Velocity, oxygen uptake and metabolic cost of pull, kick and whole body swimming

Purpose: The contributions of the limbs to velocity and metabolic parameters in front-crawl swimming at different intensities have not been identified considering both stroke and kick rate. Consequently, velocity, oxygen uptake (VO2), and metabolic cost of swimming with the whole body (swim), the upper limbs only (pull), and lower limbs only (kick) were compared with stroke and kick rate controlled. Methods: Twenty elite swimmers completed six 200-m trials: 2 swim, 2 pull, and 2 kick. Swim trials were guided by underwater lights at paces equivalent to 65% +/- 3% and 78% +/- 3% of participants' 200-m-freestyle personal-best pace; paces were described as low and moderate, respectively. In the pull and kick trials, swimmers aimed to match the stroke and kick rates, respectively, recorded during the swim trials. (V)over dot O-2 was measured continuously, with velocity and metabolic cost calculated for each 200-m effort. Results: The velocity contribution of the upper limbs (mean +/- SD; low 63.9% +/- 6.2%, moderate 59.6% +/- 4.2%) was greater than that of the lower limbs to a large extent at both intensities (low ES = 4.40, moderate ES = 4.60). The (V) over dot O-2 used by the upper limbs differed between the intensities (low 55.5% +/- 6.9%, moderate 51.4% +/- 4.0%; ES = 0.74). The lower limbs were responsible for a greater percentage of the metabolic cost than the upper limbs at both intensities (low 56.1% +/- 9.5%, ES = 1.30; moderate 55.1% +/- 6.6%, ES = 1.55). Conclusions: Implementation of this testing protocol before and after a pull-or kick-training block will enable sport scientists to determine how the velocity contributions and/or metabolic cost of the upper-and lower-limb actions have responded to the training program

Translating the oxidative stress hypothesis into the clinic: NOX versus NOS

Cardiovascular diseases remain the leading cause of death in industrialised nations. Since the pathomechanisms of most cardiovascular diseases are not understood, the majority of therapeutic approaches are symptom-orientated. Knowing the molecular mechanism of disease would enable more targeted therapies. One postulated underlying mechanism of cardiovascular diseases is oxidative stress, i.e. the increased occurrence of reactive oxygen species such as superoxide. Oxidative stress leads to a dysfunction of vascular endothelium-dependent protective mechanisms. There is growing evidence that this scenario also involves impaired nitric oxide (NO)-cyclic GMP signalling. Out of a number of enzyme families that can produce reactive oxygen species, NADPH oxidases stand out, as they are the only enzymes whose sole purpose is to produce reactive oxygen species. This review focuses on the clinically validated targets of oxidative stress, NO synthase (NOS) and the NO receptor, soluble guanylate cyclase as well as the source of ROS, e.g. NADPH oxidases. We place recent knowledge in the function and regulation of these enzyme families into clinical perspective. For a comprehensive overview of the biology and pharmacology of oxidative stress and possible other sources and targets, we refer to other literature overviews

Dynamic Gene Expression in the Human Cerebral Cortex Distinguishes Children from Adults

In comparison with other primate species, humans have an extended juvenile period during which the brain is more plastic. In the current study we sought to examine gene expression in the cerebral cortex during development in the context of this adaptive plasticity. We introduce an approach designed to discriminate genes with variable as opposed to uniform patterns of gene expression and found that greater inter-individual variance is observed among children than among adults. For the 337 transcripts that show this pattern, we found a significant overrepresentation of genes annotated to the immune system process (pFDR≅0). Moreover, genes known to be important in neuronal function, such as brain-derived neurotrophic factor (BDNF), are included among the genes more variably expressed in childhood. We propose that the developmental period of heightened childhood neuronal plasticity is characterized by more dynamic patterns of gene expression in the cerebral cortex compared to adulthood when the brain is less plastic. That an overabundance of these genes are annotated to the immune system suggests that the functions of these genes can be thought of not only in the context of antigen processing and presentation, but also in the context of nervous system development

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Velocity, aerobic power and metabolic cost of whole body and arms only front crawl swimming at various stroke rates

Stroke rate (SR) has not been considered in previous research examining the relative roles of the limbs in front-crawl performance. This study compared velocity, aerobic power () and metabolic cost (C) between whole body (WB) and arms only (AO) front-crawl swimming across various intensities while controlling SR

The non-linear relationship between sum of 7 skinfolds and fat and lean mass in elite swimmers

Body composition can substantially impact elite swimming performance. In practice, changes in fat and lean mass of elite swimmers are estimated using body mass, sum of seven skinfolds (∑7) and lean mass index (LMI). However, LMI may be insufficiently accurate to detect small changes in body composition which could meaningfully impact swimming performance. This study developed equations which estimate dual-energy x-ray absorptiometry (DXA)-derived lean and fat mass using body mass and ∑7 data. Elite Australian swimmers (n\ua0=\ua044; 18 male, 26 female) completed a DXA scan and standardised body mass and ∑7 measurements. Equations to estimate DXA-derived lean and fat mass based on body mass, ∑7 and sex were developed. The relationships between ∑7, body mass and DXA-derived lean and fat mass were non-linear. Fat mass (Adjusted R\ua0=\ua00.91; standard error\ua0=\ua01.0 kg) and lean mass (Adjusted R\ua0=\ua00.99; standard error\ua0=\ua01.0 kg) equations were considered sufficiently accurate. Lean mass estimates outperformed the LMI in identifying the correct direction of change in lean mass (82% correct; LMI 71%). Using the accurate estimations produced by these equations will enhance the prescription and evaluation of programmes to optimise the body composition and subsequent performance in swimmers

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers