The oxygen uptake (VCombining Dot AboveO2) at the respiratory compensation point (RCP) closely identifies with the maximal metabolic steady state. However, the power output (PO) at RCP cannot be ...determined from contemporary ramp-incremental exercise protocols.
PURPOSEThis study aimed to test the efficacy of a “step–ramp–step” (SRS) cycling protocol for estimating the PO at RCP and the validity of RCP as a maximal metabolic steady-state surrogate.
METHODSTen heathy volunteers (5 women; age30 ± 7 yr; VCombining Dot AboveO2max54 ± 6 mL·kg·min) performed in the following seriesa moderate step transition to 100 W (MOD), ramp (30 W·min), and after 30 min of recovery, step transition to ~50% POpeak (HVY). Ventilatory and gas exchange data from the ramp were used to identify the VCombining Dot AboveO2 at lactate threshold (LT) and RCP. The PO at LT was determined by the linear regression of the VCombining Dot AboveO2 versus PO relationship after adjusting ramp data by the difference between the ramp PO at the steady-state VCombining Dot AboveO2 from MOD and 100 W. Linear regression between the VCombining Dot AboveO2–PO values associated with LT and HVY provided, by extrapolation, the PO at RCP. Participants then performed 30-min constant-power tests at the SRS-estimated RCP and 5% above this PO.
RESULTSAll participants completed 30 min of constant-power exercise at the SRS-estimated RCP achieving steady-state VCombining Dot AboveO2 of 3176 ± 595 mL·min that was not different (P = 0.80) from the ramp-identified RCP (3095 ± 570 mL·min) and highly consistent within participants (bias = −26 mL·min, r = 0.97, coefficient of variation = 2.3% ± 2.8%). At 5% above the SRS-estimated RCP, four participants could not complete 30 min and all, but two exhibited non–steady-state responses in blood lactate and VCombining Dot AboveO2.
CONCLUSIONSIn healthy individuals cycling at their preferred cadence, the SRS protocol and the RCP are capable of accurately predicting the PO associated with maximal metabolic steady state.
Together with other physiological responses, the neuromuscular fatigue mechanisms, and related perceptual responses, accompanying task failure are suggested to be dependent on the intensity domain ...within which exercise is sustained. Here, we show that peripheral fatigue demonstrates a high domain specificity, whereas such specificity is absent for central fatigue. Sensations of fatigue, pain, and breathlessness demonstrated intensity domain specificity and might have contributed to reaching maximal levels of RPE and, thus, task failure.
A comprehensive characterization of neuromuscular and perceptual mechanisms of fatigue at task failure following exercise across the entire intensity spectrum is lacking. This study evaluated the extent of peripheral and central fatigue, and corresponding perceptual attributes, at task failure following cycling within the moderate-(MOD), heavy-(HVY), severe-(SVR), and extreme-(EXT) intensity domains. After a ramp-incremental test, 11 young males performed four constant-power output trials to the limit of tolerance (T
lim
) at 4 distinct domain-specific workloads. These trials were preceded and followed by 5-s knee-extension maximal voluntary contractions (MVCs) and femoral nerve electrical stimuli to quantify peripheral and central fatigue. In addition, perceptual measures including ratings of global fatigue, legs pain, dyspnea, and perceived effort (RPE) were also collected. At T
lim
, reductions in MVC were independent of intensity ( P > 0.05). However, peripheral fatigue was greater following EXT and SVR and progressively, but distinctively, lower following HVY and MOD ( P < 0.05). Central fatigue was similar after SVR, HVY, and MOD, but absent after EXT ( P < 0.05). At T
lim
, subjective ratings of global fatigue were progressively higher with lower exercise intensities, whereas ratings of legs pain and dyspnea were progressively higher with higher exercise intensities. On the other hand, RPE was maximal following HVY, SVR, and EXT, but not MOD. The findings demonstrate that at T
lim
, the extent of peripheral fatigue is highly domain-specific, whereas the extent of central fatigue is not. Sensations such as fatigue, pain, and dyspnea may integrate with mechanisms of sense of effort to determine task failure in a manner specific to each intensity domain.
NEW & NOTEWORTHY Together with other physiological responses, the neuromuscular fatigue mechanisms, and related perceptual responses, accompanying task failure are suggested to be dependent on the intensity domain within which exercise is sustained. Here, we show that peripheral fatigue demonstrates a high domain specificity, whereas such specificity is absent for central fatigue. Sensations of fatigue, pain, and breathlessness demonstrated intensity domain specificity and might have contributed to reaching maximal levels of RPE and, thus, task failure.
The metabolic rate (VO
2
) at the maximal metabolic steady state (MMSS) is generally not different from the VO
2
at the respiratory compensation point (RCP). Based on this, it is often assumed that ...the heart rate (HR) at RCP would also be similar to that at MMSS. The study aims to compare the HR at RCP with that at MMSS. Seventeen individuals completed a ramp-incremental test, a series of severe-intensity trials to estimate critical power and two-to-three 30-min trials to confirm MMSS. The HR at RCP was retrieved by linear interpolation of the ramp-VO
2
/HR relationship and compared to the HR at MMSS recorded at 10, 15, 20, 25 and 30 min. The HR at RCP was 166 ± 12 bpm. The HR during MMSS at the timepoints of interest was 168 ± 8, 171 ± 8, 175 ± 9, 177 ± 9 and 178 ± 10 bpm. The HR at RCP was not different from the HR at MMSS at 10 min (P > 0.05) but lower at subsequent timepoints (P < 0.05) with this difference becoming progressively larger. For all timepoints, limits of agreement were large (~30 bpm). Given these differences and the variability at the individual level, the HR at RCP cannot be used to control the metabolic stimulus of endurance exercise.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
A variety of health benefits associated with physical activity depends upon the frequency, intensity, duration, and type of exercise. Intensity of exercise is the most elusive of these elements and ...yet has important implications for the health benefits and particularly cardiovascular outcomes elicited by regular physical activity. Authorities recommend that we obtain 150min of moderate to vigorous intensity physical activity (MVPA) each week. The current descriptions of moderate to vigorous intensity are not sufficient, and we wish to enhance understanding of MVPA by recognition of important boundaries that define these intensities. There are two key thresholds identified in incremental tests: ventilatory and lactate thresholds 1 and 2, which reflect boundaries related to individualized disturbance to homeostasis that are appropriate for prescribing exercise. VT2 and LT2 correspond with critical power/speed and respiratory compensation point. Moderate intensity physical activity approaches VT1 and LT1 and vigorous intensity physical activity is between the two thresholds (1 and 2). The common practice of prescribing exercise at a fixed metabolic rate (# of METs) or percentage of maximal heart rate or of maximal oxygen uptake (V̇O
2
max) does not acknowledge the individual variability of these metabolic boundaries. As training adaptations occur, these boundaries will change in absolute and relative terms. Reassessment is necessary to maintain regular exercise in the moderate to vigorous intensity domains. Future research should consider using these metabolic boundaries for exercise prescription, so we will gain a better understanding of the specific physical activity induced health benefits.
Common methods to prescribe exercise intensity are based on fixed percentages of maximum rate of oxygen uptake (V˙O2max), peak work rate (WRpeak), maximal HR (HRmax). However, it is unknown how these ...methods compare to the current models to partition the exercise intensity spectrum.
PURPOSEThus, the aim of this study was to compare contemporary gold-standard approaches for exercise prescription based on fixed percentages of maximum values to the well-established, but underutilized, “domain” schema of exercise intensity.
METHODSOne hundred individuals participated in the study (women, 46; men, 54). A cardiopulmonary ramp-incremental test was performed to assess V˙O2max, WRpeak, HRmax, and the lactate threshold (LT), and submaximal constant-work rate trials of 30-min duration to determine the maximal lactate steady-state (MLSS). The LT and MLSS were used to partition the intensity spectrum for each individual in three domains of intensitymoderate, heavy, and severe.
RESULTSV˙O2max in women and men was 3.06 ± 0.41 L·min and 4.10 ± 0.56 L·min, respectively. Lactate threshold and MLSS occurred at a greater %V˙O2max and %HRmax in women compared with men (P < 0.05). The large ranges in both sexes at which LT and MLSS occurred on the basis of %V˙O2max (LT, 45%–74%; MLSS, 69%–96%), %WRpeak (LT, 23%–57%; MLSS, 44%–71%), and %HRmax (LT, 60%–90%; MLSS, 75%–97%) elicited large variability in the number of individuals distributed in each domain at the fixed-percentages examined.
CONCLUSIONSContemporary gold-standard methods for exercise prescription based on fixed-percentages of maximum values conform poorly to exercise intensity domains and thus do not adequately control the metabolic stimulus.
Reactive hyperemia (RH) is widely used for the investigation of macrovascular (flow-mediated dilation, or FMD) and microvascular (near-infrared spectroscopy-vascular occlusion test, or NIRS-VOT) ...function. Mixed results have been reported on fitness level- and sex-related differences in FMD outcomes, and little is known about microvascular differences in untrained and chronically trained males and females.
Fifteen chronically trained (CT: 8 males, 7 females) and 16 untrained (UT: 8 males, 8 females) individuals participated in this study. Aerobic fitness (V˙O2max) was assessed during a cycling incremental exercise test to volitional exhaustion. FMD and NIRS-VOT were performed simultaneously on the lower limb investigating superficial femoral artery and vastus lateralis muscle, respectively.
%FMD was not different between groups (CT males, 4.62 ± 1.42; CT females, 4.15 ± 2.23; UT males, 5.10 ± 2.53; CT females, 3.20 ± 1.67). Peak blood flow showed greater values in CT versus UT (P ≤ 0.0001) and males versus females (P = 0.032). RH blood flow area under the curve was greater in CT versus UT (P = 0.001). At the microvascular level, desaturation and reperfusion rates were faster in CT versus UT (P = 0.018 and P = 0.013) and males versus females (P = 0.011 and P = 0.005). V˙O2max was significantly correlated with reperfusion rate (P = 0.0005) but not with %FMD.
Whereas NIRS-VOT outcomes identified fitness- and sex-related differences in vascular responses, %FMD did not. However, when RH-related outcomes from the FMD analysis were considered, fitness- and/or sex-related differences were detected. These data highlight the importance of integrating FMD and NIRS-VOT outcomes for a more comprehensive evaluation of vascular function.
This study aimed to compare the concordance between CP and MLSS estimated by various models and criteria and their agreement with MMSS.
After a ramp test, 10 recreationally active males performed ...four to five severe-intensity constant-power output (PO) trials to estimate CP and three to four constant-PO trials to determine MLSS and identify MMSS. CP was computed using the three-parameter hyperbolic (CP3-hyp), two-parameter hyperbolic (CP2-hyp), linear (CPlin), and inverse of time (CP1/Tlim) models. In addition, the model with the lowest combined parameter error identified the "best-fit" CP (CPbest-fit). MLSS was determined as an increase in blood lactate concentration ≤1 mM during constant-PO cycling from the 5th (MLSS5-30), 10th (MLSS10-30), 15th (MLSS15-30), 20th (MLSS20-30), or 25th (MLSS25-30) to 30th minute. MMSS was identified as the greatest PO associated with the highest submaximal steady-state V˙O2 (MV˙O2ss).
Concordance between the various CP and MLSS estimates was greatest when MLSS was identified as MLSS15-30, MLSS20-30, and MLSS25-30. The PO at MV˙O2ss was 243 ± 43 W. Of the various CP models and MLSS criteria, CP2-hyp (244 ± 46 W) and CPlin (248 ± 46 W) and MLSS15-30 and MLSS20-30 (both 245 ± 46 W), respectively, displayed, on average, the greatest agreement with MV˙O2ss. Nevertheless, all CP models and MLSS criteria demonstrated some degree of inaccuracies with respect to MV˙O2ss.
Differences between CP and MLSS can be reconciled with optimal methods of determination. When estimating MMSS, from CP the error margin of the model estimate should be considered. For MLSS, MLSS15-30 and MLSS20-30 demonstrated the highest degree of accuracy.
Purpose
Different strategies for near-infrared spectroscopy (NIRS)-derived muscle oxidative capacity assessment have been reported. This study compared and evaluated (I) approaches for averaging ...trials; (II) NIRS signals and blood volume correction equations; (III) the assessment of vastus lateralis (VL) and tibialis anterior (TA) muscles in two fitness levels groups.
Methods
Thirty-six participants 18 chronically trained (CT: 14 males, 4 females) and 18 untrained (UT: 10 males, 8 females) participated in this study. Two trials of twenty transient arterial occlusions were performed for NIRS-derived muscle oxidative capacity assessment. Muscle oxygen consumption (
V
˙
O
2
m
) was estimated from deoxygenated hemoglobin (HHb), corrected for blood volume changes following Ryan (HHbR) and Beever (HHbB) equations, and from oxygen saturation (StO
2
) in VL and TA.
Results
Superimposing or averaging
V
˙
O
2
m
or averaging the rate constants (
k
) from the two trials resulted in equivalent
k
values two one-sided tests (TOST) procedure with 5% equivalence margin—
P
< 0.001. Whereas HHbR (2.35 ± 0.61 min
−1
) and HHbB (2.34 ± 0.58 min
−1
) derived
k
were equivalent (
P
< 0.001), StO
2
derived
k
(2.81 ± 0.92 min
−1
) was greater (
P
< 0.001) than both.
k
values were greater in CT
vs
UT in both muscles (VL: + 0.68 min
−1
,
P
= 0.002; TA: + 0.43 min
−1
,
P
= 0.01).
Conclusion
Different approaches for averaging trials lead to similar
k
. HHb and StO
2
signals provided different
k
, although different blood volume corrections did not impact
k
. Group differences in
k
were detected in both muscles.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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