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Relationship between heart rate and the running speed during the incremental test to determine V̇ O 2,max before and after 6 weeks training at MLSSv
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![Fig. 2 Graphical representation of the determination of [la − ] b at...](profile/Pierre-Marie-Lepretre/publication/8906006/figure/fig2/AS:349493292748812@1460337102935/Graphical-representation-of-the-determination-of-la-b-at-maximal-lactate-steady_Q320.jpg)
Training effects on time-to-exhaustion, substrate and blood lactate balances at the maximal lactate steady state velocity (MLSSv) were examined. Eleven male, veteran, long-distance runners performed three tests before and after 6 weeks of training at MLSSv: an incremental test to determine maximum O2 uptake (VO(2,max)) and the velocity at the lacta...
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Anaerobic threshold is widely used for diagnosis of swimming aerobic endurance but the precise incremental protocols step duration for its assessment is controversial. A physiological and biomechanical comparison between intermittent incremental protocols with different step lengths and a maximal lactate steady state (MLSS) test was conducted. 17 s...
Reports on reproducibility of lactate markers usually considered only two trials. The authors assessed reproducibility of power output at seven markers in 11 fit subjects over at least six trials under tightly controlled conditions. Subjects undertook incremental exercises (50 W start, +50 W every 3 min to exhaustion) on a cycle ergometer. At each...
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... Finally, performance can be influenced by PE, as discussed in Sect. 8. Nonetheless, empirical investigations consistently demonstrate associations between effort and performance [27][28][29][73][74][75]. Thus, performance can often serve as a reasonably accurate indicator of effort, allowing us to exploit this relationship with minimal drawbacks. ...
Effort and the perception of effort (PE) have been extensively studied across disciplines, resulting in multiple definitions. These inconsistencies block scientific progress by impeding effective communication between and within fields. Here, we present an integrated perspective of effort and PE that is applicable to both physical and cognitive activities. We define effort as the energy utilized to perform an action. This definition can be applied to biological entities performing various voluntary or involuntary activities, irrespective of whether the effort contributes to goal achievement. Then, we define PE as the instantaneous experience of utilizing energy to perform an action. This definition builds on that of effort without conflating it with other subjective experiences. We explore the nature of effort and PE as constructs and variables and highlight key considerations in their measurement. Our integrated perspective aims to facilitate a deeper understanding of these constructs, refine research methodologies, and promote interdisciplinary collaborations.
... Specifically, mostly strong associations have been observed between the manipulated proxies of effort of cognitive tasks and measured proxies of effort, including a range of cardiovascular responses [21,26,113,114] and brain glucose levels [34,35]. Similarly, the manipulated proxies of effort of physical tasks show associations with physiological measures such as heart rate, blood lactate levels, and ventilation and respiration rates [23][24][25]115]. These associations suggest that the more demanding the action, the greater the total investment of resources, consistent with our definition of effort. ...
Effort and the perception of effort have been extensively studied across multiple disciplines, resulting in disparate definitions across the literature. Inconsistencies in definitions impede scientific progress by blocking effective communication between and within disciplines. Here, we introduce a resource-based framework that comprehensively defines and connects effort and perception of effort, and provide a detailed analysis of these constructs. We define effort in a way that applies to all biological entities, voluntary and involuntary actions, and successful and unsuccessful actions. We define perception of effort such that it builds on our definition of effort without conflating it with other experiences. Our definition of perception of effort also aligns with various explanations regarding its proposed functions and mechanistic underpinnings. We explore the latent nature of these constructs, their employment as independent and dependent variables, and their associations. Our framework also seeks to bridge the gap between cognitive and physical effort and perception of effort, which have been primarily developed in isolation. We anticipate that our framework will facilitate a deeper understanding of these constructs, refine research methodologies and promote interdisciplinary collaborations.
... Our study also found that at high workloads (MLSSw), some group A athletes used a different pedaling technique in the ILT-test than in CP-tests (Figs 8 and 9, S9 Fig). The MLSSw is widely accepted as a precise and valid reference point to set training stimuli and to adjust the optimal workload during competition [24,51]. However, our data suggest non-fixed coordination patterns at higher workloads, which in turn can have a major impact on metabolism and neuromuscular adaptation mechanisms. ...
In cycling, propulsion is generated by the muscles of the lower limbs and hips. After the first reports of pedal/crank force measurements in the late 1960s, it has been assumed that highly trained athletes have better power transfer to the pedals than recreational cyclists. However, motor patterns indicating higher levels of performance are unknown. To compare leg muscle activation between trained (3.5–4.2 W/kgbw) and highly trained (4.3–5.1 W/kgbw) athletes we applied electromyography, lactate, and bi-pedal/crank force measurements during a maximal power test, an individual lactate threshold test and a constant power test. We show that specific activation patterns of the rectus femoris (RF) and vastus lateralis (VL) impact on individual performance during high-intensity cycling. In highly trained cyclists, we found a strong activation of the RF during hip flexion. This results in reduced negative force in the fourth quadrant of the pedal cycle. Furthermore, we discovered that pre-activation of the RF during hip flexion reduces force loss at the top dead center (TDC) and can improve force development during subsequent leg extension. Finally, we found that a higher performance level is associated with earlier and more intense coactivation of the RF and VL. This quadriceps femoris recruitment pattern improves force transmission and maintains propulsion at the TDC of the pedal cycle. Our results demonstrate neuromuscular adaptations in cycling that can be utilized to optimize training interventions in sports and rehabilitation.
... The BLC-relCHO explains metabolic FAO and CHO in relation to changes in lactate responses via BLC that do not rely solely on a single intensity such as Fatmax or COP, which addresses the limitation of a wide intensity range at MFO and related single point thresholds [34]. A major limitation in the previous indirect calorimetry-based markers is the adoption of a "fat-burning" model, which is only dependent on the amount of oxygen used at a given intensity and as such is limited in the heavy and severe exercise intensity domains, where elite endurance exercise is performed and high-intensity interval training is more effective for fat-loss and performance outcomes [6,11,35]. Instead, the present study proposes the use of kel as an independent evaluative predictor in human adults' reliance on CHO and FAO during exercise through providing a functional link between BLC, CHO and FAO. ...
... This is in line with a similar range of BLC levels of 1-2.2 mmol·L −1 reported in studies corresponding to a similarly wide range of exercise intensities at MFO of 30-75% . VO 2peak , [2,10,21,30,35]. However, kel does not rely on a fixed power, intensity end point to determine metabolic capacity, and hence it provides an independent predictor for the reliance on FAO, including MFO Fatmax or COP intensities. ...
(1) Background: Maximal fat oxidation (MFO), its associated exercise intensity (Fatmax) and the cross-over point (COP) are known indirect calorimetry-based diagnostics for whole-body metabolic health and exercise. However, large inter- and intra-individual variability in determining their corresponding intensity makes their use inconsistent, whether the intensity is based on power output or oxygen uptake. Blood lactate concentration (BLC) has often reflected a range in MFO and COP, which may offer another non-indirect calorimetry dimension based on the near equilibrium between lactate and pyruvate at the molecular level, which biochemically determines an interchange between lactate and relative rate of carbohydrate (relCHO) and relative rate of fat utilization (relFAO). This paper proposes a new testing approach describing relCHO as a function of BLC, with an individualized half-maximal activation constant of relCHO (kel), to explain and predict the variability in MFO, Fatmax and COP. (2) Methods: Following ethical approval, twenty-one healthy males participated in the incremental cardiorespiratory maximal test, and capillary BLC was measured. Indirect calorimetry relCHO and relFAO were calculated, and a constant kel that reflected 50% of CHO saturation level was estimated as a sigmoid function of BLC (mmol·L−1): relCHO = 100/(1 + kel/BLC2). (3) Results: 86% of relCHO variability was explained by BLC levels. The individualized kel estimations, which were 1.82 ± 0.95 (min/max 0.54/4.4) (mmol·L−1)2 independently explained 55% MFO and 44% of COP variabilities. Multiple regression analysis resulted in kel as the highest independent predictor of Fatmax (adjusted r-square = 22.3%, p < 0.05), whilst classic intensity-based predictors (peak power, maximal oxygen uptake, fixed BLC at 4 mmol·L−1) were not significant predictors. (4) Conclusions: The BLC-relCHO model, with its predictor kel explains the inter- and intra-individual variability in MFO, its exercise intensity Fatmax and power outs at COP through dynamic changes in BLC, fat and carbohydrates regardless of the intensity at which exercise takes place. kel capability as a predictor of MFO, Fatmax and COP independently of their associated intensities provides a new diagnostic tool in physiological exercise testing for health and exercise performance.
... In races of 10 km or more (but not over shorter distances), a significant correlation between running speed and AT has been demonstrated, especially in the group of older athletes (20). Therefore, training at the anaerobic threshold level induces a minimal increase in VO 2 max and in AT speed, but a significant increase in time to exhaustion at AT speed (21). This is probably due to better lactate clearance and improved performance. ...
... Das führt wiederum dazu, dass ausdauertrainierte Sportler an der individuellen anaeroben Schwelle eine höhere Leistung oder Laufgeschwindigkeit erbringen können (Carter et al., 1999;Weltman et al., 1992). Bereits kurzzeitige Ausdauertrainingsprogramme von sechs bis acht Wochen konnten Verbesserungen von 4 bis 8 % am maximalen Laktat-Steady-State hervorrufen (Leistung oder Sauerstoffaufnahme). Diese Effekte konnten sowohl bei gut ausdauertrainierten Alterklassensportlern (Billat et al., 2004) als auch mäßig trainierten Läufern (Philp et al., 2008) festgestellt werden. Eine Studie von MacRae et al. (1992) hat gezeigt, dass die geringeren Blutlaktatkonzentrationen bei Trainierten hauptsächlich mit einer besseren Verwertung des Blutlaktats zusammenhängt und nicht durch eine verringerte Laktatproduktion bedingt wird. ...
High-intensity interval training, characterized by repetitive short to long bouts of high-intensity exercise separated by recovery periods, represents a time-efficient training methodology for improving athlete performance. Previous research indicates that physiological and anatomical differences in men and women may result in divergences in training response. Furthermore, the state of research suggests that changes in skeletal muscle and different functional systems over the course of age may induce different responses to an exercise stimulus. In this regard, the results show that there is a sexual dimorphism in load and recovery during interval exercise. Furthermore, it was found that good trainability is possible in old age, which in turn may counteract age-related changes and their influence on load and recovery behavior.
... The speed increased automatically until the individual reported inability to continue (voluntary exhaustion) or presented uncoordinated disability to perform the test. To the test be considered maximum, it was necessary to meet at least 3 of 4 criteria: RER >1.05, HRmax ≥ 90%, voluntary exhaustion, and VO2max plateau or peak 19 . A metabolic gas analyzer (Cortex Metalyzer 3B, Germany) was used, with breath-by-breath collection and calibration with ambient and known gases (11.97% ...
We aimed to analyze the influence of cardiorespiratory fitness (CRF) on ventilatory threshold identification (VT1) using the Ventilatory Equivalents (VEq) and V-slope methods. Twenty-two male runners (32.9 ± 9.4 years) were divided into two groups: G1 - group with less cardiorespiratory fitness (CRF: VO2max 40 to 51 ml·kg-1·min-1) and G2 - higher CRF (G1; VO2max £56,4 to 72 ml·kg-1·min-1) divided by the 50th percentile. An incremental cardiopulmonary exercise test was applied to identify VT1 using VEq and V-slope methods to compare heart rate (HR), oxygen consumption (VO2), and speed. Two-way ANOVA was used to compare HR, VO2, and speed (groups vs. methods). The Effect size was calculated using Cohen’s d. The intraclass correlation coefficient, variation coefficient, typical error, and Bland Altman were applied to verify reliability and agreement. No significant differences (p < 0.05) were found between methods for G1 (VO2, HR, and speed), and Bland Altman showed good agreement (mean difference: VO2 0.35ml·kg-1·min-1; HR 2.58bpm; speed 0.33km·h-1). However, G2 presented statistical differences between methods (VO2 and speed) and a more significant mean difference (VO2 2.68ml·kg-1·min-1; HR 6.87 bpm; speed 0.88km·h-1). The small effect size was found in G1 between methods (VO2: 0.06; speed: 0.20; HR: 0.14), and small and moderate effects were found in G2 between methods (VO2: 0.39; speed: 0.43; HR: 0.51). In conclusion, runners with lower CRF have a better agreement for the V-slope and VEq methods than those with a higher CRF.
... In accordance with Seifert et al. (2010a), we hypothesize that long-distance trained swimmers, and likely endurance athletes with comparable racing times, have a higher fatigue resistance in the supra-threshold range due to improvements in technique and metabolism. Training intensity/duration adjustment in moderate to severe domains of exercise will trigger neuromuscular adaptations (Dudley et al., 1982;Dubouchaud et al., 2000;Messonnier et al., 2013;Figueiredo et al., 2014;de Araujo et al., 2015), which most likely manifest in a higher MLSS W (Billat et al., 2004;Philp et al., 2008). Such a higher fatigue resistance in the supra-threshold range can facilitate economic movement over longer periods of time. ...
The lactate threshold (LT) and the strongly related maximal lactate steady state workload (MLSSW) are critical for physical endurance capacity and therefore of major interest in numerous sports. However, their relevance to individual swimming performance is not well understood. We used a custom-made visual light pacer for real-time speed modulation during front crawl to determine the LT and MLSSW in a single-exercise test. When approaching the LT, we found that minute variations in swimming speed had considerable effects on blood lactate concentration ([La⁻]). The LT was characterized by a sudden increase in [La⁻], while the MLSSW occurred after a subsequent workload reduction, as indicated by a rapid cessation of blood lactate accumulation. Determination of the MLSSW by this so-called “individual lactate threshold” (ILT)-test was highly reproducible and valid in a constant speed test. Mean swimming speed in 800 and 1,500 m competition (S-Comp) was 3.4% above MLSSW level and S-Comp, and the difference between S-Comp and the MLSSW (Δ S-Comp/MLSSW) were higher for long-distance swimmers (800–1,500 m) than for short- and middle-distance swimmers (50–400 m). Moreover, Δ S-Comp/MLSSW varied significantly between subjects and had a strong influence on overall swimming performance. Our results demonstrate that the MLSSW determines individual swimming performance, reflects endurance capacity in the sub- to supra-threshold range, and is therefore appropriate to adjust training intensity in moderate to severe domains of exercise.
... The blood lactate concentration during heavy exercise increases above baseline and then attains a steady state. In contrast, the blood lactate during severe exercise continues to rise above baseline with an absence of a steady state A potential advantage of using the domains of exercise to determine exercise intensity is that although training status influences exercise tolerance at a given intensity [92], overall muscle glycogen content [93], discrete V O 2 patterns (e.g., the phase II time constant) [94,95], and intramuscular lactate oxidation [55,96], these factors have little effect on V O 2 and blood lactate kinetic responses during exercise in healthy individuals [97][98][99][100]. This suggests that determining exercise intensity based on these distinct and homogeneous homeostatic perturbations (i.e., systemic responses such as oxygen uptake kinetics and blood lactate responses) could be an effective method to normalise exercise intensity between individuals. ...
Prescribing the frequency, duration, or volume of training is simple as these factors can be altered by manipulating the number of exercise sessions per week, the duration of each session, or the total work performed in a given time frame (e.g., per week). However, prescribing exercise intensity is complex and controversy exists regarding the reliability and validity of the methods used to determine and prescribe intensity. This controversy arises from the absence of an agreed framework for assessing the construct validity of different methods used to determine exercise intensity. In this review, we have evaluated the construct validity of different methods for prescribing exercise intensity based on their ability to provoke homeostatic disturbances (e.g., changes in oxygen uptake kinetics and blood lactate) consistent with the moderate, heavy, and severe domains of exercise. Methods for prescribing exercise intensity include a percentage of anchor measurements, such as maximal oxygen uptake (\({\dot{\text{V}}\text{O}}_{{{\text{2max}}}}\)), peak oxygen uptake (\({\dot{\text{V}}\text{O}}_{{{\text{2peak}}}}\)), maximum heart rate (HRmax), and maximum work rate (i.e., power or velocity—\({\dot{\text{W}}}_{{\max}}\) or \({\dot{\text{V}}}_{{\max}}\), respectively), derived from a graded exercise test (GXT). However, despite their common use, it is apparent that prescribing exercise intensity based on a fixed percentage of these maximal anchors has little merit for eliciting distinct or domain-specific homeostatic perturbations. Some have advocated using submaximal anchors, including the ventilatory threshold (VT), the gas exchange threshold (GET), the respiratory compensation point (RCP), the first and second lactate threshold (LT1 and LT2), the maximal lactate steady state (MLSS), critical power (CP), and critical speed (CS). There is some evidence to support the validity of LT1, GET, and VT to delineate the moderate and heavy domains of exercise. However, there is little evidence to support the validity of most commonly used methods, with exception of CP and CS, to delineate the heavy and severe domains of exercise. As acute responses to exercise are not always predictive of chronic adaptations, training studies are required to verify whether different methods to prescribe exercise will affect adaptations to training. Better ways to prescribe exercise intensity should help sport scientists, researchers, clinicians, and coaches to design more effective training programs to achieve greater improvements in health and athletic performance.
... The high training intensity and subsequent improvements in V O 2 peak of the present study concur with previous work suggesting significant increases in oxidative capacity occur as a result of training intensities at ≥85% of V O 2max (Bickham & Le Rossignol, 2004;Billat & Paiva, 2002;Billat, Sirvent, Lepretre, & Koralsztein, 2004;Dudley et al., 1982;Fox et al., 1973;Hickson et al., 1977). These improvements have been linked to increased recruitment of Type 11a and 11x fiber types at this training intensity, compared to lower training intensities (Dudley et al., 1982;Fox et al., 1973;Hickson et al., 1977). ...
Purpose and Methods: To compare the effects of a set of 12–30 min, maximal effort, constant load cycle bouts (HICT) to 12 short work: shorter rest (10 s: 5 s) interval sessions (INT) of similar duration and effort, performed on alternate days over 4 weeks, on performance and V̇O2 l.min⁻¹. INT sessions consisted of repeated cycles of 10 s work followed by 5 s of recovery for 30 min. Fourteen male athletes (83 kg ± 6, 24year ± 2) were randomly assigned to HICT (n = 7) or INT (n = 7) training. Pre- and post-power output (PO), V̇O2 and V̇O2peak, during 60s, 3 min, and ramp (RAMP) tests were collected Results: Between group comparisons showed increased mean PO, pre- to post-INT training (p = .026) over the last min of the 3-min test whereas PO post-HICT training declined. INT showed greater training effects on the 60 s test than HCIT (INT 506 ± 45 to 535 ± 55 W; p = .002, Cd = .57; HCIT 513 ± 78 to 548 ± 83 W; p = .02, Cd = 27). RAMP peak PO and V̇O2peak increased within both groups (INT 341 ± 63 to 370 ± 48 W, p = .002, Cd = 0.52; HICT 332 ± 45 to 353 ± 44 W, p = .006, Cd = .53; 3.73 ± 0.68 to 4.06 ± 0.63 L·min⁻¹, p = .001, Cd = .50; 3.75 ± 0.62 to 4.09 ± 0.52 L·min⁻¹, p = .002, Cd = .59). Conclusion(s): These results show that utilizing this novel short work: shorter rest (10 s: 5 s) interval training paradigm will elicit better performances in moderate duration performances compared to continuous training of the same duration, effort, and frequency.
