Effect of time of day on performance, hormonal and metabolic response during a 1000-M cycling time trial

The effect of air pollution on diurnal variation of performance in anaerobic tests, cardiovascular and hematological parameters, and blood gases on soccer players following the Yo-Yo Intermittent Recovery Test Level-1

This study aimed to investigate the effect of air pollution on diurnal variation of performance in anaerobic tests, cardiovascular and hematological parameters, and blood gases on soccer players following the Yo-Yo Intermittent Recovery Test Level-1 (YYIRT1). In a randomized order, 11 healthy soccer players (mean age: 21.8 [range: 20-24] years; height: 178.00 [range: 1.64-1.83] cm; body mass index [BMI]: 23.57 [range: 20.45-28.03] kg.m^-2) performed a YYIRT1 at two different times of day (TOD) (08:00 h and 18:00 h) in two areas (i.e. polluted (PA) and non-polluted (NPA)) with a recovery period of ≥ 72 h in between, to determine the maximal oxygen uptake (VO2max). In each test session: resting oral temperature is measured, anaerobic performances (pre- and post-YYIRT1) were performed, cardiovascular parameters and blood samples were collected at: rest, 3 min and 60 min after the YYIRT1, to assess blood gases and hematological parameters. Our results showed that, agility performance, VO2max, red blood cells (RBC), hemoglobin (Hb), pH, and bicarbonate levels (HCO3^-) decrease significantly (p < 0.001) following the YYIRT1 in PA compared to NPA. Likewise, the heart rate (HR), systolic blood pressure (SBP), platelets (PLT), white blood cells (WBC), neutrophiles (NEUT), lymphocytes (LYM), and partial pressure of CO2 levels (P_vCO2) were significantly higher (p < 0.001) in PA. This effect was slightly accentuated at 18:00 h for some parameters (i.e. Agility, HCO3^-, HR, P_vCO2, RBC, SBP). However, performances of sprint and Sargent jump test (SJT), oral temperature, rate of perceived exertion scales (RPE), partial pressure of O2 (P_vO2), diastolic blood pressure (DBP), and monocytes (MON) were not affected by pollution (p > 0.05). In conclusion, pollution seems to be critical for health stability and performance in response to YYIRT1 especially in the evening and the winter season. Therefore, coaches and athletes should draw attention to the potential importance of land use planning in their training sessions and competitions in the morning in polluted area to minimize the risk of pollution exposure.

Effects of time-of-day on oxidative stress, cardiovascular parameters, biochemical markers, and hormonal response following level-1 Yo-Yo intermittent recovery test

The aim of this study was to investigate the effect of time-of-day on oxidative stress, cardiovascular parameters, muscle damage parameters, and hormonal responses following the level-1 Yo-Yo intermittent recovery test (YYIRT). A total of 11 healthy subjects performed an intermittent test (YYIRT) at two times-of-day (i.e., 07:00 h and 17:00 h), with a recovery period of ≥36 h in-between, in a randomized order. Blood samples were taken at the rest (baseline) and immediately (post-YYIRT) after the YYIRT for measuring oxidative stress, biochemical markers, and hormonal response. Data were statistically analyzed using one-way and two-way repeated measures ANOVA and Bonferroni test at p < 0.05. Observed power (α = 0.05) and partial eta-squared were used. Our results showed that oxygen uptake (VO2max), maximal aerobic speed, and the total distance covered tended to be higher in the evening (17:00 h). There was also a main effect of time-of-day for cortisol and testosterone concentration, which were higher after the YYIRT in the morning (p < 0.05). The heart rate peak and the rating of perceived exertion scales were lower in the morning (p < 0.05). However, the plasma glucose (p < 0.01), malondialdehyde, creatine kinase (p < 0.01), lactate dehydrogenase (p < 0.05), high-density lipoprotein (p < 0.01), total cholesterol (p < 0.01), and triglycerides (p < 0.05) were higher after the YYIRT in the evening. Low-density lipoprotein, systolic blood pressure, diastolic blood pressure, and lactate levels (p > 0.05) were similar for the morning and evening test. In conclusion, our findings suggest that aerobic performance presents diurnal variation with great result observed in the evening accompanied by an improvement of hormonal, metabolic, and oxidative responses. These data may help to guide athletes and coaches and contribute to public health recommendations on exercise and muscle damage particularly in the competitive periods.

Effect of Creatine Loading on Oxygen Uptake during a 1-km Cycling Time Trial

PURPOSE

For the first time, we investigated the effects of altering cellular metabolic capacitance, via a 5-d creatine (Cr) loading protocol (20 g·d⁻¹), on oxygen uptake (VO2), accumulated oxygen deficit, muscle recruitment, and performance during a 1-km cycling time trial.

METHODS

In a double-blind, randomized, placebo-controlled design, 19 amateur cyclists were allocated to a Cr (n = 10, VO2peak = 56.0 ± 7.8 mL·kg⁻¹·min⁻¹) or placebo (n = 9, VO2peak = 56.0 ± 8.4 mL·kg⁻¹·min⁻¹) group, and performed a 1-km cycling time trial before and after the supplementation period.

RESULTS

Body mass was significantly increased in the Cr group (P < 0.05), but not in the placebo group. Participants adopted an "all-out" pacing strategy in both groups. However, Cr loading reduced VO2 immediately after the beginning (12th to 23th seconds), and this was accompanied by a reduced aerobic and increased anaerobic contribution. The VO2 mean response time was slower (pre: 17.2 ± 5.6 s vs post: 19.9 ± 4.6 s), the total O2 uptake was reduced (pre: 4.64 ± 0.59 L vs post: 4.47 ± 0.53 L), and the oxygen deficit was increased (pre: 0.82 ± 0.27 L vs post: 0.98 ± 0.25 L) after Cr loading. No differences were observed in the placebo group for these variables. Plasma lactate and integrated electromyography were not altered in either group, nor was the time to complete the trial (Cr group: pre: 89.1 ± 6.7 s vs post 89.1 ± 6.2 s and placebo group: pre 85.9 ± 4.9 s vs post 87.0 ± 5.4 s).

CONCLUSION

Cr loading slows the V˙O2 response and increases the anaerobic contribution during a 1-km cycling time trial.

Expectancy of ergogenicity from sodium bicarbonate ingestion increases high-intensity cycling capacity

This study examined whether expectancy of ergogenicity of a commonly used nutritional supplement (sodium bicarbonate; NaHCO3) influenced subsequent high-intensity cycling capacity. Eight recreationally active males (age, 21 ± 1 years; body mass, 75 ± 8 kg; height, 178 ± 4 cm; WPEAK = 205 ± 22 W) performed a graded incremental test to assess peak power output (WPEAK), one familiarisation trial and two experimental trials. Experimental trials consisted of cycling at 100% WPEAK to volitional exhaustion (TLIM) 60 min after ingesting either a placebo (PLA: 0.1 g·kg−1 sodium chloride (NaCl), 4 mL·kg−1 tap water, and 1 mL·kg−1 squash) or a sham placebo (SHAM: 0.1 g·kg−1 NaCl, 4 mL·kg−1 carbonated water, and 1 mL·kg−1 squash). SHAM aimed to replicate the previously reported symptoms of gut fullness (GF) and abdominal discomfort (AD) associated with NaHCO3 ingestion. Treatments were administered double blind and accompanied by written scripts designed to remain neutral (PLA) or induce expectancy of ergogenicity (SHAM). After SHAM mean TLIM increased by 9.5% compared to PLA (461 ± 148 s versus 421 ± 150 s; P = 0.048, d = 0.3). Ratings of GF and AD were mild but ∼1 unit higher post-ingestion for SHAM. After 3 min TLIM overall ratings of perceived exertion were 1.4 ± 1.3 units lower for SHAM compared to PLA (P = 0.020, d = 0.6). There were no differences between treatments for blood lactate, blood glucose, or heart rate. In summary, ergogenicity after NaHCO3 ingestion may be influenced by expectancy, which mediates perception of effort during subsequent exercise. The observed ergogenicity with SHAM did not affect our measures of cardiorespiratory physiology or metabolic flux.

The behavior of an opponent alters pacing decisions in 4-km cycling time trials

INTRODUCTION

The present study aimed to explore how athletes respond to different behaviors of their opponents.

METHODS

Twelve moderately to highly physically active participants with at least two years of cycling experience completed four 4-km time trials on a Velotron cycle ergometer. After a familiarization time trial (FAM), participants performed three experimental time trials in randomized order with no opponent (NO), a virtual opponent who started slower and finished faster compared to FAM (OP-SLOWFAST), or a virtual opponent who started faster and finished slower compared to FAM (OP-FASTSLOW). Repeated-measures ANOVAs (P<0.05) were used to examine differences in pacing and performance related to power output, velocity and RPE.

RESULTS

OP-SLOWFAST and OP-FASTSLOW were completed faster compared to NO (385.5±27.5, 385.0±28.6, and 390.6±29.3s, respectively). An interaction effect for condition×distance (F=3.944, P<0.001) indicated differences in pacing profiles between conditions. Post-hoc analysis revealed that a less aggressive starting strategy was adopted in NO compared to OP-FASTSLOW and OP-SLOWFAST during the initial 1000m. Finally, a faster starting opponent evokes higher power outputs by the participants in the initial 750m compared to a slower starting opponent.

CONCLUSION

The present study is the first to show that the behavior of an opponent affects pacing-related decisions in laboratory-controlled conditions. Our findings support the recently proposed interdependence of perception and action, and emphasize the interaction with the environment as an important determinant for an athlete's pacing decisions, especially during the initial stages of a race.

GEDAE-LaB: A Free Software to Calculate the Energy System Contributions during Exercise

Purpose

The aim of the current study is to describe the functionality of free software developed for energy system contributions and energy expenditure calculation during exercise, namely GEDAE-LaB.

Methods

Eleven participants performed the following tests: 1) a maximal cycling incremental test to measure the ventilatory threshold and maximal oxygen uptake (V˙O₂max); 2) a cycling workload constant test at moderate domain (90% ventilatory threshold); 3) a cycling workload constant test at severe domain (110% V˙O₂max). Oxygen uptake and plasma lactate were measured during the tests. The contributions of the aerobic (A_MET), anaerobic lactic (LA_MET), and anaerobic alactic (AL_MET) systems were calculated based on the oxygen uptake during exercise, the oxygen energy equivalents provided by lactate accumulation, and the fast component of excess post-exercise oxygen consumption, respectively. In order to assess the intra-investigator variation, four different investigators performed the analyses independently using GEDAE-LaB. A direct comparison with commercial software was also provided.

Results

All subjects completed 10 min of exercise at moderate domain, while the time to exhaustion at severe domain was 144 ± 65 s. The A_MET, LA_MET, and AL_MET contributions during moderate domain were about 93, 2, and 5%, respectively. The A_MET, LA_MET, and AL_MET contributions during severe domain were about 66, 21, and 13%, respectively. No statistical differences were found between the energy system contributions and energy expenditure obtained by GEDAE-LaB and commercial software for both moderate and severe domains (P > 0.05). The ICC revealed that these estimates were highly reliable among the four investigators for both moderate and severe domains (all ICC ≥ 0.94).

Conclusion

These findings suggest that GEDAE-LaB is a free software easily comprehended by users minimally familiarized with adopted procedures for calculations of energetic profile using oxygen uptake and lactate accumulation during exercise. By providing availability of the software and its source code we hope to facilitate future related research.

Pacing in a self-paced world record attempt in 24-h road cycling

Background

Pacing strategy plays a major role in sport performance. However, there is a dearth of knowledge concerning pacing during ultra-endurance sport events. The present case study investigated the pacing of an ultra-cyclist in a self-paced attempt to break the world record in 24-h road cycling and, with all the caveats and the limitations affecting a case report, could be useful in generating hypotheses and further studies about pacing dynamics during prolonged sport performances.

Case description

A well experienced ultra-cyclist completed laps of 11.731 km during 24 h and the support crew recorded for each lap time and power output in Watt. The trend in cycling speed and power output across laps was investigated using regression analyses. A mixed-effects regression model including lap, ambient air temperature, air pressure, air humidity and wind speed as fixed variables was used to investigate a relationship of environmental factors with cycling speed.

Discussion and evaluation

The athlete achieved 896.173 km within the 24 h. He set a new world record by breaking the old record (Jure Robic, 2004, 834.77 km) by 61.403 km. He cycled at an average speed of 37.34 km/h with an average power output of 250.2 W. The decrease in cycling speed and power output across laps could be modelled linearly. Temperature and wind speed were related to cycling speed during the whole event. There was a significant interaction air temperature × relative humidity for the whole event.

Conclusions

The athlete adopted a positive pacing (i.e. speed gradually declined throughout the event) and environmental factors (i.e. temperature and wind speed) influenced cycling speed during the event.