1976 and growing to 0.33% in 1989 and 0.64% in 2002-2003. There was a higher rate in the South in the first two surveys, but the prevalence in the Southeast rose steadily, reaching 0.77% in 2002-2003 and overtaking the South. Since 1999, the Brazilian Unified Health System has covered surgical treatment for morbid obesity. From 2000 to 2006, there was a sixfold increase in the number of surgeries, which topped the 2,500 mark in 2006. The geographic distribution of these surgeries is heavily concentrated in the Southeast, the most developed region of Brazil, where there is also the highest prevalence of morbid obesity. This was followed by the Southern region. The figures for the rise in morbid obesity in Brazil are startling, especially the increase among men. This is a situation that calls for further study, alongside measures to encourage the adoption of healthy lifestyles. Preventive measures aimed at slowing down or reversing the obesity epidemic are urgently required.

Percolation in a network with long-range connections: Implications for cytoskeletal structure and function

Cell shape, signaling, and integrity depend on cytoskeletal organization. In this study we describe the cytoskeleton as a simple network of filamentary proteins (links) anchored by complex protein structures (nodes). The structure of this network is regulated by a distance-dependent probability of link formation as P = p/d(s), where p regulates the network density and s controls how fast the probability for link formation decays with node distance (d). It was previously shown that the regulation of the link lengths is crucial for the mechanical behavior of the cells. Here we examined the ability of the two-dimensional network to percolate (i.e. to have end-to-end connectivity), and found that the percolation threshold depends strongly on s. The system undergoes a transition around s = 2. The percolation threshold of networks with s < 2 decreases with increasing system size L, while the percolation threshold for networks with s > 2 converges to a finite value. We speculate that s < 2 may represent a condition in which cells can accommodate deformation while still preserving their mechanical integrity. Additionally, we measured the length distribution of F-actin filaments from publicly available images of a variety of cell types. In agreement with model predictions, cells originating from more deformable tissues show longer F-actin cytoskeletal filaments. (C) 2008 Elsevier B.V. All rights reserved.