Physical activity and clustered cardiovascular disease risk factors in young children: a cross-sectional study (the IDEFICS study)

<p>Background The relevance of physical activity (PA) for combating cardiovascular disease (CVD) risk in children has been highlighted, but to date there has been no large-scale study analyzing that association in children aged ≤9 years of age. This study sought to evaluate the associations between objectively-measured PA and clustered CVD risk factors in a large sample of European children, and to provide evidence for gender-specific recommendations of PA.</p> <p>Methods Cross-sectional data from a longitudinal study in 16,224 children aged 2 to 9 were collected. Of these, 3,120 (1,016 between 2 to 6 years, 2,104 between 6 to 9 years) had sufficient data for inclusion in the current analyses. Two different age-specific and gender-specific clustered CVD risk scores associated with PA were determined. First, a CVD risk factor (CRF) continuous score was computed using the following variables: systolic blood pressure (SBP), total triglycerides (TG), total cholesterol (TC)/high-density lipoprotein cholesterol (HDL-c) ratio, homeostasis model assessment of insulin resistance (HOMA-IR), and sum of two skinfolds (score CRFs). Secondly, another CVD risk score was obtained for older children containing the score CRFs + the cardiorespiratory fitness variable (termed score CRFs + fit). Data used in the current analysis were derived from the IDEFICS (‘Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS’) study.</p> <p>Results In boys <6 years, the odds ratios (OR) for CVD risk were elevated in the least active quintile of PA (OR: 2.58) compared with the most active quintile as well as the second quintile for vigorous PA (OR: 2.91). Compared with the most active quintile, older children in the first, second and third quintiles had OR for CVD risk score CRFs + fit ranging from OR 2.69 to 5.40 in boys, and from OR 2.85 to 7.05 in girls.</p> <p>Conclusions PA is important to protect against clustering of CVD risk factors in young children, being more consistent in those older than 6 years. Healthcare professionals should recommend around 60 and 85 min/day of moderate-to-vigorous PA, including 20 min/day of vigorous PA.</p&gt

Valley polarization in MoS2 monolayers by optical pumping

We report experimental evidences on selective occupation of the degenerate valleys in MoS2 monolayers by circularly polarized optical pumping. Over 30% valley polarization has been observed at K and K' valley via the polarization resolved luminescence spectra on pristine MoS2 monolayers. It demonstrates one viable way to generate and detect valley polarization towards the conceptual valleytronics applications with information carried by the valley index

Neurocranium versus Face: A Morphometric Approach with Classical Anthropometric Variables for Characterizing Patterns of Cranial Integration in Extant Hominoids and Extinct Hominins

The relative importance of the two main cranial complexes, the neurocranium and the splanchnocranium, has been examined in the five species of extant hominoids and in a huge sample of extinct hominins using six standard craniometric variables that measure the length, width and height of each cranial module. Factor analysis and two-block partial least squares were used for establishing the major patterns of developmental and evolutionary integration between both cranial modules. The results obtained show that all extant hominoids (including the anatomically modern humans) share a conserved pattern of developmental integration, a result that agrees with previous studies. The pattern of evolutionary integration between both cranial modules in australopiths runs in parallel to developmental integration. In contrast, the pattern of evolutionary and developmental integration of the species of the genus Homo is the opposite, which is probably the consequence of distinctive selective regimes for both hominin groups.JAPC, JMJA and PP received fundings from Ministerio de Ciencia e Innovación, Gobierno de España (http://www.idi.mineco.gob.es), project CGL2011-30334, and Consejería de Economía, Innovación, Ciencia y Empleo, Junta de Andalucía, España (http://www.juntadeandalucia.es/organismo​s/economiainnovacioncienciayempleo.html), project P11-HUM-7248 and Research Groups RNM-146 and HUM-607

A population study on the association between leisure time physical activity and self-rated health among diabetics in Taiwan

<p>Abstract</p> <p>Background</p> <p>There is strong evidence for the beneficial effects of physical activity in diabetes. There has been little research demonstrating a dose-response relationship between physical activity and self-rated health in diabetics. The aim of this study was to explore the dose-response association between leisure time physical activity and self-rated health among diabetics in Taiwan.</p> <p>Methods</p> <p>Data came from the 2001 Taiwan National Health Interview Survey (NHIS). Inclusion criteria were a physician confirmed diagnosis of diabetes mellitus and age 18 years and above (n = 797). Self-rated health was assessed by the question "In general, would you say that your health is excellent, very good, good, fair, or poor?" Individuals with a self perceived health status of good, very good, or excellent were considered to have positive health status.</p> <p>Results</p> <p>In the full model, the odds ratio (OR) for positive health was 2.51(95% CI = 1.53-4.13), 1.62(95% CI = 0.93-2.84), and 1.35(95% CI = 0.77-2.37), for those with a total weekly energy expenditure of ≥ 1000 kcal, between 500 and 999 kcal, and between 1 and 499 kcal, respectively, compared to inactive individuals. Those with duration over 10 years (OR = 0.53, 95%CI = 0.30-0.94), heart disease (OR = 0.50, 95%CI = 0.30-0.85), and dyslipidemia (OR = 0.65, 95% CI = 0.43-0.98) were less likely to have positive health than their counterparts. After stratified participants by duration, those with a duration of diabetes < 6 years, the adjusted OR for positive health was 1.95(95% CI = 1.02-3.72), 1.22(95% CI = 0.59-2.52), and 1.19(95% CI = 0.58-2.41) for those with a total weekly energy expenditure of ≥ 1000 kcal, between 500 and 999 kcal, and between 1 and 499 kcal, respectively, compared to inactive individuals. In participants with a duration of diabetes ≥ 6 years, total energy expenditure showed a gradient effect on self-perceived positive health. The adjusted OR for positive health was 3.45(95% CI = 1.53-7.79), 2.77(95% CI = 1.11-6.92), and 1.90(95% CI = 0.73-4.94) for those with a total weekly energy expenditure of ≥ 1000 kcal, between 500 and 999 kcal, and between 1 and 499 kcal, respectively, compared to inactive individuals.</p> <p>Conclusions</p> <p>Our results highlight that regular leisure activity with an energy expenditure ≧ 500 kcal per week is associated with better self-rated health for those with longstanding diabetes.</p

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Inference of Functional Relations in Predicted Protein Networks with a Machine Learning Approach

Background: Molecular biology is currently facing the challenging task of functionally characterizing the proteome. The large number of possible protein-protein interactions and complexes, the variety of environmental conditions and cellular states in which these interactions can be reorganized, and the multiple ways in which a protein can influence the function of others, requires the development of experimental and computational approaches to analyze and predict functional associations between proteins as part of their activity in the interactome. Methodology/Principal Findings: We have studied the possibility of constructing a classifier in order to combine the output of the several protein interaction prediction methods. The AODE (Averaged One-Dependence Estimators) machine learning algorithm is a suitable choice in this case and it provides better results than the individual prediction methods, and it has better performances than other tested alternative methods in this experimental set up. To illustrate the potential use of this new AODE-based Predictor of Protein InterActions (APPIA), when analyzing high-throughput experimental data, we show how it helps to filter the results of published High-Throughput proteomic studies, ranking in a significant way functionally related pairs. Availability: All the predictions of the individual methods and of the combined APPIA predictor, together with the used datasets of functional associations are available at http://ecid.bioinfo.cnio.es/. Conclusions: We propose a strategy that integrates the main current computational techniques used to predict functional associations into a unified classifier system, specifically focusing on the evaluation of poorly characterized protein pairs. We selected the AODE classifier as the appropriate tool to perform this task. AODE is particularly useful to extract valuable information from large unbalanced and heterogeneous data sets. The combination of the information provided by five prediction interaction prediction methods with some simple sequence features in APPIA is useful in establishing reliability values and helpful to prioritize functional interactions that can be further experimentally characterized.This work was funded by the BioSapiens (grant number LSHG-CT-2003-503265) and the Experimental Network for Functional Integration (ENFIN) Networks of Excellence (contract number LSHG-CT-2005-518254), by Consolider BSC (grant number CSD2007-00050) and by the project “Functions for gene sets” from the Spanish Ministry of Education and Science (BIO2007-66855). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

3D Morphology, Ultrastructure and Development of Ceratomyxa puntazzi Stages: First Insights into the Mechanisms of Motility and Budding in the Myxozoa

Free, amoeboid movement of organisms within media as well as substrate-dependent cellular crawling processes of cells and organisms require an actin cytoskeleton. This system is also involved in the cytokinetic processes of all eukaryotic cells. Myxozoan parasites are known for the disease they cause in economical important fishes. Usually, their pathology is related to rapid proliferation in the host. However, the sequences of their development are still poorly understood, especially with regard to pre-sporogonic proliferation mechanisms. The present work employs light microscopy (LM), electron microscopy (SEM, TEM) and confocal laser scanning microscopy (CLSM) in combination with specific stains (Nile Red, DAPI, Phalloidin), to study the three-dimensional morphology, motility, ultrastructure and cellular composition of Ceratomyxa puntazzi, a myxozoan inhabiting the bile of the sharpsnout seabream