Proximity to Sports Facilities and Sports Participation for Adolescents in Germany

Objectives - To assess the relationship between proximity to specific sports facilities and participation in the corresponding sports activities for adolescents in Germany. Methods - A sample of 1,768 adolescents aged 11–17 years old and living in 161 German communities was examined. Distances to the nearest sports facilities were calculated as an indicator of proximity to sports facilities using Geographic Information Systems (GIS). Participation in specific leisure-time sports activities in sports clubs was assessed using a self-report questionnaire and individual-level socio-demographic variables were derived from a parent questionnaire. Community-level socio-demographics as covariates were selected from the INKAR database, in particular from indicators and maps on land development. Logistic regression analyses were conducted to examine associations between proximity to the nearest sports facilities and participation in the corresponding sports activities. Results - The logisitic regression analyses showed that girls residing longer distances from the nearest gym were less likely to engage in indoor sports activities; a significant interaction between distances to gyms and level of urbanization was identified. Decomposition of the interaction term showed that for adolescent girls living in rural areas participation in indoor sports activities was positively associated with gym proximity. Proximity to tennis courts and indoor pools was not associated with participation in tennis or water sports, respectively. Conclusions - Improved proximity to gyms is likely to be more important for female adolescents living in rural areas

Elevated Proteasome Capacity Extends Replicative Lifespan in Saccharomyces cerevisiae

Aging is characterized by the accumulation of damaged cellular macromolecules caused by declining repair and elimination pathways. An integral component employed by cells to counter toxic protein aggregates is the conserved ubiquitin/proteasome system (UPS). Previous studies have described an age-dependent decline of proteasomal function and increased longevity correlates with sustained proteasome capacity in centenarians and in naked mole rats, a long-lived rodent. Proof for a direct impact of enhanced proteasome function on longevity, however, is still lacking. To determine the importance of proteasome function in yeast aging, we established a method to modulate UPS capacity by manipulating levels of the UPS–related transcription factor Rpn4. While cells lacking RPN4 exhibit a decreased non-adaptable proteasome pool, loss of UBR2, an ubiquitin ligase that regulates Rpn4 turnover, results in elevated Rpn4 levels, which upregulates UPS components. Increased UPS capacity significantly enhances replicative lifespan (RLS) and resistance to proteotoxic stress, while reduced UPS capacity has opposing consequences. Despite tight transcriptional co-regulation of the UPS and oxidative detoxification systems, the impact of proteasome capacity on lifespan is independent of the latter, since elimination of Yap1, a key regulator of the oxidative stress response, does not affect lifespan extension of cells with higher proteasome capacity. Moreover, since elevated proteasome capacity results in improved clearance of toxic huntingtin fragments in a yeast model for neurodegenerative diseases, we speculate that the observed lifespan extension originates from prolonged elimination of damaged proteins in old mother cells. Epistasis analyses indicate that proteasome-mediated modulation of lifespan is at least partially distinct from dietary restriction, Tor1, and Sir2. These findings demonstrate that UPS capacity determines yeast RLS by a mechanism that is distinct from known longevity pathways and raise the possibility that interventions to promote enhanced proteasome function will have beneficial effects on longevity and age-related disease in humans

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Candidate gene analysis of spontaneous preterm delivery: New insights from re-analysis of a case-control study using case-parent triads and control-mother dyads

<p>Abstract</p> <p>Background</p> <p>Spontaneous preterm delivery (PTD) has a multifactorial etiology with evidence of a genetic contribution to its pathogenesis. A number of candidate gene case-control studies have been performed on spontaneous PTD, but the results have been inconsistent, and do not fully assess the role of how two genotypes can impact outcome. To elucidate this latter point we re-analyzed data from a previously published case-control candidate gene study, using a case-parent triad design and a hybrid design combining case-parent triads and control-mother dyads. These methods offer a robust approach to genetic association studies for PTD compared to traditional case-control designs.</p> <p>Methods</p> <p>The study participants were obtained from the Norwegian Mother and Child Cohort Study (MoBa). A total of 196 case triads and 211 control dyads were selected for the analysis. A case-parent triad design as well as a hybrid design was used to analyze 1,326 SNPs from 159 candidate genes. We compared our results to those from a previous case-control study on the same samples. Haplotypes were analyzed using a sliding window of three SNPs and a pathway analysis was performed to gain biological insight into the pathophysiology of preterm delivery.</p> <p>Results</p> <p>The most consistent significant fetal gene across all analyses was COL5A2. The functionally similar COL5A1 was significant when combining fetal and maternal genotypes. PON1 was significant with analytical approaches for single locus association of fetal genes alone, but was possibly confounded by maternal effects. Focal adhesion (hsa04510), Cell Communication (hsa01430) and ECM receptor interaction (hsa04512) were the most constant significant pathways.</p> <p>Conclusion</p> <p>This study suggests a fetal association of COL5A2 and a combined fetal-maternal association of COL5A1 with spontaneous PTD. In addition, the pathway analysis implied interactions of genes affecting cell communication and extracellular matrix.</p

Evaluation of cell-free DNA approaches for multi-cancer early detection

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test

Oxidative Stress and Vascular Function: Implications for Pharmacologic Treatments

Production of considerable amounts of reactive oxygen species (ROS) eventually leads to oxidative stress. A key role of oxidative stress is evident in the pathologic mechanisms of endothelial dysfunction and associated cardiovascular diseases. Vascular enzymes such as NADPH oxidases, xanthine oxidase, and uncoupled endothelial nitric oxide synthase are involved in the production of ROS. The question remains whether pharmacologic approaches can effectively combat the excessive ROS production in the vasculature. Interestingly, existing registered cardiovascular drugs can directly or indirectly act as antioxidants, thereby preventing the damaging effects of ROS. Moreover, new compounds targeting NADPH oxidases have been developed. Finally, food-derived compounds appear to be effective inhibitors of oxidative stress and preserve vascular function

Unsupervised assessment of microarray data quality using a Gaussian mixture model

<p>Abstract</p> <p>Background</p> <p>Quality assessment of microarray data is an important and often challenging aspect of gene expression analysis. This task frequently involves the examination of a variety of summary statistics and diagnostic plots. The interpretation of these diagnostics is often subjective, and generally requires careful expert scrutiny.</p> <p>Results</p> <p>We show how an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and the naïve Bayes model can be used to automate microarray quality assessment. The method is flexible and can be easily adapted to accommodate alternate quality statistics and platforms. We evaluate our approach using Affymetrix 3' gene expression and exon arrays and compare the performance of this method to a similar supervised approach.</p> <p>Conclusion</p> <p>This research illustrates the efficacy of an unsupervised classification approach for the purpose of automated microarray data quality assessment. Since our approach requires only unannotated training data, it is easy to customize and to keep up-to-date as technology evolves. In contrast to other "black box" classification systems, this method also allows for intuitive explanations.</p

Hyperdimensional Analysis of Amino Acid Pair Distributions in Proteins

Our manuscript presents a novel approach to protein structure analyses. We have organized an 8-dimensional data cube with protein 3D-structural information from 8706 high-resolution non-redundant protein-chains with the aim of identifying packing rules at the amino acid pair level. The cube contains information about amino acid type, solvent accessibility, spatial and sequence distance, secondary structure and sequence length. We are able to pose structural queries to the data cube using program ProPack. The response is a 1, 2 or 3D graph. Whereas the response is of a statistical nature, the user can obtain an instant list of all PDB-structures where such pair is found. The user may select a particular structure, which is displayed highlighting the pair in question. The user may pose millions of different queries and for each one he will receive the answer in a few seconds. In order to demonstrate the capabilities of the data cube as well as the programs, we have selected well known structural features, disulphide bridges and salt bridges, where we illustrate how the queries are posed, and how answers are given. Motifs involving cysteines such as disulphide bridges, zinc-fingers and iron-sulfur clusters are clearly identified and differentiated. ProPack also reveals that whereas pairs of Lys residues virtually never appear in close spatial proximity, pairs of Arg are abundant and appear at close spatial distance, contrasting the belief that electrostatic repulsion would prevent this juxtaposition and that Arg-Lys is perceived as a conservative mutation. The presented programs can find and visualize novel packing preferences in proteins structures allowing the user to unravel correlations between pairs of amino acids. The new tools allow the user to view statistical information and visualize instantly the structures that underpin the statistical information, which is far from trivial with most other SW tools for protein structure analysis