title: Six weeks of a polarized training-intensity distribution leads to greater physiological and performance adaptations than a threshold model in trained cyclists.
abstract: This study was undertaken to investigate physiological adaptation with two endurance-training periods differing in intensity distribution. In a randomized crossover fashion, separated by 4 wk of detraining, 12 male cyclists completed two 6-wk training periods: 1) a polarized model [6.4 (±1.4 SD) h/wk; 80%, 0%, and 20% of training time in low-, moderate-, and high-intensity zones, respectively]; and 2) a threshold model [7.5 (±2.0 SD) h/wk; 57%, 43%, and 0% training-intensity distribution]. Before and after each training period, following 2 days of diet and exercise control, fasted skeletal muscle biopsies were obtained for mitochondrial enzyme activity and monocarboxylate transporter (MCT) 1 and 4 expression, and morning first-void urine samples were collected for NMR spectroscopy-based metabolomics analysis. Endurance performance (40-km time trial), incremental exercise, peak power output (PPO), and high-intensity exercise capacity (95% maximal work rate to exhaustion) were also assessed. Endurance performance, PPOs, lactate threshold (LT), MCT4, and high-intensity exercise capacity all increased over both training periods. Improvements were greater following polarized rather than threshold for PPO [mean (±SE) change of 8 (±2)% vs. 3 (±1)%, P < 0.05], LT [9 (±3)% vs. 2 (±4)%, P < 0.05], and high-intensity exercise capacity [85 (±14)% vs. 37 (±14)%, P < 0.05]. No changes in mitochondrial enzyme activities or MCT1 were observed following training. A significant multilevel, partial least squares-discriminant analysis model was obtained for the threshold model but not the polarized model in the metabolomics analysis. A polarized training distribution results in greater systemic adaptation over 6 wk in already well-trained cyclists. Markers of muscle metabolic adaptation are largely unchanged, but metabolomics markers suggest different cellular metabolic stress that requires further investigation.
authors.affiliation: Health and Exercise Sciences Research Group, School of Sport, University of Stirling, Stirling, Scotland, UK.
authors.forename: Craig M
authors.initials: CM
authors.lastname: Neal
authors.forename: Angus M
authors.initials: AM
authors.lastname: Hunter
authors.forename: Lorraine
authors.initials: L
authors.lastname: Brennan
authors.forename: Aifric
authors.initials: A
authors.lastname: O'Sullivan
authors.forename: D Lee
authors.initials: DL
authors.lastname: Hamilton
authors.forename: Giuseppe
authors.initials: G
authors.lastname: De Vito
authors.forename: Stuart D R
authors.initials: SD
authors.lastname: Galloway
mesh_terms: D000222:Adaptation, Physiological; D000328:Adult; D001642:Bicycling; D015415:Biomarkers / Q000652:urine; D001706:Biopsy; D018592:Cross-Over Studies; D016002:Discriminant Analysis; D015444:Exercise; D005080:Exercise Test; D006801:Humans; D016018:Least-Squares Analysis; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D055432:Metabolomics / Q000379:methods; D008931:Mitochondria, Muscle / Q000378:metabolism; D027501:Monocarboxylic Acid Transporters / Q000378:metabolism; D009119:Muscle Contraction; D018763:Muscle Fatigue; D009124:Muscle Proteins / Q000378:metabolism; D053580:Muscle Strength; D018482:Muscle, Skeletal / Q000378:metabolism / Q000502:physiology*; D010807:Physical Endurance; D012606:Scotland; D027981:Symporters / Q000378:metabolism; D013997:Time Factors; D016482:Urinalysis; D000099233:Monocarboxylate Transport Protein 1
chemical_list: D015415:Biomarkers; D027501:Monocarboxylic Acid Transporters; D009124:Muscle Proteins; D027981:Symporters; D000099233:Monocarboxylate Transport Protein 1; C406962:SLC16A4 protein, human