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.

This study highlights important sex and training status differences in the senescent and naïve T-lymphocyte redistribution in response to exercise that warrants further investigation.

In the present study, we analysed the training-intensity distribution and physiological adaptations over a 6-month period preceding an Ironman triathlon race. Ten athletes (mean ± s: age 43 ± 3 years, mass 78.3 ± 10.3 kg, stature 1.79 ± 0.05 m) participated in the study. The study consisted of three training periods (A, B, C), each of approximately 2 months' duration, and four testing weeks. Testing consisted of incremental tests to exhaustion for swimming, cycling and running, and assessments for anthropometry plus cardiovascular and pulmonary measures. The lactate threshold and the lactate turnpoint were used to demarcate three discipline-specific, exercise-intensity zones. The mean percentage of time spent in zones 1, 2, and 3 was 69 ± 9%, 25 ± 8%, and 6 ± 2% for periods A-C combined. Only modest physiological adaptation occurred throughout the 6-month period, with small to moderate effect sizes at best. Relationships between the training volume/training load and the training-intensity distribution with the changes in key measures of adaptation were weak and probably reflect differences in initial training status. Our results suggest that the effects of intensity distribution are small over short-term training periods and future experimental research is needed to clarify the potential impact of intensity distribution on physiological adaptation.

Athletes appear to be at a greater risk of illness while undertaking arduous training regimens in preparation for endurance events. As infection susceptibility has been linked with increased proportions of differentiated and senescent T cells in the periphery, changes in the proportions of these cell types due to long-term high-volume exercise training could have important implications for athlete infection risk. This study examined the effects of 6-month training preparation for an Ironman triathlon on the proportions of naïve, memory and senescent T cells in resting blood. Ten club-level triathletes (9 males; 1 female: 43 ± 3 years) were sampled at 27 (December), 21 (January), 15 (March), 9 (May) and 3 (June) weeks before an Ironman Triathlon. An additional sample was collected 2-week post-competition (August). Four-colour flow cytometry was used for the phenotypic analysis of CD4+ and CD8+ blood T cells. Proportions of differentiated (KLRG1+/CD57-) CD8+ T cells and "transitional" (CD45RA+/CD45RO+) CD4+ and CD8+ T cells increased with training, as the values in June were elevated 37, 142 and 116%, respectively, from those observed in December. Proportions of senescent (KLRG1+/CD57+) CD4+ or CD8+ T cells did not change during the training phase. Two weeks post-race, proportions of differentiated CD8+ T cells had returned to baseline values, while the proportions of senescent CD4+ T cells increased 192% alongside a 31% reduction in naïve (CD45RA+/CD45RO-) cells. In conclusion, increases in differentiated and "transitional" T cells due to arduous exercise training could compromise host protection to novel pathogens and increase athlete infection risk, although whether or not the composition of naïve and differentiated T cells in blood can serve as prognostic biomarkers in athletes remains to be established.

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