Introduction The aim of this study was to determine whether muscle oxidative capacity is influenced by alterations in training volume in middle-distance runners. Methods Twenty-four highly trained middle-distance runners (n = 16 males; V˙O2peak = 73.3(4.3) mL·kg−1·min−1; n = 8 females, V˙O2peak = 63.2(3.4) mL·kg−1·min−1) completed 3 wk of normal training (NormTr), 3 wk of high-volume training (HVTr; a 10%, 20%, and 30% increase in training volume during each successive week from NormTr), and a 1-wk taper (TapTr; 55% exponential reduction in training volume from HVTr week 3). Before and immediately after each training period, the rate of recovery of muscle oxygen consumption (mV˙O2) of the gastrocnemius medialis was measured using near-infrared spectroscopy, with the rate constant indicating muscle oxidative capacity. Time to exhaustion (TTE) and V˙O2peak were determined during a maximal incremental treadmill test. Results Twelve subjects were classified as being functionally overreached (FOR) after HVTr (decreased running TTE and high perceived fatigue), whereas the other 12 subjects were classified as acutely fatigued (AF; no decrease in running TTE). The AF group demonstrated a significant increase in muscle oxidative capacity after HVTr (rate constant: 15.1% ± 9.7% min−1; P = 0.009), with no further improvement after TapTr, whereas there was no change in muscle oxidative capacity for FOR at any time point (P > 0.05). Compared with the FOR group, the AF group had substantially larger improvements in TTE from pre-HVTr to post-TapTr (FOR, 8.8% ± 3.7%; AF, 3.2% ± 3.0%; P = 0.04). Conclusion The present study was able to demonstrate that muscle oxidative capacity was increased in response to a period of HVTr, but only in runners who did not develop FOR. Furthermore, runners who did not develop FOR had substantially larger performance improvements after a taper period.

Background Sleep loss may influence subsequent physical performance. Quantifying the impact of sleep loss on physical performance is critical for individuals involved in athletic pursuits. Design Systematic review and meta-analysis. Search and Inclusion Studies were identified via the Web of Science, Scopus, and PsycINFO online databases. Investigations measuring exercise performance under ‘control’ (i.e., normal sleep, > 6 h in any 24 h period) and ‘intervention’ (i.e., sleep loss, ≤ 6 h sleep in any 24 h period) conditions were included. Performance tasks were classified into different exercise categories (anaerobic power, speed/power endurance, high-intensity interval exercise (HIIE), strength, endurance, strength-endurance, and skill). Multi-level random-effects meta-analyses and meta-regression analyses were conducted, including subgroup analyses to explore the influence of sleep-loss protocol (e.g., deprivation, restriction, early [delayed sleep onset] and late restriction [earlier than normal waking]), time of day the exercise task was performed (AM vs. PM) and body limb strength (upper vs. lower body). Results Overall, 227 outcome measures (anaerobic power: n = 58; speed/power endurance: n = 32; HIIE: n = 27; strength: n = 66; endurance: n = 22; strength-endurance: n = 9; skill: n = 13) derived from 69 publications were included. Results indicated a negative impact of sleep loss on the percentage change (%Δ) in exercise performance (n = 959 [89%] male; mean %Δ =  − 7.56%, 95% CI − 11.9 to − 3.13, p = 0.001, I2 = 98.1%). Effects were significant for all exercise categories. Subgroup analyses indicated that the pattern of sleep loss (i.e., deprivation, early and late restriction) preceding exercise is an important factor, with consistent negative effects only observed with deprivation and late-restriction protocols. A significant positive relationship was observed between time awake prior to the exercise task and %Δ in performance for both deprivation and late-restriction protocols (~ 0.4% decrease for every hour awake prior to exercise). The negative effects of sleep loss on different exercise tasks performed in the PM were consistent, while tasks performed in the AM were largely unaffected. Conclusions Sleep loss appears to have a negative impact on exercise performance. If sleep loss is anticipated and unavoidable, individuals should avoid situations that lead to experiencing deprivation or late restriction, and prioritise morning exercise in an effort to maintain performance.

The aim of this study was to determine the influence of training volume alterations on diversity and composition of the gut microbiome in a free-living cohort of middle-distance runners. Fourteen highly-trained middle-distance runners (n=8 men; 𝑉 ̇O2peak = 70.1 ± 4.3 ml•kg•min -1 ; n=6 women, 𝑉 ̇O2peak: 59.0 ± 3.2 ml•kg•min -1 ) completed three weeks of normal training (NormTr), three weeks of high-volume training (HVolTr; a 10, 20 and 30% increase in training volume during each successive week from NormTr), and a one-week taper (TaperTr; 55% exponential reduction in training volume from HVolTr week three). Faecal samples were collected before and immediately after each training phase to quantify alphadiversity and composition of the gut microbiome. A three-day diet record was collected during each training phase and a maximal incremental running test was completed after each training phase. Results showed no significant changes in nutritional intake, alpha-diversity, or global microbial composition following HVolTr or TaperTr compared to NormTr (p's>0.05).Following HVolTr, there was a significant decrease in Pasterellaceae (p=0.03), Lachnoclostridium (p=0.02), Haemophilus (p=0.03), S. parasagunis (p=0.02), and H. parainfluenzae (p=0.03), while R. callidus (p=0.03) significantly increased. These changes did not return to NormTr levels following TaperTr. This study shows that the alpha-diversity and global composition of the gut microbiome were unaffected by changes in training volume. However, an increase in training volume led to several changes at the lower taxonomy levels that did not return to pre-HVolTr levels following a taper period.

The aim of this study was to identify markers of training stress and characteristics of middle-distance runners related to the incidence of overreaching following overload training. Twenty-four highly-trained runners (n=16 male; VO2peak=73.3(4.3) mL·kg·min-1; n=8 female, VO2peak=63.2(3.4) mL·kg·min-1) completed 3 weeks of normal training (NormTr), 3 weeks of high-volume training (HVTr; a 10, 20 and 30% increase in training volume each successive week from NormTr), and a 1-week taper (TapTr; 55% exponential reduction in training volume from HVTr week 3). Before, and immediately after each training period, an incremental treadmill-running test was performed, while resting metabolic rate (RMR), subjective fatigue responses and various resting blood biomarkers were assessed. Muscle fiber typology of the gastrocnemius was estimated by quantification of muscle carnosine using proton magnetic resonance spectroscopy and expressed as a z-score relative to a non-athlete control group. Twelve runners were classified as functionally overreached (FOR) following HVTr (decreased running TTE), whereas the other twelve were classified as acutely fatigued (AF; no decrease in running TTE). The FOR group did not demonstrate systematic alterations in RMR, resting blood biomarkers or submaximal exercise responses compared to the AF group. Gastrocnemius carnosine z-score was significantly higher in FOR (-0.44 ± 0.57) compared to AF (-1.25 ± 0.49, p = 0.004, d = 1.53) and was also associated with changes in running TTE from pre- to post-HVTr (r=-0.55, p=0.005) and pre-HVTr to post-TapTr (r=-0.64, p=0.008). Muscle fiber typology is related to the incidence of overreaching and performance super-compensation following increased training volume and a taper.

Background Rapid restoration of muscle glycogen stores is imperative for athletes undertaking consecutive strenuous exercise sessions with limited recovery time (e.g. ≤ 8 h). Strategies to optimise muscle glycogen re-synthesis in this situation are essential. This two-part systematic review and meta-analysis investigated the effect of consuming carbohydrate (CHO) with and without protein (PRO) on the rate of muscle glycogen re-synthesis during short-term post-exercise recovery (≤ 8 h). Methods Studies were identified via the online databases Web of Science and Scopus. Investigations that measured muscle glycogen via needle biopsy during recovery (with the first measurement taken ≤ 30 min post-exercise and at least one additional measure taken ≤ 8 h post-exercise) following a standardised exercise bout (any type) under the following control vs. intervention conditions were included in the meta-analysis: part 1, water (or non-nutrient beverage) vs. CHO, and part 2, CHO vs. CHO+PRO. Publications were examined for methodological quality using the Rosendal scale. Random-effects meta-analyses and meta-regression analyses were conducted to evaluate intervention efficacy. Results Overall, 29 trials (n = 246 participants) derived from 21 publications were included in this review. The quality assessment yielded a Rosendal score of 61 ± 8% (mean ± standard deviation). Part 1: 10 trials (n = 86) were reviewed. Ingesting CHO during recovery (1.02 ± 0.4 g·kg body mass (BM)−1 h−1) improved the rate of muscle glycogen re-synthesis compared with water; change in muscle glycogen (MGΔ) re-synthesis rate = 23.5 mmol·kg dm−1 h−1, 95% CI 19.0–27.9, p < 0.001; I2 = 66.8%. A significant positive correlation (R2 = 0.44, p = 0.027) was observed between interval of CHO administration (≤ hourly vs. > hourly) and the mean difference in rate of re-synthesis between treatments. Part 2: 19 trials (n = 160) were reviewed. Ingesting CHO+PRO (CHO: 0.86 ± 0.2 g·kg BM−1 h−1; PRO: 0.27 ± 0.1 g·kg BM−1 h−1) did not improve the rate of muscle glycogen re-synthesis compared to CHO alone (0.95 ± 0.3 g·kg BM−1 h−1); MGΔ re-synthesis rate = 0.4 mmol·kg  dm−1 h−1, 95% CI −2.7 to 3.4, p = 0.805; I2 = 56.4%. Conclusions Athletes with limited time for recovery between consecutive exercise sessions should prioritise regular intake of CHO, while co-ingesting PRO with CHO appears unlikely to enhance (or impede) the rate of muscle glycogen re-synthesis. Trial Registration Registered at the International Prospective Register of Systematic Reviews (PROSPERO) (identification code CRD42020156841).

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