The Borg Scale as an Important Tool of Self-Monitoring and Self-Regulation of Exercise Prescription in Heart Failure Patients During Hydrotherapy - A Randomized Blinded Controlled Trial

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)

TCF7L2 variant genotypes and type 2 diabetes risk in Brazil: significant association, but not a significant tool for risk stratification in the general population

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.

Half-Pringle Maneuver: A Useful Tool in Laparoscopic Liver Resection

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.

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.

A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR

Background: Considering the broad variation in the expression of housekeeping genes among tissues and experimental situations, studies using quantitative RT-PCR require strict definition of adequate endogenous controls. For glioblastoma, the most common type of tumor in the central nervous system, there was no previous report regarding this issue. Results: Here we show that amongst seven frequently used housekeeping genes TBP and HPRT1 are adequate references for glioblastoma gene expression analysis. Evaluation of the expression levels of 12 target genes utilizing different endogenous controls revealed that the normalization method applied might introduce errors in the estimation of relative quantities. Genes presenting expression levels which do not significantly differ between tumor and normal tissues can be considered either increased or decreased if unsuitable reference genes are applied. Most importantly, genes showing significant differences in expression levels between tumor and normal tissues can be missed. We also demonstrated that the Holliday Junction Recognizing Protein, a novel DNA repair protein over expressed in lung cancer, is extremely over-expressed in glioblastoma, with a median change of about 134 fold. Conclusion: Altogether, our data show the relevance of previous validation of candidate control genes for each experimental model and indicate TBP plus HPRT1 as suitable references for studies on glioblastoma gene expression.

SMALL MAMMAL PREY SELECTION BY TWO OWL SPECIES IN SOUTHEASTERN BRAZIL

A variety of factors influence prey selection by predators. Because Barn Owls (Tyto alba) and Burrowing Owls (Athene cunicularia) differ in size and foraging tactics, we expected differential predation on small mammal prey. We hypothesized that the Barn Owl, all active predator, would prey on smaller and younger individuals than the Burrowing Owl, a sit-and-wait predator. We used pellet analyses to evaluate selection of small mammals by the two owls in relation to prey), species, age, and size at the Ecological Station of Itirapina, state of Sao Paulo, in southeastern Brazil. Small mammals constituted most of the prey individuals and biomass in the diet of Barn Owls. Although Burrowing Owls consumed a wider range of taxa, small mammals represented one-third of all biomass consumed. With respect. to small mammals, Barn Owls foraged selectively relative to prey species, size, and age. Burrowing Owls foraged opportunistically relative to prey species, but selectively relative to prey size and age. Barn Owls selected smaller and younger (juvenile and subadult) individuals of the delicate vesper mouse (Calomys tener) and Burrowing Owls preyed more oil larger and older (subadult only) individuals. morphology and behavior of both prey and predators may explain this differential predation. Our data suggest that the active predator feeds oil smaller and younger prey, and the sit-and-wait predator took relatively larger and older prey.

Positive Selection Results in Frequent Reversible Amino Acid Replacements in the G Protein Gene of Human Respiratory Syncytial Virus

Human respiratory syncytial virus (HRSV) is the major cause of lower respiratory tract infections in children under 5 years of age and the elderly, causing annual disease outbreaks during the fall and winter. Multiple lineages of the HRSVA and HRSVB serotypes co-circulate within a single outbreak and display a strongly temporal pattern of genetic variation, with a replacement of dominant genotypes occurring during consecutive years. In the present study we utilized phylogenetic methods to detect and map sites subject to adaptive evolution in the G protein of HRSVA and HRSVB. A total of 29 and 23 amino acid sites were found to be putatively positively selected in HRSVA and HRSVB, respectively. Several of these sites defined genotypes and lineages within genotypes in both groups, and correlated well with epitopes previously described in group A. Remarkably, 18 of these positively selected tended to revert in time to a previous codon state, producing a ""flipflop'' phylogenetic pattern. Such frequent evolutionary reversals in HRSV are indicative of a combination of frequent positive selection, reflecting the changing immune status of the human population, and a limited repertoire of functionally viable amino acids at specific amino acid sites.

Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

Genetic variability and natural selection at the ligand domain of the Duffy binding protein in brazilian Plasmodium vivax populations

Background: Plasmodium vivax malaria is a major public health challenge in Latin America, Asia and Oceania, with 130-435 million clinical cases per year worldwide. Invasion of host blood cells by P. vivax mainly depends on a type I membrane protein called Duffy binding protein (PvDBP). The erythrocyte-binding motif of PvDBP is a 170 amino-acid stretch located in its cysteine-rich region II (PvDBP(II)), which is the most variable segment of the protein. Methods: To test whether diversifying natural selection has shaped the nucleotide diversity of PvDBP(II) in Brazilian populations, this region was sequenced in 122 isolates from six different geographic areas. A Bayesian method was applied to test for the action of natural selection under a population genetic model that incorporates recombination. The analysis was integrated with a structural model of PvDBP(II), and T-and B-cell epitopes were localized on the 3-D structure. Results: The results suggest that: (i) recombination plays an important role in determining the haplotype structure of PvDBP(II), and (ii) PvDBP(II) appears to contain neutrally evolving codons as well as codons evolving under natural selection. Diversifying selection preferentially acts on sites identified as epitopes, particularly on amino acid residues 417, 419, and 424, which show strong linkage disequilibrium. Conclusions: This study shows that some polymorphisms of PvDBP(II) are present near the erythrocyte-binding domain and might serve to elude antibodies that inhibit cell invasion. Therefore, these polymorphisms should be taken into account when designing vaccines aimed at eliciting antibodies to inhibit erythrocyte invasion.

Near-barrier quasielastic scattering as a sensitive tool to derive nuclear matter diffuseness

Quasielastic excitation functions for the (16,18)O + (60)Ni systems were measured at energies near and below the Coulomb barrier, at the backward angle theta(LAB) = 161 degrees. The corresponding quasielastic barrier distributions were derived. The data were compared with predictions from coupled channel calculations using a double-folding potential as a bare potential. For the (16)O-induced scattering, good agreement was obtained for the barrier distribution by using the projectile default nuclear matter diffuseness obtained from the Sao Paulo potential systematic, that is, 0.56 fm. However, for the (18)O-induced scattering, good agreement was obtained only when the projectile nuclear matter diffuseness was changed to 0.62 fm. Therefore, in this paper we show how near-barrier quasielastic scattering can be used as a sensitive tool to derive nuclear matter diffuseness.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

Simultaneous optimization by neuro-genetic approach for analysis of plant materials by laser induced breakdown spectroscopy

A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.

Anthropometric characteristics and motor skills in talent selection and development in indoor soccer

Kick performance, anthropometric characteristics, slalom, and linear running were assessed in 49 (24 elite, 25 nonelite) postpubertal indoor soccer players in order to (a) verify whether anthropometric characteristics and physical and technical capacities can distinguish players of different competitive levels, (b) compare the kicking kinematics of these groups, with and without a defined target, and (c) compare results on the assessments and coaches` subjective rankings of the players. Thigh circumference and specific technical capacities differentiated the players by level of play; cluster analysis correctly classified 77.5% of the players. The correlation between players` standardized measures and the coaches` rankings was 0.29. Anthropometric characteristics and physical capacities do not necessarily differentiate players at post-pubertal stages and should not be overvalued during early development. Considering the coaches` rankings, performance measures outside the specific game conditions may not be useful in identification of talented players.