Effects of endurance training on transient oxygen uptake responses in cyclists

Changes in Plasma Free Amino Acid Profile in Endurance Athletes over a 9-Month Training Cycle

We aimed to evaluate long-term changes in proteinogenic and non-proteinogenic plasma free amino acids (PFAA). Eleven male endurance triathletes participated in a 9-month study. Blood was collected at rest, immediately after exhaustive exercise, and during 30-min recovery, in four consecutive training phases: transition, general, specific, and competition. Twenty proteinogenic and 22 non-proteinogenic PFAAs were assayed using the LC-ESI-MS/MS technique. The structured training modified the patterns of exercise-induced PFAA response, with the competition phase being the most distinct from the others. Branched-chain amino acids (p = 0.002; η2 = 0.216), phenylalanine (p = 0.015; η2 = 0.153), methionine (p = 0.002; η2 = 0.206), and lysine (p = 0.006; η2 = 0.196) declined more rapidly between rest and exhaustion in the competition phase. Glutamine (p = 0.008; η2 = 0.255), glutamate (p = 0.006; η2 = 0.265), tyrosine (p = 0.001; η2 = 0.195), cystine (p = 0.042; η2 = 0.183), and serine (p < 0.001; η2 = 0.346) levels were reduced in the competition phase. Arginine (p = 0.046; η2 = 0.138) and aspartate (p = 0.011; η2 = 0.171) levels were highest during exercise in the transition phase. During the competition phase, α-aminoadipic acid (p = 0.023; η2 = 0.145), β-aminoisobutyric acid (p = 0.007; η2 = 0.167), β-alanine (p < 0.001; η2 = 0.473), and sarcosine (p = 0.017; η2 = 0.150) levels increased, whereas phosphoethanolamine (p = 0.037; η2 = 0.189) and taurine (p = 0.008; η2 = 0.251) concentrations decreased. Overtraining indicators were not elevated. The altered PFAA profile suggests adaptations within energy metabolic pathways such as the tricarboxylic acid cycle, oxidative phosphorylation, ammonia neutralization, the purine nucleotide cycle, and buffering of intracellular H+ ions. The changes seem to reflect normal adaptations.

VO₂FITTING: A Free and Open-Source Software for Modelling Oxygen Uptake Kinetics in Swimming and other Exercise Modalities

The assessment of oxygen uptake (VO₂) kinetics is a valuable non-invasive way to evaluate cardiorespiratory and metabolic response to exercise. The aim of the study was to develop, describe and evaluate an online VO₂ fitting tool (VO₂FITTING) for dynamically editing, processing, filtering and modelling VO₂ responses to exercise. VO₂FITTING was developed in Shiny, a web application framework for R language. Validation VO₂ datasets with both noisy and non-noisy data were developed and applied to widely-used models (n = 7) for describing different intensity transitions to verify concurrent validity. Subsequently, we then conducted an experiment with age-group swimmers as an example, illustrating how VO₂FITTING can be used to model VO₂ kinetics. Perfect fits were observed, and parameter estimates perfectly matched the known inputted values for all available models (standard error = 0; p < 0.001). The VO₂FITTING is a valid, free and open-source software for characterizing VO₂ kinetics in exercise, which was developed to help the research and performance analysis communities.

Moderate-Intensity Oxygen Uptake Kinetics: Is a Mono-Exponential Function Always Appropriate to Model the Response?

PURPOSE

This study investigated the existence of the oxygen uptake ([Formula: see text]) overshoot and the effects of exercise intensity and fitness status on the [Formula: see text] response during moderate-intensity exercise.

METHODS

Twelve "high-fitness" (M_age = 26 ± 5 years; M_height = 184.1 ± 5.4 cm; M_{body mass} = 76.6 ± 8.9 kg; mean peak oxygen uptake ([Formula: see text]peak) = 59.0 ± 3.3 mL·kg^-1·min·^-1) and 11 "moderate-fitness" (M_age = 29 ± 5 years; M_height = 178.7 ± 7.5 cm; M_{body mass} = 81.7 ± 10.9 kg; M_V̇O2peak = 45.2 ± 3.1 mL·kg^-1·min·^-1) participants performed square-wave transitions from unloaded cycling to 3 different intensities (70%, 82.5%, and 95% of the gas exchange threshold). The data were modeled using both a mono-exponential function (Model 1) and a function that included a switch-on component (Model 2). The overshoot was computed by subtracting the steady state from the peak of the modeled response and by calculating the area of the curve that was above steady state.

RESULTS

The goodness of fit was affected by model type (p = .002) and exercise intensity (p < .001). High-fitness participants displayed a smaller τ (p < .05) and a larger amplitude (p < .05) and were more likely to overshoot the steady state (p = .035). However, while exercise intensity did affect the amplitude (p < .001), it did not affect τ (p ≥ .05) or the likelihood of an overshoot occurring (p = .389).

CONCLUSION

While exercise intensity did not alter the [Formula: see text] response, fitness status affected τ and the likelihood of an overshoot occurring. The overshoot questions the traditional approach to modeling moderate-intensity [Formula: see text] data.

A "Wearable" Test for Maximum Aerobic Power: Real-Time Analysis of a 60-m Sprint Performance and Heart Rate Off-Kinetics

Maximum aerobic power (V˙O2peak) as an indicator of body fitness is today a very well-known concept not just for athletes but also for the layman. Unfortunately, the accurate measurement of that variable has remained a complex and exhaustive laboratory procedure, which makes it inaccessible to many active people. In this paper we propose a quick estimate of it, mainly based on the heart rate off-kinetics immediately after an all-out 60-m sprint run. The design of this test took into account the recent availability of wrist wearable, heart band free, multi-sensor smart devices, which could also inertially detect the different phases of the sprint and check the distance run. 25 subjects undertook the 60-m test outdoor and a V˙O2peak test on the laboratory treadmill. Running average speed, HR excursion during the sprint and the time constant (τ) of HR exponential decay in the off-kinetics were fed into a multiple regression, with measured V˙O2peak as the dependent variable. Statistics revealed that within the investigated range (25–55 ml O₂/(kg min)), despite a tendency to overestimate low values and underestimate high values, the three predictors confidently estimate individual V˙O2peak (R² = 0.65, p < 0.001). The same analysis has been performed on a 5-s averaged time course of the same measured HR off-kinetics, as these are the most time resolved data for HR provided by many modern smart watches. Results indicate that despite of the substantial reduction in sample size, predicted V˙O2peak still explain 59% of the variability of the measured V˙O2peak.

Mean Normalized Gain: A New Method for the Assessment of the Aerobic System Temporal Dynamics during Randomly Varying Exercise in Humans

The temporal dynamics of the oxygen uptake ([Formula: see text]) during moderate exercise has classically been related to physical fitness and a slower [Formula: see text] dynamics was associated with deterioration of physical health. However, methods that better characterize the aerobic system temporal dynamics remain challenging. The purpose of this study was to develop a new method (named mean normalized gain, MNG) to systematically characterize the [Formula: see text] temporal dynamics. Eight healthy, young adults (28 ± 6 years old, 175 ± 7 cm and 79 ± 13 kg) performed multiple pseudorandom binary sequence cycling protocols on different days and time of the day. The MNG was calculated as the normalized amplitude of the [Formula: see text] signal in frequency-domain. The MNG was validated considering the time constant τ obtained from time-domain analysis as reference. The intra-subject consistency of the MNG was checked by testing the same participant on different days and times of the day. The MNG and τ were strongly negatively correlated (r = -0.86 and p = 0.005). The MNG measured on different days and periods of the day was similar between conditions. Calculations for the MNG have inherent filtering characteristics enhancing reliability for the evaluation of the aerobic system temporal dynamics. In conclusion, the present study successfully validated the use of the MNG for aerobic system analysis and as a potential complementary tool to assess changes in physical fitness.

Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models

Physical activity levels are related through algorithms to the energetic demand, with no information regarding the integrity of the multiple physiological systems involved in the energetic supply. Longitudinal analysis of the oxygen uptake (V̇o₂) by wearable sensors in realistic settings might permit development of a practical tool for the study of the longitudinal aerobic system dynamics (i.e., V̇o₂ kinetics). This study evaluated aerobic system dynamics based on predicted V̇o₂ data obtained from wearable sensors during unsupervised activities of daily living (μADL). Thirteen healthy men performed a laboratory-controlled moderate exercise protocol and were monitored for ≈6 h/day for 4 days (μADL data). Variables derived from hip accelerometer (ACC_HIP), heart rate monitor, and respiratory bands during μADL were extracted and processed by a validated random forest regression model to predict V̇o₂. The aerobic system analysis was based on the frequency-domain analysis of ACC_HIP and predicted V̇o₂ data obtained during μADL. Optimal samples for frequency domain analysis (constrained to ≤0.01 Hz) were selected when ACC_HIP was higher than 0.05 g at a given frequency (i.e., participants were active). The temporal characteristics of predicted V̇o₂ data during μADL correlated with the temporal characteristics of measured V̇o₂ data during laboratory-controlled protocol ([Formula: see text] = 0.82, P < 0.001, n = 13). In conclusion, aerobic system dynamics can be investigated during unsupervised activities of daily living by wearable sensors. Although speculative, these algorithms have the potential to be incorporated into wearable systems for early detection of changes in health status in realistic environments by detecting changes in aerobic response dynamics. NEW & NOTEWORTHY The early detection of subclinical aerobic system impairments might be indicative of impaired physiological reserves that impact the capacity for physical activity. This study is the first to use wearable sensors in unsupervised activities of daily living in combination with novel machine learning algorithms to investigate the aerobic system dynamics with the potential to contribute to models of functional health status and guide future individualized health care in the normal population.

Aerobic system analysis based on oxygen uptake and hip acceleration during random over-ground walking activities

Deteriorated aerobic response to moderate exercise might precede the manifestation of clinical symptoms of noncommunicable diseases. The purpose of the current study was to verify that the use of current wearable technologies for analysis of pulmonary oxygen uptake (V̇o₂) dynamics during a pseudorandom ternary sequence (PRTS) over-ground walking protocol is a suitable procedure for the investigation of the aerobic response in more realistic settings. A wearable accelerometer located at the hip assessed the magnitude of the input changes delivered to the aerobic system. Eight adults (24 ± 4 yr old, 174 ± 7 cm, and 71.4 ± 7.4 kg) performed two identical PRTS over-ground walking protocols. In addition, they performed on the cycle ergometer two identical pseudorandom binary sequence (PRBS) protocols and one incremental protocol for maximal V̇o₂ determination. In the frequency domain, mean normalized gain amplitude (MNG in %) quantified V̇o₂ dynamics. The MNG during PRTS was correlated (r = -0.80, P = 0.01) with the V̇o₂ time constant (τ) obtained during cycling. The MNG estimated during PRBS was similar to the MNG estimated during PRTS (r = 0.80, P = 0.01). The maximal V̇o₂ correlated with the MNG obtained during the PRBS (r = 0.79, P = 0.01) and PRTS (r = 0.78, P = 0.02) protocols. In conclusion, PRTS over-ground walking protocol can be used to evaluate the aerobic system dynamics by the simultaneous measurement of V̇o₂ and hip acceleration. In addition, the aerobic response dynamics from PRBS and PRTS were correlated to maximal V̇o₂ This study has shown that wearable technologies in combination with assessment of MNG, a novel indicator of system dynamics, open new possibilities to monitor cardiorespiratory health under conditions that better simulate activities of daily living than cardiopulmonary exercise testing performed in a medical environment.

Unchanged content of oxidative enzymes in fast-twitch muscle fibers and V˙O2 kinetics after intensified training in trained cyclists

The present study examined if high intensity training (HIT) could increase the expression of oxidative enzymes in fast-twitch muscle fibers causing a faster oxygen uptake () response during intense (INT), but not moderate (MOD), exercise and reduce the slow component and muscle metabolic perturbation during INT. Pulmonary kinetics was determined in eight trained male cyclists (-max: 59 ± 4 (means ± SD) mL min⁻¹ kg⁻¹) during MOD (205 ± 12 W ∼65% -max) and INT (286 ± 17 W ∼85% -max) exercise before and after a 7-week HIT period (30-sec sprints and 4-min intervals) with a 50% reduction in volume. Both before and after HIT the content in fast-twitch fibers of CS (P < 0.05) and COX-4 (P < 0.01) was lower, whereas PFK was higher (P < 0.001) than in slow-twitch fibers. Content of CS, COX-4, and PFK in homogenate and fast-twitch fibers was unchanged with HIT. Maximal activity (μmol g DW⁻¹ min⁻¹) of CS (56 ± 8 post-HIT vs. 59 ± 10 pre-HIT), HAD (27 ± 6 vs. 29 ± 3) and PFK (340 ± 69 vs. 318 ± 105) and the capillary to fiber ratio (2.30 ± 0.16 vs. 2.38 ± 0.20) was unaltered following HIT. kinetics was unchanged with HIT and the speed of the primary response did not differ between MOD and INT. Muscle creatine phosphate was lower (42 ± 15 vs. 66 ± 17 mmol kg DW⁻¹) and muscle lactate was higher (40 ± 18 vs. 14 ± 5 mmol kg DW⁻¹) at 6 min of INT (P < 0.05) after compared to before HIT. A period of intensified training with a volume reduction did not increase the content of oxidative enzymes in fast-twitch fibers, and did not change kinetics.

High-intensity interval training, solutions to the programming puzzle: Part I: cardiopulmonary emphasis

High-intensity interval training (HIT), in a variety of forms, is today one of the most effective means of improving cardiorespiratory and metabolic function and, in turn, the physical performance of athletes. HIT involves repeated short-to-long bouts of rather high-intensity exercise interspersed with recovery periods. For team and racquet sport players, the inclusion of sprints and all-out efforts into HIT programmes has also been shown to be an effective practice. It is believed that an optimal stimulus to elicit both maximal cardiovascular and peripheral adaptations is one where athletes spend at least several minutes per session in their 'red zone,' which generally means reaching at least 90% of their maximal oxygen uptake (VO2max). While use of HIT is not the only approach to improve physiological parameters and performance, there has been a growth in interest by the sport science community for characterizing training protocols that allow athletes to maintain long periods of time above 90% of VO2max (T@VO2max). In addition to T@VO2max, other physiological variables should also be considered to fully characterize the training stimulus when programming HIT, including cardiovascular work, anaerobic glycolytic energy contribution and acute neuromuscular load and musculoskeletal strain. Prescription for HIT consists of the manipulation of up to nine variables, which include the work interval intensity and duration, relief interval intensity and duration, exercise modality, number of repetitions, number of series, as well as the between-series recovery duration and intensity. The manipulation of any of these variables can affect the acute physiological responses to HIT. This article is Part I of a subsequent II-part review and will discuss the different aspects of HIT programming, from work/relief interval manipulation to the selection of exercise mode, using different examples of training cycles from different sports, with continued reference to T@VO2max and cardiovascular responses. Additional programming and periodization considerations will also be discussed with respect to other variables such as anaerobic glycolytic system contribution (as inferred from blood lactate accumulation), neuromuscular load and musculoskeletal strain (Part II).

Oxygen uptake kinetics

Muscular exercise requires transitions to and from metabolic rates often exceeding an order of magnitude above resting and places prodigious demands on the oxidative machinery and O2-transport pathway. The science of kinetics seeks to characterize the dynamic profiles of the respiratory, cardiovascular, and muscular systems and their integration to resolve the essential control mechanisms of muscle energetics and oxidative function: a goal not feasible using the steady-state response. Essential features of the O2 uptake (VO2) kinetics response are highly conserved across the animal kingdom. For a given metabolic demand, fast VO2 kinetics mandates a smaller O2 deficit, less substrate-level phosphorylation and high exercise tolerance. By the same token, slow VO2 kinetics incurs a high O2 deficit, presents a greater challenge to homeostasis and presages poor exercise tolerance. Compelling evidence supports that, in healthy individuals walking, running, or cycling upright, VO2 kinetics control resides within the exercising muscle(s) and is therefore not dependent upon, or limited by, upstream O2-transport systems. However, disease, aging, and other imposed constraints may redistribute VO2 kinetics control more proximally within the O2-transport system. Greater understanding of VO2 kinetics control and, in particular, its relation to the plasticity of the O2-transport/utilization system is considered important for improving the human condition, not just in athletic populations, but crucially for patients suffering from pathologically slowed VO2 kinetics as well as the burgeoning elderly population.

Oxygen uptake kinetics and middle distance swimming performance

OBJECTIVE

The aim of this study was to determine whether V˙O(2) kinetics and specifically, the time constant of transitions from rest to heavy (τ(p)H) and severe (τ(p)S) exercise intensities, are related to middle distance swimming performance.

DESIGN

Fourteen highly trained male swimmers (mean ± SD: 20.5 ± 3.0 yr; 75.4 ± 12.4 kg; 1.80 ± 0.07 m) performed an discontinuous incremental test, as well as square wave transitions for heavy and severe swimming intensities, to determine V˙O(2) kinetics parameters using two exponential functions.

METHODS

All the tests involved front-crawl swimming with breath-by-breath analysis using the Aquatrainer swimming snorkel. Endurance performance was recorded as the time taken to complete a 400 m freestyle swim within an official competition (T400), one month from the date of the other tests.

RESULTS

T400 (Mean ± SD) (251.4 ± 12.4 s) was significantly correlated with τ(p)H (15.8 ± 4.8s; r=0.62; p=0.02) and τ(p)S (15.8 ± 4.7s; r=0.61; p=0.02). The best single predictor of 400 m freestyle time, out of the variables that were assessed, was the velocity at V˙O(2max)vV˙O(2max), which accounted for 80% of the variation in performance between swimmers. However, τ(p)H and V˙O(2max) were also found to influence the prediction of T400 when they were included in a regression model that involved respiratory parameters only.

CONCLUSIONS

Faster kinetics during the primary phase of the V˙O(2) response is associated with better performance during middle-distance swimming. However, vV˙O(2max) appears to be a better predictor of T400.

Assessment of physiological capacities of elite athletes & respiratory limitations to exercise performance

Physiological assessment of athletes is an important process for the characterization of the athlete, monitoring progress and the trained state or 'level of preparedness' of an athlete, as well as aiding the process of training program design. Interestingly, the majority of physiological assessments performed on athletes can also be performed on children with disease, and therefore clinicians can learn a great deal about physiology and assessment of patient populations through the examination of the physiological responses of elite athletes. This review describes typical physiological responses of elite athletes to tests of aerobic and anaerobic metabolism and provides a specific focus upon respiratory limitations to exercise performance. Typical responses of elite athletes are described to provide the scientist and clinician with a perspective of the upper range of physiological capacities of elite athletes.

Influence of repeated sprint training on pulmonary O2 uptake and muscle deoxygenation kinetics in humans

We hypothesized that a short-term training program involving repeated all-out sprint training (RST) would be more effective than work-matched, low-intensity endurance training (ET) in enhancing the kinetics of oxygen uptake (V̇o2) and muscle deoxygenation {deoxyhemoglobin concentration ([HHb])} following the onset of exercise. Twenty-four recreationally active subjects (15 men, mean ± SD: age 21 ± 4 yr, height 173 ± 9 cm, body mass 71 ± 11 kg) were allocated to one of three groups: RST, which completed six sessions of four to seven 30-s RSTs; ET, which completed six sessions of work-matched, moderate-intensity cycling; and a control group (CON). All subjects completed moderate-intensity and severe-intensity “step” exercise transitions before (Pre) and after the 2-wk intervention period (Post). Following RST, [HHb] kinetics were speeded, and the amplitude of the [HHb] response was increased during both moderate and severe exercise ( P < 0.05); the phase II V̇o2 kinetics were accelerated for both moderate (Pre: 28 ± 8, Post: 21 ± 8 s; P < 0.01) and severe (Pre: 29 ± 5, Post: 23 ± 5 s; P < 0.05) exercise; the amplitude of the V̇o2 slow component was reduced (Pre: 0.52 ± 0.19, Post: 0.40 ± 0.17 l/min; P < 0.01); and exercise tolerance during severe exercise was improved by 53% (Pre: 700 ± 234, Post: 1,074 ± 431 s; P < 0.01). None of these parameters was significantly altered in the ET and CON groups. Six sessions of RST, but not ET, resulted in changes in [HHb] kinetics consistent with enhanced fractional muscle O2 extraction, faster V̇o2 kinetics, and an increased tolerance to high-intensity exercise.

Effect of short-term high-intensity interval training vs. continuous training on O2 uptake kinetics, muscle deoxygenation, and exercise performance

The early time course of adaptation of pulmonary O(2) uptake (Vo(2)(p)) (reflecting muscle O(2) consumption) and muscle deoxygenation kinetics (reflecting the rate of O(2) extraction) were examined during high-intensity interval (HIT) and lower-intensity continuous endurance (END) training. Twelve male volunteers underwent eight sessions of either HIT (8-12 x 1-min intervals at 120% maximal O(2) uptake separated by 1 min of rest) or END (90-120 min at 65% maximal O(2) uptake). Subjects completed step transitions to a moderate-intensity work rate ( approximately 90% estimated lactate threshold) on five occasions throughout training, and ramp incremental and constant-load performance tests were conducted at pre-, mid-, and posttraining periods. Vo(2)(p) was measured breath-by-breath by mass spectrometry and volume turbine. Deoxygenation (change in deoxygenated hemoglobin concentration; Delta[HHb]) of the vastus lateralis muscle was monitored by near-infrared spectroscopy. The fundamental phase II time constants for Vo(2)(p) (tauVo(2)) and deoxygenation kinetics {effective time constant, tau' = (time delay + tau), Delta[HHb]} during moderate-intensity exercise were estimated using nonlinear least-squares regression techniques. The tauVo(2) was reduced by approximately 20% (P < 0.05) after only two training sessions and by approximately 40% (P < 0.05) after eight training sessions (i.e., posttraining), with no differences between HIT and END. The tau'Delta[HHb] ( approximately 20 s) did not change over the course of eight training sessions. These data suggest that faster activation of muscle O(2) utilization is an early adaptive response to both HIT and lower-intensity END training. That Delta[HHb] kinetics (a measure of fractional O(2) extraction) did not change despite faster Vo(2)(p) kinetics suggests that faster kinetics of muscle O(2) utilization were accompanied by adaptations in local muscle (microvascular) blood flow and O(2) delivery, resulting in a similar "matching" of blood flow to O(2) utilization. Thus faster kinetics of Vo(2)(p) during the transition to moderate-intensity exercise occurs after only 2 days HIT and END training and without changes to muscle deoxygenation kinetics, suggesting concurrent adaptations to microvascular perfusion.

Relationships between pulmonary oxygen uptake kinetics and other measures of aerobic fitness in middle- and long-distance runners

The purpose of this study was to assess the relationships between on- and off-transient pulmonary oxygen uptake kinetics and other measures of aerobic fitness in middle-distance (MD) and long-distance (LD) runners. 16 MD and 16 LD runners participated and each completed a series of tests to determine their maximal oxygen uptake (VO2max) gas-exchange threshold (GET), running economy (RE) and the primary time-constant for VO2 at the onset (tau(on)) and offset (tau(off)) of moderate-intensity treadmill exercise. Relationships between measures were established using Pearson product moment correlations (r). The relationships between VO2 kinetic parameter and other aerobic measures varied depending on classification of runner (MD or LD runner). There was a significant relationship between (VO2max) and tau(on) and tau(off) in LD runners (tau(on): r = -0.70, P = 0.003; tau(off): r = -0.55, P = 0.029), but not for MD (tau(on): r = 0.24, P = 0.366; tau(off): r = -0.09, P = 0.739). Similar relationships also existed between GET, RE and kinetic parameters for LD but not MD runners. The inconsistent relationships between VO2 kinetic parameters and other measures of aerobic fitness in MD and LD runners is intriguing. Further work is now required to identify how the volume and intensity of training influence peripheral adaptations in Type I and Type II fibres and how these may, or may not influence VO2 kinetic responses in the moderate- and heavy-intensity domain.

Moderate-domain pulmonary oxygen uptake kinetics and endurance running performance

The aims of this study were to determine if the primary time constant (tau) for oxygen uptake (VO2) at the onset of moderate-intensity treadmill exercise is related to endurance running performance, and to establish if tau could be considered a determinant of endurance running performance. Thirty-six endurance trained male runners performed a series of laboratory tests, on separate days, to determine maximal oxygen uptake (VO2max), the ventilatory threshold (VT) and running economy. In addition, runners completed six transitions from walking (4 km x h-1) to moderate-intensity running (80% VT) for the determination of the VO2 primary time constant and mean response time. During all tests, pulmonary gas-exchange was measured breath-by-breath. Endurance running performance was determined using a treadmill 5-km time-trial, after which runners were considered as combined performers (n=36) and, using a ranking system, high performers (n=10) and low performers (n=10). Relationships between tau and endurance running performance were quantified using correlation coefficients (r). Stepwise multiple regression was used to determine the primary predictor variables of endurance running performance in combined performers. Moderate correlations were observed between tau, mean response time and endurance running performance, but only for the combined performers (r=-0.55, P=0.001 and r=-0.50, P=0.002, respectively). The regression model for predicting 5-km performance did not include tau or mean response time. The velocity at VO2max was strongly correlated to endurance running performance in all groups (r=0.72 - 0.84, P < 0.01) and contributed substantially to the prediction of performance. In conclusion, the results suggest that despite their role in determining the oxygen deficit and having a moderate relationship with endurance running performance, neither tau nor mean response time is a primary determinant of endurance running performance.

Effects of high-intensity interval training on the VO2 response during severe exercise

This study examined the effect of high-intensity interval training on the VO2 response during severe, constant-load exercise. Prior to, and following training, 10 females (V O2 peak 37.4+/-6.0 mL kg-1 min-1) performed a graded exercise test to determine VO2 peak and lactate threshold (LT) and a 6 min cycle test (CT) at the pre-training VO2 peak intensity. Training involved high-intensity intervals (2 min work, 1 min rest) performed 3x week for 8 weeks. Breath-by-breath data from 0 to 6 min during the CT were smoothed using 5s averages and fit to a bi-exponential model starting from 20s. Training resulted in significant improvements in VO2 max (2.34+/-0.37-2.78+/-0.30 L min-1), power at VO2 max (170+/-26-204+/-25 W) and power at LT (113+/-17-136+/-20 W) (p<0.05). Following training, the VO2 response showed a significant increase in the amplitude of the primary phase (A1) (1396+/-103-1695+/-100 mL min-1; p<0.05) and end-exercise VO2 (VO2 EE), with no difference (p>0.05) in the time constants of either phase or the amplitude of the slow component (318+/-67-380+/-48 mL; p=0.15). In conjunction, accumulated oxygen deficit (AOD) (43.7+/-9.8-17.2+/-2.8 mL O2 eq kg-1) and anaerobic contribution to the CT (19.4+/-4.4-7.2+/-1.2%) were significantly reduced. In contrast to previous moderate-intensity research, a high-intensity interval training program increased A1 and VO2 EE for the same absolute exercise intensity, decreasing the AOD during a severe-intensity CT.

Objective and subjective analysis of the training content in young cyclists

The purpose of this study was to analyse the objective and subjective training for young cyclists that is prescribed by their coaches. Seven cyclists performed an incremental exercise to exhaustion before and after 14 weeks of training using an incremental test to determine their maximal oxygen uptake (VO2 max), the velocity associated with VO2 max (vVO<I>2</I>max), and the velocity associated with the ventilatory threshold (vVT). Cyclists completed a training record with the actual content and the perceived exertion of each training session during these 14 weeks. We have focused on the actual content of the training prescribed by the coaches. Analysis of the content of each session allowed us to calculate the objective training load (volume at different intensities) and to determine the subjective training load from perceived exertion ratings (training load, monotony, strain, and fitness-fatigue). The results showed that cyclists were training at a relatively low intensity and that training rating of perceived exhaustion was weak. Moreover, after 14 weeks of training, VO2 max did not change whereas vVO<I>2</I>max and vVT increased significantly. Therefore, a discrepancy may exist between what is perceived during training and the effects of training. Consequently, objective and subjective indices collected from training books provided useful information supplementary to that recorded from the physiological indices alone.Key words: training load, training book, perceived exertion, performance.

Influence of Continuous and Interval Training on Oxygen Uptake On-Kinetics

PURPOSE

To examine the relative effectiveness of moderate-intensity continuous training and high-intensity interval training on pulmonary O2 uptake (VO2) kinetics at the onset of moderate- and severe-intensity cycle exercise in previously sedentary subjects.

METHODS

Twenty-three healthy subjects (11 males; mean +/- SD age 24 +/- 5 yr; VO2peak 34.3 +/- 5.5 mL x kg(-1) x min(-1)) were assigned to one of three groups: a continuous training group that completed three to four sessions per week of 30-min duration at 60% VO2peak (LO); an interval training group that completed three to four sessions per week involving 20 x 1-min exercise bouts at 90% VO2peak separated by 1-min rest periods (HI); or a control group (CON). Before and after the 6-wk intervention period, all subjects completed a series of step exercise tests to moderate and severe work rates during which pulmonary VO2 was measured breath-by-breath.

RESULTS

ANOVA revealed that continuous and interval training were similarly effective in reducing the phase II VO2 time constant during moderate (LO: from 31 +/- 8 to 23 +/- 5 s; HI: from 32 +/- 9 to 21 +/- 4 s; both P < 0.05; CON: from 30 +/- 6 to 29 +/- 7 s; NSD) and severe exercise (LO: from 35 +/- 6 to 24 +/- 7 s; HI: from 32 +/- 11 to 24 +/- 7 s; both P < 0.05; CON: from 27 +/- 7 to 25 +/- 5 s; NSD) and in reducing the amplitude of the VO2 slow component (LO: from 0.38 +/- 0.10 to 0.29 +/- 0.09 L x min(-1); HI: from 0.41 +/- 0.28 to 0.30 +/- 0.28 L x min(-1); both P < 0.05; CON: from 0.54 +/- 0.22 to 0.66 +/- 0.38 L.min; NSD).

CONCLUSIONS

Six weeks of low-intensity continuous training and high-intensity interval training were similarly effective in enhancing VO2 on-kinetics following step transitions to moderate and severe exercise in previously untrained subjects.

Multiple sprint work : physiological responses, mechanisms of fatigue and the influence of aerobic fitness

The activity patterns of many sports (e.g. badminton, basketball, soccer and squash) are intermittent in nature, consisting of repeated bouts of brief (<or=6-second) maximal/near-maximal work interspersed with relatively short (<or=60-second) moderate/low-intensity recovery periods. Although this is a general description of the complex activity patterns experienced in such events, it currently provides the best means of directly assessing the physiological response to this type of exercise. During a single short (5- to 6-second) sprint, adenosine triphosphate (ATP) is resynthesised predominantly from anaerobic sources (phosphocreatine [PCr] degradation and glycolysis), with a small (<10%) contribution from aerobic metabolism. During recovery, oxygen uptake (V-O2) remains elevated to restore homeostasis via processes such as the replenishment of tissue oxygen stores, the resynthesis of PCr, the metabolism of lactate, and the removal of accumulated intracellular inorganic phosphate (Pi). If recovery periods are relatively short, V-O2 remains elevated prior to subsequent sprints and the aerobic contribution to ATP resynthesis increases. However, if the duration of the recovery periods is insufficient to restore the metabolic environment to resting conditions, performance during successive work bouts may be compromised. Although the precise mechanisms of fatigue during multiple sprint work are difficult to elucidate, evidence points to a lack of available PCr and an accumulation of intracellular Pi as the most likely causes. Moreover, the fact that both PCr resynthesis and the removal of accumulated intracellular Pi are oxygen-dependent processes has led several authors to propose a link between aerobic fitness and fatigue during multiple sprint work. However, whilst the theoretical basis for such a relationship is compelling, corroborative research is far from substantive. Despite years of investigation, limitations in analytical techniques combined with methodological differences between studies have left many issues regarding the physiological response to multiple sprint work unresolved. As such, multiple sprint work provides a rich area for future applied sports science research.

Characterisation, asymmetry and reproducibility of on- and off-transient pulmonary oxygen uptake kinetics in endurance-trained runners

The purpose of this study was three-fold: (1) to characterise both the on- and off-transient oxygen uptake (V(.)O(2)) kinetics in endurance runners during moderate-intensity treadmill running; (2) to determine the degree of symmetry between on- and off-transients; and (3) to determine the reproducibility of V(.)O(2) kinetic parameters in endurance runners. Twelve endurance-trained runners [mean (SD) age 25.2 (4.7) years, body mass 70.1 (9.7) kg, height 179.5 (7.5) cm, ventilatory threshold (V(T)), 3,429 (389) ml.min(-1), maximal V(.)O(2) (V(.)O(2max)) 4,138 (625) ml.min(-1)] performed two multiple square-wave transition protocols on separate days. The protocol consisted of six (three transitions, 15 min rest, three transitions) square-wave transitions from walking at 4 km.h(-1) to running at a speed equivalent to 80% of the V(.)O(2) at the V(T) (80%V(T)). To determine the reproducibility, the protocol was repeated on a separate day (i.e. a test-retest design). Pulmonary gas-exchange was measured breath-by-breath. The V(.)O(2) data were modelled [from 20 s post-onset (or offset) of exercise] using non-linear least squares regression by a mono-exponential model, incorporating a time delay. The on- and off-transient time constants (tau(on) and tau(off)), mean response times (MRT(on) and MRT(off)) and amplitudes (A(on) and A(off)) were obtained from the model fit. On- and off transient kinetics were compared using paired t-tests. The reproducibility of each kinetic parameter was explored using statistical (paired t-tests) and non-statistical techniques [95% limits of agreement (LOA, including measurement error and systematic bias) and coefficient of variation (CV)]. It was found that the tau(on) [12.4 (1.9)] was significantly (P<0.001) shorter than tau(off) [24.5 (2.3) s]. Similarly, MRT(on) [27.1 (1.9) s] was shorter than MRT(off) [33.4 (2.2) s]. With respect to the reproducibility of the parameters, paired t-tests did not reveal significant differences between test 1 and test 2 for any on- or off-transient V(.)O(2) kinetic parameter (P>0.05). The LOA for tau(on) (1.9 s), tau(off) (2.3 s), MRT(on) (1.2 s), MRT(off) (3.2 s), A(on) (204 ml.min(-1)) and A(off) (198 ml.min(-1)) were narrow and acceptable. Furthermore, the measurement error (range, 4.3 to 15.1%) and CV (1.3 to 4.8%) all indicated good reproducibility. There was a tendency for tau(off) to be more reproducible than tau(on). However, MRT(on) was the most reproducible kinetic parameter. Overall, the results suggest that: (1) a multiple square-wave transition protocol can be used to characterise, reproducibly, both on- and off-transient V(.)O(2) kinetic parameters during treadmill running in runners; (2) the phase II time constant is independent of V(.)O(2) (max), and (3) asymmetry exists between on- and off transient V(.)O(2) kinetic parameters.

Dynamic Responses of Oxygen Uptake at the Onset and End of Moderate and Heavy Exercise in Trained Subjects

Inconsistencies about dynamic asymmetry between the on- and off-transient responses in [Formula: see text] are found in the literature. Therefore the purpose of this study was to examine [Formula: see text]on-and off-transients during moderate- and heavy-intensity cycling exercise in trained subjects. Ten men underwent an initial incremental test for the estimation of ventilatory threshold (VT) and, on different days, two bouts of square-wave exercise at moderate (< VT) and heavy (> VT) intensities. [Formula: see text] kinetics in exercise and recovery were better described by a single exponential model (< VT), or by a double exponential with two time delays (> VT). For moderate exercise, we found a symmetry of [Formula: see text] kinetics between the on- and off-transients (i.e., fundamental component), consistent with a system manifesting linear control dynamics. For heavy exercise, a slow component superimposed on the fundamental phase was expressed in both the exercise and recovery, with similar parameter estimates. But the on-transient values of the time constant were appreciably faster than the associated off-transient, and independent of the work rate imposed (< VT and > VT). Our results do not support a dynamically linear system model of [Formula: see text] during cycling exercise in the heavy-intensity domain. Key words: oxygen uptake kinetics, on- and off-transients, slow component

Oxygen uptake kinetic response to exercise in children

The oxygen uptake (.VO2) kinetic response to exercise assesses the integrated response of the cardiovascular system and the metabolic requirements of the exercising muscle. The response differs both qualitatively and quantitatively according to the exercise intensity domain (moderate, heavy, very heavy and severe) in which it lies. In each domain, a rapid cardiodynamic phase 1 response is followed by an exponential rise in .VO2 toward a projected steady state (for which the inverse of the rate constant is represented as the time constant [tau]). The achievement of the new steady state may be delayed and elevated due to a slow component of .VO2 in the heavy intensity domain, or above this exercise intensity, the achievement of peak .VO2 truncates the exercise period. For each of these domains, specific mathematical models have been identified and may be applied to appropriate breath-by-breath response data in order to allow quantification of the response. Much of our understanding of the .VO2 kinetic response and the methodologies required to obtain meaningful assessment are derived from adult studies. Although pioneering, early studies with young people were lacking in suitable equipment and the methodologies used may consequently have clouded the true interpretation of the kinetic response. More recently, with the advent of online breath-by-breath analysis systems, studies using mathematical modelling procedures have been hindered by the low signal-to-noise ratio which is inherent to children's response profiles. This has the effect of widening the confidence intervals for estimated parameters, and therefore questions the validity in making inter- and intra-study comparisons. In addition, the difficulty in accurately assessing domain demarcators, especially critical power, often confounds the interpretation of age and sex effects on the exercise response.This review therefore analyses the literature to date on the .VO2 kinetic response during childhood and adolescence, and specifically highlights concerns with technical rigour in its determination. Rigorously determined data indicate that the exponential rise in .VO2 is more rapid in children than adults and that at exercise intensities above the anaerobic threshold, the slow component of .VO2 may be attenuated in the young. Sex differences have not been found in the response to moderate intensity exercise, and there does not appear to be a consistent correlation between peak .VO2 and tau in children. However, sex differences in the response to exercise intensities above the anaerobic threshold are identified and discussed.

Oxygen uptake kinetics and time to exhaustion in cycling and running: a comparison between trained and untrained subjects

The objective of the present study was to compare pulmonary gas exchange kinetics (VO2 kinetics) and time to exhaustion (Tlim) between trained and untrained individuals during severe exercise performed on a cycle ergometer and treadmill. Eleven untrained males in running (UR) and cycling (UC), nine endurance cyclists (EC), and seven endurance runners (ER) were submitted to the following tests on separate days: (i) incremental test for determination of maximal oxygen uptake (VO2max) and the intensity associated with the achievement of VO2max (IVO2max) on a mechanical braked cycle ergometer (EC and UC) and on a treadmill (ER and UR); (ii) all-out exercise bout performed at IVO2max to determine the time to exhaustion at IVO2max (Tlim) and the time constant of oxygen uptake kinetics (tau). The tau was significantly faster in trained group, both in cycling (EC = 28.2 +/- 4.7s; UC = 63.8 +/- 25.0s) and in running (ER = 28.5 +/- 8.5s; UR = 59.3 +/- 12.0s). Tlim of untrained was significantly lower in cycling (EC = 384.4 +/- 66.6s vs. UC; 311.1 +/- 105.7 s) and higher in running (ER = 309.2 +/- 176.6 s vs. UR = 439.8 +/- 104.2 s). We conclude that the VO2 kinetic response at the onset of severe exercise, carried out at the same relative intensity is sensitive to endurance training, irrespective of the exercise type. The endurance training seems to differently influence Tlim during exercise at IVO2max in running and cycling.

Dynamic responses of O2 uptake at the onset and end of exercise in trained subjects

Inconsistencies about dynamic asymmetry between the on- and off-transient responses in .VO2 are found in the literature. Therefore the purpose of this study was to examine .VO2on- and off-transients during moderate- and heavy-intensity cycling exercise in trained subjects. Ten men underwent an initial incremental test for the estimation of ventilatory threshold (VT) and, on different days, two bouts of square-wave exercise at moderate (<VT) and heavy (>VT) intensities. .VO2 kinetics in exercise and recovery were better described by a single exponential model (<VT) or by a double exponential with two time delays (>VT). For moderate exercise, we found a symmetry of .VO2 kinetics between the on- and off-transients (i.e., fundamental component), consistent with a system manifesting linear control dynamics. For heavy exercise, a slow component superimposed on the fundamental phase was expressed in both the exercise and recovery, with similar parameter estimates. But the on-transient values of the time constant were appreciably faster than the associated off-transient, and independent of the work rate imposed (<VT and >VT). Our results do not support a dynamically linear system model of .VO2 during cycling exercise in the heavy-intensity domain.

A Framework for Understanding the Training Process Leading to Elite Performance

The development of performance in competition is achieved through a training process that is designed to induce automation of motor skills and enhance structural and metabolic functions. Training also promotes self-confidence and a tolerance for higher training levels and competition. In general, there are two broad categories of athletes that perform at the highest level: (i) the genetically talented (the thoroughbred); and (ii) those with a highly developed work ethic (the workhorse) with a system of training guiding their effort. The dynamics of training involve the manipulation of the training load through the variables: intensity, duration and frequency. In addition, sport activities are a combination of strength, speed and endurance executed in a coordinated and efficient manner with the development of sport-specific characteristics. Short- and long-term planning (periodisation) requires alternating periods of training load with recovery for avoiding excessive fatigue that may lead to overtraining. Overtraining is long-lasting performance incompetence due to an imbalance of training load, competition, non-training stressors and recovery. Furthermore, annual plans are normally constructed in macro-, meso- and microcycles around the competitive phases with the objective of improving performance for a peak at a predetermined time. Finally, at competition time, optimal performance requires a healthy body, and integration of not only the physiological elements but also the psychological, technical and tactical components.

Interval training program optimization in highly trained endurance cyclists

PURPOSE

The purpose of this study was to examine the influence of three different high-intensity interval training (HIT) regimens on endurance performance in highly trained endurance athletes.

METHODS

Before, and after 2 and 4 wk of training, 38 cyclists and triathletes (mean +/- SD; age = 25 +/- 6 yr; mass = 75 +/- 7 kg; VO(2peak) = 64.5 +/- 5.2 mL x kg(-1) min(-1)) performed: 1) a progressive cycle test to measure peak oxygen consumption (VO(2peak)) and peak aerobic power output (PPO), 2) a time to exhaustion test (T(max)) at their VO(2peak) power output (P(max)), as well as 3) a 40-km time-trial (TT(40)). Subjects were matched and assigned to one of four training groups (G(2), N = 8, 8 x 60% T(max) at P(max), 1:2 work:recovery ratio; G(2), N = 9, 8 x 60% T(max) at P(max), recovery at 65% HR(max); G(3), N = 10, 12 x 30 s at 175% PPO, 4.5-min recovery; G(CON), N = 11). In addition to G(1), G(2), and G(3) performing HIT twice per week, all athletes maintained their regular low-intensity training throughout the experimental period.

RESULTS

All HIT groups improved TT(40) performance (+4.4 to +5.8%) and PPO (+3.0 to +6.2%) significantly more than G(CON) (-0.9 to +1.1%; P < 0.05). Furthermore, G(1) (+5.4%) and G(2) (+8.1%) improved their VO(2peak) significantly more than G(CON) (+1.0%; P < 0.05).

CONCLUSION

The present study has shown that when HIT incorporates P(max) as the interval intensity and 60% of T(max) as the interval duration, already highly trained cyclists can significantly improve their 40-km time trial performance. Moreover, the present data confirm prior research, in that repeated supramaximal HIT can significantly improve 40-km time trial performance.

Effects of concurrent endurance and strength training on running economy and .VO(2) kinetics

PURPOSE

It has been suggested that endurance training influences the running economy (CR) and the oxygen uptake (.VO(2)) kinetics in heavy exercise by accelerating the primary phase and attenuating the .VO(2) slow component. However, the effects of heavy weight training (HWT) in combination with endurance training remain unclear. The purpose of this study was to examine the influence of a concurrent HWT+endurance training on CR and the .VO(2) kinetics in endurance athletes.

METHODS

Fifteen triathletes were assigned to endurance+strength (ES) or endurance-only (E) training for 14 wk. The training program was similar, except ES performed two HWT sessions a week. Before and after the training period, the subjects performed 1) an incremental field running test for determination of .VO(2max) and the velocity associated (V(.VO2max)), the second ventilatory threshold (VT(2)); 2) a 3000-m run at constant velocity, calculated to require 25% of the difference between .VO(2max) and VT(2), to determine CR and the characteristics of the VO(2) kinetics; 3) maximal hopping tests to determine maximal mechanical power and lower-limb stiffness; 4) maximal concentric lower-limb strength measurements.

RESULTS

After the training period, maximal strength were increased (P < 0.01) in ES but remained unchanged in E. Hopping power decreased in E (P < 0.05). After training, economy (P < 0.05) and hopping power (P < 0.001) were greater in ES than in E. .VO(2max), leg hopping stiffness and the .VO(2) kinetics were not significantly affected by training either in ES or E.

CONCLUSION

Additional HWT led to improved maximal strength and running economy with no significant effects on the .VO(2) kinetics pattern in heavy exercise.

The scientific basis for high-intensity interval training: optimising training programmes and maximising performance in highly trained endurance athletes

While the physiological adaptations that occur following endurance training in previously sedentary and recreationally active individuals are relatively well understood, the adaptations to training in already highly trained endurance athletes remain unclear. While significant improvements in endurance performance and corresponding physiological markers are evident following submaximal endurance training in sedentary and recreationally active groups, an additional increase in submaximal training (i.e. volume) in highly trained individuals does not appear to further enhance either endurance performance or associated physiological variables [e.g. peak oxygen uptake (VO2peak), oxidative enzyme activity]. It seems that, for athletes who are already trained, improvements in endurance performance can be achieved only through high-intensity interval training (HIT). The limited research which has examined changes in muscle enzyme activity in highly trained athletes, following HIT, has revealed no change in oxidative or glycolytic enzyme activity, despite significant improvements in endurance performance (p < 0.05). Instead, an increase in skeletal muscle buffering capacity may be one mechanism responsible for an improvement in endurance performance. Changes in plasma volume, stroke volume, as well as muscle cation pumps, myoglobin, capillary density and fibre type characteristics have yet to be investigated in response to HIT with the highly trained athlete. Information relating to HIT programme optimisation in endurance athletes is also very sparse. Preliminary work using the velocity at which VO2max is achieved (V(max)) as the interval intensity, and fractions (50 to 75%) of the time to exhaustion at V(max) (T(max)) as the interval duration has been successful in eliciting improvements in performance in long-distance runners. However, V(max) and T(max) have not been used with cyclists. Instead, HIT programme optimisation research in cyclists has revealed that repeated supramaximal sprinting may be equally effective as more traditional HIT programmes for eliciting improvements in endurance performance. Further examination of the biochemical and physiological adaptations which accompany different HIT programmes, as well as investigation into the optimal HIT programme for eliciting performance enhancements in highly trained athletes is required.

Ventilatory and gas exchange responses during heavy constant work-rate exercise

PURPOSE

At constant work-rates below the gas exchange threshold (VO(2 theta)), VO(2) normally achieves steady-state values within 3 min, whereas at heavier work-rates, VO(2) may continue to rise. The VO(2) response to heavy exercise can be described by a three-exponential model with the slow phase usually commencing 2-3 min after the onset of exercise. The aim of our study was to estimate precisely the VO(2), VCO(2), VE and f(C) required for above-VO(2 theta) exercise from the relationship of the specific variable to work-rate below VO(2 theta) and to compare this with the actual value achieved.

METHODS

Nine cyclists performed five constant work-rates of 8 min duration, four below VO(2 theta) (40, 80, 120, 160 W) and one midway between VO(2 theta) and VO(2max) (295 +/- 34 W). The VO(2), VCO(2), VE and f(C) were averaged for the final 2 min of each below-VO(2 theta) test and were found to be linear with respect to work-rate (average r2 >0.95). Variables for the above-VO(2 theta) work-rate were predicted by extrapolation and compared with the actual measured values at the end of the exercise bout.

RESULTS

VO(2) exceeded the predicted value by 0.48 +/- 0.21 L x min(-1) (12.4 +/- 5.1%), VCO(2) by 0.78 +/- 0.26 L x min(-1) (23.2 +/- 7.2%), VE by 40.3 +/- 16.3 L x min(-1) (51.0 +/- 23.1%), and f(C) by 12.2 +/- 12.5 beats x min(-1) (8.8 +/- 9.3%), all P < 0.0001 except f(C) P < 0.02, paired t-test. The point at which VO(2) during above-VO(2 theta) exercise exceeded the predicted value (145.7 +/- 64.9 s) agreed with the point at which the slow component of VO(2) began, as determined by nonlinear regression analysis (131.5 +/- 44.3 s, P = NS, ANOVA).

CONCLUSION

There is an excessive metabolic response to heavy exercise over and above that predicted by extrapolation from light-moderate exercise and this excess VO(2) approximates on average to the slow phase of a three-compartment exponential model.

Improving cycling performance: how should we spend our time and money

Cycling performance is dependent on physiological factors which influence mechanical power production and mechanical and environmental factors that affect power demand. The purpose of this review was to summarize these factors and to rank them in order of importance. We used a model by Martin et al. to express all performance changes as changes in 40 km time trial performance. We modelled the performance of riders with different ability ranging from novice to elite cyclists. Training is a first and most obvious way to improve power production and was predicted to have the potential to improve 40 km time trial performance by 1 to 10% (1 to 7 minutes). The model also predicts that altitude training per se can cause a further improvement of 23 to 34 seconds. Carbohydrate-electrolyte drinks may decrease 40 km time by 32 to 42 seconds. Relatively low doses of caffeine may improve 40 km time trial performance by 55 to 84 seconds. Another way of improving time trial performance is by reducing the power demand of riding at a certain velocity. Riding with hands on the brake hoods would improve aerodynamics and increase performance time by approximately 5 to 7 minutes and riding with hands on the handlebar drops would increase performance time by 2 to 3 minutes compared with a baseline position (elbows on time trail handle bars). Conversely, riding with a carefully optimised position could decrease performance time by 2 to 2.5 minutes. An aerodynamic frame saved the modelled riders 1:17 to 1:44 min:sec. Furthermore, compared with a conventional wheel set, an aerodynamic wheel set may improve time trial performance time by 60 to 82 seconds. From the analysis in this article it becomes clear that novice cyclists can benefit more from the suggested alterations in position, equipment, nutrition and training compared with elite cyclists. Training seems to be the most important factor, but sometimes large improvements can be made by relatively small changes in body position. More expensive options of performance improvement include altitude training and modifications of equipment (light and aerodynamic bicycle and wheels). Depending on the availability of time and financial resources cyclists have to make decisions about how to achieve their performance improvements. The data presented here may provide a guideline to help make such decisions.

Interval training for performance: a scientific and empirical practice. Special recommendations for middle- and long-distance running. Part I: aerobic interval training

This article traces the history of scientific and empirical interval training. Scientific research has shed some light on the choice of intensity, work duration and rest periods in so-called 'interval training'. Interval training involves repeated short to long bouts of rather high intensity exercise (equal or superior to maximal lactate steady-state velocity) interspersed with recovery periods (light exercise or rest). Interval training was first described by Reindell and Roskamm and was popularised in the 1950s by the Olympic champion, Emil Zatopek. Since then middle- and long- distance runners have used this technique to train at velocities close to their own specific competition velocity. In fact, trainers have used specific velocities from 800 to 5000m to calibrate interval training without taking into account physiological markers. However, outside of the competition season it seems better to refer to the velocities associated with particular physiological responses in the range from maximal lactate steady state to the absolute maximal velocity. The range of velocities used in a race must be taken into consideration, since even world records are not run at a constant pace.