357 research outputs found

    Agreement between left and right middle cerebral artery blood velocity responses to incremental and constant work-rate exercise in healthy males and females

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    This is the author accepted manuscript. The final version is available from IOP Publishing via the DOI in this recordObjective: To quantify the agreement between left and right middle cerebral artery blood velocity (MCAv) responses to incremental and constant work-rate exercise in adults. Approach: Seventeen healthy adults (23.8±2.4 years, 9 females) completed a ramp incremental test to exhaustion on a cycle ergometer, three 6-minute transitions at a moderate-intensity, and three at a heavy-intensity, all on separate days. Bilateral MCAv was measured throughout using transcranial Doppler ultrasonography, with left and right MCAv data analysed separately. Data were analysed at baseline, gas exchange threshold, respiratory compensation point and exhaustion during ramp incremental exercise. MCAv responses to constant work-rate exercise were analysed using a mono-exponential model, to determine time- and amplitude-based kinetic response parameters. Main Results: Left and right MCAv responses to incremental and constant work-rate exercise were significantly, strongly and positively correlated (r≥0.61, P<0.01). Coefficient of variation (left vs right) ranged from 7.3-20.7%, 6.4-26.2% and 5.9-22.5% for ramp, moderate and heavy 33 intensity exercise, respectively. The relative change in MCAv from baseline was higher in the right compared to left MCAv during ramp, moderate and heavy-intensity exercise (all P<0.05), but the effect sizes were small (d≤0.4). Small mean left-right differences were present during ramp incremental exercise at all time-points (<6 cm/s; <4%), and for all kinetic parameters during moderate and heavy-intensity exercise (<3 cm/s, <3%, <4 s). Significance: These findings demonstrate similarities between left and right MCAv responses to incremental and constant-work rate exercise in adults on a group-level, but also highlight individual variation in the agreement between left and right MCAv exercise responsesQUEX Institut

    Inspiratory flow-resistive breathing, respiratory muscle-induced systemic oxidative stress, and diaphragm fatigue in healthy humans

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    We questioned whether the respiratory muscles of humans contribute to systemic oxidative stress following inspiratory flow-resistive breathing, whether the amount of oxidative stress is influenced by the level of resistive load, and whether the amount of oxidative stress is related to the degree of diaphragm fatigue incurred. Eight young and healthy participants attended the laboratory for four visits on separate days. During the first visit, height, body mass, lung function, and maximal inspiratory mouth and transdiaphragmatic pressure (Pdimax) were assessed. During visits 2–4, participants undertook inspiratory flow-resistive breathing with either no resistance (control) or resistive loads equivalent to 50 and 70% of their Pdimax (Pdimax50% and Pdimax70%) for 30 min. Participants undertook one resistive load per visit, and the order in which they undertook the loads was randomized. Inspiratory muscle pressures were higher (P < 0.05) during the 5th and Final min of Pdimax50% and Pdimax70% compared with control. Plasma F2-isoprostanes increased (P < 0.05) following inspiratory flow-resistive breathing at Pdimax70%. There were no increases in plasma protein carbonyls or total antioxidant capacity. Furthermore, although we evidenced small reductions in transdiapragmaic twitch pressures (PdiTW) after inspiratory flow-resistive breathing at Pdimax50% and Pdimax70%, this was not related to the increase in plasma F2-isoprostanes. Our novel data suggest that it is only when sufficiently strenuous that inspiratory flow-resistive breathing in humans elicits systemic oxidative stress evidenced by elevated plasma F2-isoprostanes, and based on our data, this is not related to a reduction in PdiTW

    Effects of exercise intensity on gut microbiome composition and function in people with type 2 diabetes

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    This is the final version. Available from Taylor and Francis Group via the DOI in this record. Exercise is positively associated with higher microbial diversity, but there is limited information on exercise intensity's effect on gut microbiome composition and function in clinical populations. This study examines whether different intensities of exercise exert differential effects on gut microbiome composition and function in low active people with type 2 diabetes. This is a sub-study of the Exercise for Type 2 Diabetes Study, a single centre, prospective, randomised controlled trial. Participants (n = 12) completed 8-weeks of combined aerobic and resistance moderate intensity continuous training (C-MICT) or combined aerobic and resistance high-intensity interval training (C-HIIT). Faecal samples were collected before and after intervention to measure gut microbiome composition and metabolic pathways (metagenome shotgun sequencing) and short-chain fatty acids. Post-exercise α-diversity was different between groups as was the relative abundance of specific taxa was (p < .05). Post-exercise relative abundance of Bifidobacterium, A. municiphila, and butyrate-producers Lachnospira eligens, Enterococcus spp., and Clostridium Cluster IV were higher at lower exercise intensity. Other butyrate-producers (from Eryspelothrichales and Oscillospirales), and methane producer Methanobrevibacter smithii were higher at higher exercise intensity. Pyruvate metabolism (ko00620),COG “Cell wall membrane envelope biogenesis” and “Unknown function” pathways were significantly different between groups and higher in C-MICT post-exercise. Differential abundance analysis on KO showed higher expression of Two-component system in C-HIIT. Transcription factors and “unknown metabolism” related pathways decreased in both groups. There were no significant between group changes in faecal short chain fatty acids. Exercise intensity had a distinct effect on gut microbiome abundance and metabolic function, without impacting short-chain fatty acid output.Biotechnology & Biological Sciences Research Council (BBSRC)Biotechnology & Biological Sciences Research Council (BBSRC)Centre for Research in Exercise and Physical Activity (The University of Queensland

    Genes to predict VO2 max trainability: A systematic review

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    Cardiorespiratory fitness (VO2max) is an excellent predictor of chronic disease morbidity and mortality risk. Guidelines recommend individuals undertake exercise training to improve VO2max for chronic disease reduction. However, there are large inter-individual differences between exercise training responses. This systematic review is aimed at identifying genetic variants that are associated with VO2max trainability.Peer-reviewed research papers published up until October 2016 from four databases were examined. Articles were included if they examined genetic variants, incorporated a supervised aerobic exercise intervention; and measured VO2max/VO2peak pre and post-intervention.Thirty-five articles describing 15 cohorts met the criteria for inclusion. The majority of studies used a cross-sectional retrospective design. Thirty-two studies researched candidate genes, two used Genome-Wide Association Studies (GWAS), and one examined mRNA gene expression data, in addition to a GWAS. Across these studies, 97 genes to predict VO2max trainability were identified. Studies found phenotype to be dependent on several of these genotypes/variants, with higher responders to exercise training having more positive response alleles than lower responders (greater gene predictor score). Only 13 genetic variants were reproduced by more than two authors. Several other limitations were noted throughout these studies, including the robustness of significance for identified variants, small sample sizes, limited cohorts focused primarily on Caucasian populations, and minimal baseline data. These factors, along with differences in exercise training programs, diet and other environmental gene expression mediators, likely influence the ideal traits for VO2max trainability.Ninety-seven genes have been identified as possible predictors of VO2max trainability. To verify the strength of these findings and to identify if there are more genetic variants and/or mediators, further tightly-controlled studies that measure a range of biomarkers across ethnicities are required

    Sex modifies the relationship between age and neurovascular coupling in healthy adults

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    This is the final version. Available on open access from SAGE Publications via the DOI in this recordNeurovascular coupling (NVC) is the matching between local neuronal activity and regional cerebral blood flow (CBF), but little is known about the effects of age and sex on NVC. This study aimed to investigate the relationships and interaction between age and sex on NVC. Sixty-four healthy adults (18-85 years, N = 34 female) completed a visual stimulus evoked NVC assessment to a flashing checkerboard. NVC responses were measured in the posterior cerebral artery (PCAv) using transcranial Doppler ultrasound. A hierarchical multiple regression was used to determine the relationships between age, sex, and the age by sex interaction on NVC. There was a significant age by sex interaction for baseline (P = 0.001) and peak PCAv (P = 0.01), with a negative relationship with age in females (P < 0.005), and no relationship in males (P ≥ 0.17). NVC responses as a percent increase from baseline showed a significant age by sex interaction (P = 0.014), with a positive relationship with age in females (P = 0.04) and no relationship in males (P = 0.17), even after adjusting for baseline PCAv. These data highlight important sex differences, with an association between age and NVC only apparent in females but not males, and thus a need to account for sex dependent effects of ageing when investigating cerebrovascular regulation.QUEX Institut

    Effects of exercise intensity and nutrition advice on myocardial function in obese children and adolescents: a multicentre randomised controlled trial study protocol.

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    INTRODUCTION: The prevalence of paediatric obesity is increasing, and with it, lifestyle-related diseases in children and adolescents. High-intensity interval training (HIIT) has recently been explored as an alternate to traditional moderate-intensity continuous training (MICT) in adults with chronic disease and has been shown to induce a rapid reversal of subclinical disease markers in obese children and adolescents. The primary aim of this study is to compare the effects of HIIT with MICT on myocardial function in obese children and adolescents. METHODS AND ANALYSIS: Multicentre randomised controlled trial of 100 obese children and adolescents in the cities of Trondheim (Norway) and Brisbane (Australia). The trial will examine the efficacy of HIIT to improve cardiometabolic outcomes in obese children and adolescents. Participants will be randomised to (1) HIIT and nutrition advice, (2) MICT and nutrition advice or (3) nutrition advice. Participants will partake in supervised exercise training and/or nutrition sessions for 3 months. Measurements for study end points will occur at baseline, 3 months (postintervention) and 12 months (follow-up). The primary end point is myocardial function (peak systolic tissue velocity). Secondary end points include vascular function (flow-mediated dilation assessment), quantity of visceral and subcutaneous adipose tissue, myocardial structure and function, body composition, cardiorespiratory fitness, autonomic function, blood biochemistry, physical activity and nutrition. Lean, healthy children and adolescents will complete measurements for all study end points at one time point for comparative cross-sectional analyses. ETHICS AND DISSEMINATION: This randomised controlled trial will generate substantial information regarding the effects of exercise intensity on paediatric obesity, specifically the cardiometabolic health of this at-risk population. It is expected that communication of results will allow for the development of more effective evidence-based exercise prescription guidelines in this population while investigating the benefits of HIIT on subclinical markers of disease. TRIAL REGISTRATION NUMBER: NCT01991106

    Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery

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    <p>Abstract</p> <p>Background</p> <p>As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. However, its clinical use is not fully validated yet. An important factor to prevent this young technology to become a mainstream cancer diagnostic paradigm is that robustly identifying cancer molecular patterns from high-dimensional protein expression data is still a challenge in machine learning and oncology research. As a well-established dimension reduction technique, PCA is widely integrated in pattern recognition analysis to discover cancer molecular patterns. However, its global feature selection mechanism prevents it from capturing local features. This may lead to difficulty in achieving high-performance proteomic pattern discovery, because only features interpreting global data behavior are used to train a learning machine.</p> <p>Methods</p> <p>In this study, we develop a nonnegative principal component analysis algorithm and present a nonnegative principal component analysis based support vector machine algorithm with sparse coding to conduct a high-performance proteomic pattern classification. Moreover, we also propose a nonnegative principal component analysis based filter-wrapper biomarker capturing algorithm for mass spectral serum profiles.</p> <p>Results</p> <p>We demonstrate the superiority of the proposed algorithm by comparison with six peer algorithms on four benchmark datasets. Moreover, we illustrate that nonnegative principal component analysis can be effectively used to capture meaningful biomarkers.</p> <p>Conclusion</p> <p>Our analysis suggests that nonnegative principal component analysis effectively conduct local feature selection for mass spectral profiles and contribute to improving sensitivities and specificities in the following classification, and meaningful biomarker discovery.</p

    RPPAML/RIMS: A metadata format and an information management system for reverse phase protein arrays

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    <p>Abstract</p> <p>Background</p> <p>Reverse Phase Protein Arrays (RPPA) are convenient assay platforms to investigate the presence of biomarkers in tissue lysates. As with other high-throughput technologies, substantial amounts of analytical data are generated. Over 1000 samples may be printed on a single nitrocellulose slide. Up to 100 different proteins may be assessed using immunoperoxidase or immunoflorescence techniques in order to determine relative amounts of protein expression in the samples of interest.</p> <p>Results</p> <p>In this report an RPPA Information Management System (RIMS) is described and made available with open source software. In order to implement the proposed system, we propose a metadata format known as reverse phase protein array markup language (RPPAML). RPPAML would enable researchers to describe, document and disseminate RPPA data. The complexity of the data structure needed to describe the results and the graphic tools necessary to visualize them require a software deployment distributed between a client and a server application. This was achieved without sacrificing interoperability between individual deployments through the use of an open source semantic database, S3DB. This data service backbone is available to multiple client side applications that can also access other server side deployments. The RIMS platform was designed to interoperate with other data analysis and data visualization tools such as Cytoscape.</p> <p>Conclusion</p> <p>The proposed RPPAML data format hopes to standardize RPPA data. Standardization of data would result in diverse client applications being able to operate on the same set of data. Additionally, having data in a standard format would enable data dissemination and data analysis.</p

    Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome

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    Despite many attempts to establish pre-treatment prognostic markers to understand the clinical biology of esophageal adenocarcinoma (EAC), validated clinical biomarkers or parameters remain elusive. We generated and analyzed tumor transcriptome to develop a practical biomarker prognostic signature in EAC.Untreated esophageal endoscopic biopsy specimens were obtained from 64 patients undergoing surgery and chemoradiation. Using DNA microarray technology, genome-wide gene expression profiling was performed on 75 untreated cancer specimens from 64 EAC patients. By applying various statistical and informatical methods to gene expression data, we discovered distinct subgroups of EAC with differences in overall gene expression patterns and identified potential biomarkers significantly associated with prognosis. The candidate marker genes were further explored in formalin-fixed, paraffin-embedded tissues from an independent cohort (52 patients) using quantitative RT-PCR to measure gene expression. We identified two genes whose expression was associated with overall survival in 52 EAC patients and the combined 2-gene expression signature was independently associated with poor outcome (P<0.024) in the multivariate Cox hazard regression analysis.Our findings suggest that the molecular gene expression signatures are associated with prognosis of EAC patients and can be assessed prior to any therapy. This signature could provide important improvement for the management of EAC patients
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