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.

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.

A TR beta-selective agonist confers resistance to diet-induced obesity

Thyroid hormone receptor beta (TR beta also listed as THRB oil the MGI Database)-selective agonists activate brown adipose tissue (BAT) thermogenesis, while only minimally affecting cardiac activity or lean body mass. Here, we tested the hypothesis that daily administration of the TR beta agonist GC-24 prevents the metabolic alterations associated with a hypercaloric diet. Rats were placed on a high-fat diet and after a month exhibited increased body weight (BW) and adiposity, fasting hyperglycemia and glucose intolerance, increased plasma levels of triglycerides, cholesterol, nonesterified Fatty acids and interleukin-6. While GC-24 administration to these animals did not affect food ingestion or modified the progression of BW gain, it did increase energy, g the increase in adiposity Without expenditure, eliminating causing cardiac hypertrophy Fasting hyperglycemia remained unchanged, but treatment with GC-24 improved glucose I tolerance by increasing insulin Sensitivity and also normalized plasma triglyceride levels. plasma cholesterol levels were only Partially normalized and liver cholesterol content remained high in the GC-24-treated animals. Gene expression in liver, skeletal muscle, and white adipose tissue was only minimally affected by treatment with GC-24, with the main target being BAT In conclusion, during high-fat feeding treatment with the TR beta-selective agonist, GC-24 only partially improves metabolic control probably as a result Of accelerating the resting metabolic rate. Journal of Endocrinology (2009) 203, 291-299

Exercise training associated with diet improves heart rate recovery and cardiac autonomic nervous system activity in obese children

The purpose of this study was to test the hypotheses that in obese children: 1) hypocaloric diet (D) improves both heart rate recovery at 1 min (Delta HRR1) cfter an exercise test, and cardiac autonomic nervous system activity (CANSA) in obese children; 2) Diet and exercise training (DET) combined leads to greater improvement in both Delta HRR1 after an exercise test and in CANSA, than D alone. Moreover, we examined the relationships among Delta HRR1, CANSA, cardiorespiratory fitness and anthropometric variables (AV) in obese children submitted to D and to DET. 33 obese children (10 +/- 0.2 years; body mass index (BMI) >95(th) percentile) were divided into 2 groups: D (n = 15; BMI = 31 +/- 1 kg/m(2)) and DET (n = 18; 29 +/- 1 kg/m(2)). All children performed a maximal cardiopulmonary exercise test on a treadmill. The Delta HRR1 was defined as the difference between heart rate at peak and at 1-min post-exercise. CANSA was assessed using power spectral analysis of heart rate variability at rest. The sympathovagal balance (low frequency and high frequency ratio, LF/HF) was measured. After interventions, all obese children showed reduced body weight (P < 0.05). The D group did not improve in terms of peak VO(2), Delta HRR1 or LF/HF ratio (P > 0.05). In contrast, the DET group showed increased peak VO(2) (P = 0.01) and improved Delta HRR1 (Delta HRR1 = 37.3 +/- 2.6; P = 0.01) and LF/HF ratio (P = 0.001). The DET group demonstrated significant relationships among Delta HRR1, peak VO(2) and CANSA (P < 0.05). In conclusion, DET, in contrast to D, promoted improved Delta HRR1 and CANSA in obese children, suggesting a positive influence of increased levels of cardiorespiratory fitness by exercise training on cardiac autonomic activity.

Influence of high- and low-carbohydrate diet following glycogen-depleting exercise on heart rate variability and plasma catecholamines

The purpose of this study was to investigate the effects of a short-term low-or high-carbohydrate (CHO) diet consumed after exercise on sympathetic nervous system activity. Twelve healthy males underwent a progressive incremental test; a control measurement of plasma catecholamines and heart rate variability (HRV); an exercise protocol to reduce endogenous CHO stores; a low-or high-CHO diet (counterbalanced order) consumed for 2 days, beginning immediately after the exercise protocol; and a second resting plasma catecholamine and HRV measurement. The exercise and diet protocols and the second round of measurements were performed again after a 1-week washout period. The mean (+/- SD) values of the standard deviation of R-R intervals were similar between conditions (control, 899.0 +/- 146.1 ms; low-CHO diet, 876.8 +/- 115.8 ms; and high-CHO diet, 878.7 +/- 127.7 ms). The absolute high-and low-frequency (HF and LF, respectively) densities of the HRV power spectrum were also not different between conditions. However, normalized HF and LF (i.e., relative to the total power spectrum) were lower and higher, respectively, in the low-CHO diet than in the control diet (mean +/- SD, 17 +/- 9 normalized units (NU) and 83 +/- 9 NU vs. 27 +/- 11 NU and 73 +/- 17 NU, respectively; p < 0.05). The LF/HF ratio was higher with the low-CHO diet than with the control diet (mean +/- SD, 7.2 +/- 6.2 and 4.2 +/- 3.2, respectively; p < 0.05). The mean values of plasma catecholamines were not different between diets. These results suggest that the autonomic control of the heart rate was modified after a short-term low-CHO diet, but plasma catecholamine levels were not altered.

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.

A low carbohydrate diet affects autonomic modulation during heavy but not moderate exercise

The aim of this study was to examine the effects of low carbohydrate (CHO) availability on heart rate variability (HRV) responses during moderate and severe exercise intensities until exhaustion. Six healthy males (age, 26.5 +/- 6.7 years; body mass, 78.4 +/- 7.7 kg; body fat %, 11.3 +/- 4.5%; (V) over dotO(2max), 39.5 +/- 6.6 mL kg(-1) min(-1)) volunteered for this study. All tests were performed in the morning, after 8-12 h overnight fasting, at a moderate intensity corresponding to 50% of the difference between the first (LT(1)) and second (LT(2)) lactate breakpoints and at a severe intensity corresponding to 25% of the difference between the maximal power output and LT(2). Forty-eight hours before each experimental session, the subjects performed a 90-min cycling exercise followed by 5-min rest periods and subsequent 1-min cycling bouts at 125% (V) over dotO(2max) (with 1-min rest periods) until exhaustion, in order to deplete muscle glycogen. A diet providing 10% (CHO(low)) or 65% (CHO(control)) of energy as carbohydrates was consumed for the following 2 days until the experimental test. The Poicare plots (standard deviations 1 and 2: SD1 and SD2, respectively) and spectral autoregressive model (low frequency LF, and high frequency HF) were applied to obtain HRV parameters. The CHO availability had no effect on the HRV parameters or ventilation during moderate-intensity exercise. However, the SD1 and SD2 parameters were significantly higher in CHO(low) than in CHO(control), as taken at exhaustion during the severe-intensity exercise (P < 0.05). The HF and LF frequencies (ms(2)) were also significantly higher in CHO(low) than in CHO(control) (P < 0.05). In addition, ventilation measured at the 5 and 10-min was higher in CHO(low) (62.5 +/- 4.4 and 74.8 +/- 6.5 L min(-1), respectively, P < 0.05) than in CHO(control) (70.0 +/- 3.6 and 79.6 +/- 5.1 L min(-1), respectively; P < 0.05) during the severe-intensity exercise. These results suggest that the CHO availability alters the HRV parameters during severe-, but not moderate-, intensity exercise, and this was associated with an increase in ventilation volume.

Low carbohydrate diet affects the oxygen uptake on-kinetics and rating of perceived exertion in high intensity exercise

The aim of this study was to determine if the carbohydrate (CHO) availability alters the rate of increase in the rating of perceived exertion (RPE) during high intensity exercise and whether this would be associated with physiological changes. Six males performed high intensity exercise after 48 h of controlled, high CHO (80%) and low CHO (10%) diets. Time to exhaustion was lower in the low compared to high CHO diet. The rate of increase in RPE was greater and the VO(2) slow component was lower in the low CHO diet than in the control. There was no significant condition effect for cortisol, insulin, pH, plasma glucose, potassium, or lactate concentrations. Multiple linear regression indicated that the total amplitude of VO(2) and perceived muscle strain accounted for the greatest variance in the rate of increase in RPE. These results suggest that cardiorespiratory variables and muscle strain are important afferent signals from the periphery for the RPE calculations.

Raspberry (Rubus idaeus L.) wine: Yeast selection, sensory evaluation and instrumental analysis of volatile and other compounds

To evaluate the potential for fermentation of raspberry pulp, sixteen yeast strains (S. cerevisiae and S. bayanus) were studied. Volatile compounds were determined by GC-MS, GC-FID, and GC-PFPD. Ethanol. glycerol and organic acids were determined by HPLC. HPLC-DAD was used to analyse phenolic acids. Sensory analysis was performed by trained panellists. After a screening step, CAT-1, UFLA FW 15 and S. bayanus CBS 1505 were previously selected based on their fermentative characteristics and profile of the metabolites identified. The beverage produced with CAT-1 showed the highest volatile fatty acid concentration (1542.6 mu g/L), whereas the beverage produced with UFLA FIN 15 showed the highest concentration of acetates (2211.1 mu g/L) and total volatile compounds (5835 mu g/L). For volatile sulphur compounds. 566.5 mu g/L were found in the beverage produced with S. bayanus CBS 1505. The lowest concentration of volatile sulphur compounds (151.9 mu g/L) was found for the beverage produced with UFLA FW 15. In the sensory analysis, the beverage produced with UFLA FW 15 was characterised by the descriptors raspberry, cherry, sweet, strawberry, floral and violet. In conclusion, strain UFLA FW 15 was the yeast that produced a raspberry wine with a good chemical and sensory quality. (C) 2010 Elsevier Ltd. All rights reserved.

Selection of new glass-forming compositions in Al-La system using a combination of topological instability and thermodynamic criteria

A combination of an extension of the topological instability ""lambda criterion"" and a thermodynamic criterion were applied to the Al-La system, indicating the best range of compositions for glass formation. Alloy compositions in this range were prepared by melt-spinning and casting in an arc-melting furnace with a wedge-section copper mold. The GFA of these samples was evaluated by X-ray diffraction, differential scanning calorimetry and scanning electron microscopy. The results indicated that the gamma* parameter of compositions with high GFA is higher, corresponding to a range in which the lambda parameter is greater than 0.1, which are compositions far from Al solid solution. A new alloy was identified with the best GFA reported so far for this system, showing a maximum thickness of 286 mu m in a wedge-section copper mold. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

Risk-based decision making method for maintenance policy selection of thermal power plant equipment

This study presents a decision-making method for maintenance policy selection of power plants equipment. The method is based on risk analysis concepts. The method first step consists in identifying critical equipment both for power plant operational performance and availability based on risk concepts. The second step involves the proposal of a potential maintenance policy that could be applied to critical equipment in order to increase its availability. The costs associated with each potential maintenance policy must be estimated, including the maintenance costs and the cost of failure that measures the critical equipment failure consequences for the power plant operation. Once the failure probabilities and the costs of failures are estimated, a decision-making procedure is applied to select the best maintenance policy. The decision criterion is to minimize the equipment cost of failure, considering the costs and likelihood of occurrence of failure scenarios. The method is applied to the analysis of a lubrication oil system used in gas turbines journal bearings. The turbine has more than 150 MW nominal output, installed in an open cycle thermoelectric power plant. A design modification with the installation of a redundant oil pump is proposed for lubricating oil system availability improvement. (C) 2009 Elsevier Ltd. All rights reserved.

Miniaturized structures for removal or selection of particles from liquid flow

The aim of this work was the development of miniaturized structures useful for retention and/or selection of particles and viscous substances from a liquid flow. The proposed low costs structures are similar to macroscopic wastewater treatment systems, named baffles, and allow disassemble. They were simulated using FEMLAB 3.2b package and manufactured in acrylic with conventional tools. Tests for retention or selection of particles in water or air and viscous fluids in water were carried out. Either in air or water particles with 50 mu m diameter will be retained but not with 13 mu m diameter. In aqueous flow, it is also possible the retention of viscous samples, such as silicone 350 cSt. The simulated results showed good agreement with experimental measurements. These miniaturized structures can be useful in sample pretreatment for chemical analysis and microorganism manipulation. (C) 2007 Elsevier B.V. All rights reserved.