European Journal of Applied Physiology

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Participant flow diagram
A Study design. B Neuromuscular testing protocol. White rectangles represent the warm-up performed with both plantar flexors and handgrip muscles. Black figures represent contractions performed with plantar flexors. Grey figures represent contractions performed with handgrip
Data obtained from a single participant performing maximal voluntary contractions before and after consuming each supplement
Total torque-integral individual values after supplement consumption. CON Control supplement, ZE Zein, LAC α-Lactalbumin supplement. Grey and coloured circles indicate individual data. Black dots and line indicate mean ± 95% confidence interval lower and upper limits. *Significant difference with Control (p < 0.01), # significant difference with Zein (p = 0.01)
Total torque-integral traces obtained from a single participant performing the fatigue protocol after consuming each supplement. Dotted line represents the 60% intensity for each session
  • Karen Mackay-PhillipsKaren Mackay-Phillips
  • Lucas B. R. OrssattoLucas B. R. Orssatto
  • Remco PolmanRemco Polman
  • [...]
  • Gabriel S. TrajanoGabriel S. Trajano
Purpose The neurotransmitter serotonin has a strong effect on behaviour and motor control. Regarding motor control, serotonin contributes to the development of fatigue and is also involved in the ability of motor neurones to operate across a large range of forces (gain control). The consumption of tryptophan-rich supplements (such as α-lactalbumin) is of interest because this amino acid is the only precursor for brain serotonin synthesis. Therefore, the purpose of this study was to determine the effects of α-lactalbumin supplementation on neuromuscular performance. Methods Using a randomised double-blind cross-over design, 16 healthy participants performed plantar flexor and handgrip maximal voluntary contractions, a 30-s submaximal handgrip contraction, and a plantar flexor fatigue protocol before and 90 min after consuming either 40 g of α-lactalbumin, an isonitrogenous beverage (Zein) or an isocaloric beverage (corn-starch). Sleepiness, mood, and cognition were assessed to evaluate any psychological effects. Results α-Lactalbumin decreased force steadiness by 25% during the sustained submaximal handgrip contraction (p < 0.01) and induced greater fatigue (15% reduction in total torque–time integral, p = 0.01) during the fatigue protocol. These effects were not observed for the other control beverages. No effects were found for maximal or explosive strength, or psychological measurements. Conclusions 40 g of α-lactalbumin increased handgrip force variability and reduced performance during fatiguing muscle contractions but did not influence brief maximal contractions or psychological parameters in healthy individuals. These findings support the hypothesis that the consumption of α-lactalbumin can increase motor neurone input–output gain and exacerbate central fatigue during sustained maximal exercise.
Study design (A) and neuromuscular testing protocol (B). Black figures represent contractions performed with plantar flexors. Grey figures represent contractions performed with handgrip. MVC: maximal voluntary contraction
Data obtained from a single participant during a triangle-shaped contraction before and after performing the handgrip contraction. A Torque traces obtained during the triangle contractions up to 20% of their maximal torque. B Participant’s test unit (in blue) with their 5th polynomial fit. C Participant’s control unit (in red) with their 5th polynomial fit. Grey shaded areas represent the ΔF amplitude for the participant
ΔF (A) and peak discharge rate (B) before and after handgrip contraction. Values obtained from 123 test motor units from participants (N = 10) on soleus muscle using the pairwise motor unit method. Both ΔF and discharge rate was increased in soleus after submaximal handgrip contraction. Each coloured dot indicates individual motor unit data. Black lines indicate mean ± 95% confidence interval lower and upper limits. pps peaks per second. *p < 0.01
  • Karen Mackay PhillipsKaren Mackay Phillips
  • Lucas B. R. OrssattoLucas B. R. Orssatto
  • Remco PolmanRemco Polman
  • [...]
  • Gabriel S. TrajanoGabriel S. Trajano
Introduction We tested two strategies that hypothetically increase serotonin availability (α-lactalbumin consumption and a remote submaximal handgrip contraction) on estimates of persistent inward currents (PICs) amplitude of soleus muscle in healthy participants. Methods With a randomised, double-blind, and cross-over design, 13 healthy participants performed triangular-shaped ramp contractions with their plantar flexors (20% of maximal torque), followed by a 30-s handgrip sustained contraction (40% of maximal force) and consecutive repeated triangular-shaped contractions. This was performed before and after the consumption of either 40 g of α-lactalbumin, an isonitrogenous beverage (Zein) or an isocaloric beverage (Corn-starch). Soleus motor units discharge rates were analysed from high-density surface electromyography signals. PICs were estimated by calculating the delta frequency (ΔF) of motor unit train spikes using the paired motor unit technique. Results ΔF (0.19 pps; p = 0.001; d = 0.30) and peak discharge rate (0.20 pps; p < 0.001; d = 0.37) increased after the handgrip contraction, irrespective of the consumed supplement. No effects of α-lactalbumin were observed. Conclusions Our results indicate that 40 g of α-lactalbumin was unable to modify intrinsic motoneuron excitability. However, performing a submaximal handgrip contraction before the plantar flexion triangular contraction was capable of increasing ΔF and discharge rates on soleus motor units. These findings highlight the diffused effects of serotonergic input, its effects on motoneuron discharge behaviour, and suggest a cross-effector effect within human motoneurons.
Representation of study protocols. Legend: # denotes affect and self-efficacy measurements
Mean ± SD across all three condition experimental visits in time-lapsed changes in W at each 5-min TZ and overall, during the 30-min fixed effort cycling exercise. Legend: * denotes a significant difference in overall values between conditions (P < .05), § denotes a moderate effect size
Mean ± SD across all three condition experimental visits in time-lapsed changes in cardiorespiratory parameters (a = HR, b = V̇⁻¹, c = V̇E, d = BF) at each five-minute TZ and overall, during the 30-min fixed effort cycling exercise. Legend: * denotes a significant difference in overall values between conditions (P < .05), § denotes a moderate effect size, and Ψ denotes a large effect size
Mean ± SD across all three condition experimental visits in time-lapsed changes in [La⁻]b at each 5-min timepoint and overall, during the 30-min fixed effort cycling exercise. Legend: * denotes a significant difference in overall values between conditions (P < .05), § denotes a moderate effect size, and Ψ denotes a large effect size
Mean ± SD across all three condition experimental visits in time-lapsed changes in psychological parameters: a = affective valence, b = self-efficacy at each 5-min timepoint and overall, during the 30-min fixed effort cycling exercise. Legend: * denotes a significant difference in overall values between conditions (P < .05), § denotes a moderate effect size, and Ψ denotes a large effect size
Purpose Using exercise protocols at a fixed rating of perceived effort (RPE) is a useful method for exploring the psychophysical influences on exercise performance. However, studies that have employed this protocol have arbitrarily selected RPE values without considering how these values correspond to exercise intensity thresholds and domains. Therefore, aligning RPE intensities with established physiological thresholds seems more appropriate, although the reliability of this method has not been assessed. Methods Eight recreationally active cyclists completed two identical ramped incremental trials on a cycle ergometer to identify gas exchange threshold (GET). A linear regression model plotted RPE responses during this test alongside gas parameters to establish an RPE corresponding to GET (RPE GET ) and 15% above GET (RPE +15%GET ). Participants then completed three trials at each intensity, in which performance, physiological, and psychological measures were averaged into 5-min time zone (TZ) intervals and 30-min ‘overall’ averages. Data were assessed for reliability using intraclass correlation coefficients (ICC) and accompanying standard error measurements (SEM), 95% confidence intervals, and coefficient of variations (CoV). Results All performance and gas parameters showed excellent levels of test–retest reliability (ICCs = > .900) across both intensities. Performance, gas-related measures, and heart rate averaged over the entire 30-min exercise demonstrated good intra-individual reliability (CoV = < 5%). Conclusion Recreationally active cyclists can reliably replicate fixed perceived effort exercise across multiple visits when RPE is aligned to physiological thresholds. Some evidence suggests that exercise at RPE +15%GET is more reliable than RPE GET .
Participant CONSORT flow diagram
Differences in lactate progression pre-and post-exercise until 10 min post-intervention. Data are displayed as mean and 95% confidence interval. a Vigorous-intensity intervention on the treadmill, b moderate-intensity intervention with individual selected speed on flat ground
Differences in miRNA expression pre- and post-training. Data are displayed as mean and 95% confidence intervals. a Vigorous-intensity training. b Moderate-intensity training
Background Walking is the preferred therapy for peripheral arterial disease in early stage. An effect of walking exercise is the increase of blood flow and fluid shear stress, leading, triggered by arteriogenesis, to the formation of collateral blood vessels. Circulating micro-RNA may act as an important information transmitter in this process. We investigated the acute effects of a single bout of 1) aerobic walking with moderate intensity; and 2) anaerobic walking with vigorous intensity on miRNA parameters related to vascular collateral formation. Methods Ten (10) patients with peripheral arterial disease with claudication (age 72 ± 7 years) participated in this two-armed, randomized-balanced cross-over study. The intervention arms were single bouts of supervised walking training at (1) vigorous intensity on a treadmill up to volitional exhaustion and (2) moderate intensity with individual selected speed for a duration of 20 min. One week of washout was maintained between the arms. During each intervention, heart rate was continuously monitored. Acute effects on circulating miRNAs and lactate concentration were determined using pre- and post-intervention measurement comparisons. Results Vigorous-intensity walking resulted in a higher heart rate (125 ± 21 bpm) than the moderate-intensity intervention (88 ± 9 bpm) (p < 0.05). Lactate concentration was increased after vigorous-intensity walking (p = 0.005; 3.3 ± 1.2 mmol/l), but not after moderate exercising (p > 0.05; 1.7 ± 0.6 mmol/l). The circulating levels of miR-142-5p and miR-424-5p were up-regulated after moderate-intensity (p < 0.05), but not after vigorous-intensity training (p > 0.05). Conclusion Moderate-intensity walking seems to be more feasible than vigorous exercises to induce changes of blood flow and endurance training-related miRNAs in patients with peripheral arterial disease. Our data thus indicates that effect mechanisms might follow an optimal rather than a maximal dose response relation. Steady state walking without the necessity to reach exhaustion seems to be better suited as stimulus.
Schematic representation of electrode positioning used for data acquisition for all three muscles of the triceps surae (GM gastrocnemius medialis, GL gastrocnemius lateralis and SOL soleus. One electrode was placed over GM, one electrode over GL, and two electrodes over SOL, one medially and one laterally to the Achilles tendon
Motor unit mean discharge rate of soleus during 10 and 20% peak isometric contraction. Each dot represents a single motor unit data point, coloured by participants. Mean and 95% confidence interval are offset to the left to facilitate visualisation. pps pulse per second
Motor unit mean discharge rate of gastrocnemius medialis during 10 and 20% peak isometric contraction. Each dot represents a single motor unit data point, coloured by participants. Mean and 95% confidence interval are offset to the left to facilitate visualisation. pps pulse per second
Motor unit mean discharge rate of gastrocnemius lateralis during 10 and 20% peak isometric contraction. Each dot represents a single motor unit data point, coloured by participants. Mean and 95% confidence interval are offset to the left, to facilitate visualisation. pps pulse per second
Objectives Deficits in muscle performance could be a consequence of a reduced ability of a motor neuron to increase the rate in which it discharges. This study aimed to investigate motor unit (MU) discharge properties of each triceps surae muscle (TS) and TS torque steadiness during submaximal intensities in runners with Achilles tendinopathy (AT). Methods We recruited runners with (n = 12) and without (n = 13) mid-portion AT. MU discharge rate was analysed for each of the TS muscles, using high-density surface electromyography during 10 and 20% isometric plantar flexor contractions. Results MU mean discharge rate was lower in the gastrocnemius lateralis (GL) in AT compared to controls. In AT, GL MU mean discharge rate did not increase as torque increased from 10% peak torque, 8.24 pps (95% CI 7.08 to 9.41) to 20%, 8.52 pps (7.41 to 9.63, p = 0.540); however, in controls, MU discharge rate increased as torque increased from 10%, 8.39 pps (7.25–9.53) to 20%, 10.07 pps (8.89–11.25, p < 0.001). There were no between-group difference in gastrocnemius medialis (GM) or soleus (SOL) MU discharge rates. We found no between-group differences in coefficient of variation of MU discharge rate in any of the TS muscles nor in TS torque steadiness. Conclusion Our data demonstrate that runners with AT may have a lower neural drive to GL, failing to increase MU discharge rate to adjust for the increase in torque demand. Further research is needed to understand how interventions focussing on increasing neural drive to GL would affect muscle function in runners with AT.
Number of athletes included in the study, separated by sex and sport discipline
Bland-Altman Plots: differences between calculated running speed a at lactate threshold 2 determined by oxygen cost of running at a fixed running speed of 2.8 m·s-1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {m} \cdot \hbox {s}^{-1}$$\end{document} (calLT2fix), b at lactate threshold 1 (calLT2LT1), and c at 80% of maximal oxygen uptake (calLT280%) vs. running speed at lactate threshold 2 (vLT2) determined by modified maximal deviation method. The individual data of male (N = 45) and female (N = 55) athletes are presented by blue cycles and red triangles, respectively; the solid line indicates mean difference; the dashed lines indicate the limits of agreement (mean ± 1.96 standard deviation); the dotted line represents the fitted linear regression
Graphical summary of commonality analyses for the modeled running speed at lactate threshold 2 (LT2) within all (N = 100), male (N = 45) and female (N = 55) athletes. The percentage contribution of each unique predictor to the total regression effect (i.e., R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^2$$\end{document}) is presented by the black filled arrows; the dashed lines and external solid lines represent the common effects of two and all predictors in R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^2$$\end{document}, respectively. V˙O2peak\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$\end{document}: maximal oxygen uptake; CR80%: cost of running determined at 80% of V˙O2peak\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$\end{document}; LT2%: fractional utilization of V˙O2peak\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$\end{document} at LT2.
Purpose: This study aimed to investigate: 1. The influence of sex and age on the accuracy of the classical model of endurance performance, including maximal oxygen uptake ([Formula: see text]), its fraction (LT2%), and cost of running (CR), for calculating running speed at lactate threshold 2 (vLT2) in young athletes. 2. The impact of different CR determination methods on the accuracy of the model. 3. The contributions of [Formula: see text], LT2%, and CR to vLT2 in different sexes. Methods: 45 male and 55 female young squad athletes from different sports (age: 15.4 ± 1.3 years; [Formula: see text]: 51.4 ± 6.8 [Formula: see text]) performed an incremental treadmill test to determine [Formula: see text], LT2%, CR, and vLT2. CR was assessed at a fixed running speed (2.8 [Formula: see text]), at lactate threshold 1 (LT1), and at 80% of [Formula: see text], respectively. Results: Experimentally determined and modeled vLT2 were highly consistent independent of sex and age (ICC [Formula: see text] 0.959). The accuracy of vLT2 modeling was improved by reducing random variation using individualized CR at 80% [Formula: see text] (± 4%) compared to CR at LT1 (± 7%) and at a fixed speed (± 8%). 97% of the total variance of vLT2 was explained by [Formula: see text], LT2%, and CR. While [Formula: see text] and CR showed the highest unique (96.5% and 31.9% of total [Formula: see text], respectively) and common (- 31.6%) contributions to the regression model, LT2% made the smallest contribution (7.5%). Conclusion: Our findings indicate: 1. High accuracy of the classical model of endurance performance in calculating vLT2 in young athletes independent of age and sex. 2. The importance of work rate selection in determining CR to accurately predict vLT2. 3. The largest contribution of [Formula: see text] and CR to vLT2, the latter being more important in female athletes than in males, and the least contribution of LT2%.
Purpose Poliomyelitis is an infectious disease that can cause total paralysis. Furthermore, poliomyelitis survivors may develop new signs and symptoms, including muscular weakness and fatigue, years after the acute phase of the disease, i.e., post-polio syndrome (PPS). Thus, the objective was to compare the functional exercise capacity during maximal and submaximal exercises among individuals with polio sequelae (without PPS diagnosis), PPS, and a control group. Methods Thirty individuals participated in three groups: a control group (CG, n = 10); a group of individuals with polio sequelae but without PPS diagnosis (PG, n = 10); and a PPS group (PPSG, n = 10). All participants underwent (i) a cardiopulmonary exercise test to determine their maximal oxygen uptake (V˙O2max\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{V}}\text{O}}_{{2}} {\text{max}}$$\end{document}) and (ii) a series of functional field tests (i.e., walking test, sit-to-stand test, and stair climbing test). Results V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}O2max was 30% lower in PPSG than in CG and PG. Regarding functional field tests, walking and stair climbing test performances were significantly different among all groups. The PPSG sit-to-stand performance was lower than CG. Conclusion The sequelae of paralytic poliomyelitis impair functional exercise capacity obtained from maximal and submaximal tests, especially in patients with PPS. Furthermore, submaximal variables appear to be more negatively impacted than maximal variables.
Research should equitably reflect responses in men and women. Including women in research, however, necessitates an understanding of the ovarian hormones and menstrual phase variations in both cellular and systems physiology. This review outlines recent advances in the multiplicity of ovarian hormone molecular signaling that elucidates the mechanisms for menstrual phase variability in exercise metabolism. The prominent endogenous estrogen, 17-β-estradiol (E2), molecular structure is bioactive in stabilizing plasma membranes and quenching free radicals and both E2 and progesterone (P4) promote the expression of antioxidant enzymes attenuating exercise-induced muscle damage in the late follicular (LF) and mid-luteal (ML) phases. E2 and P4 bind nuclear hormone receptors and membrane-bound receptors to regulate gene expression directly or indirectly, which importantly includes cross-regulated expression of their own receptors. Activation of membrane-bound receptors also regulates kinases causing rapid cellular responses. Careful analysis of these signaling pathways explains menstrual phase-specific differences. Namely, E2-promoted plasma glucose uptake during exercise, via GLUT4 expression and kinases, is nullified by E2-dominant suppression of gluconeogenic gene expression in LF and ML phases, ameliorated by carbohydrate ingestion. E2 signaling maximizes fat oxidation capacity in LF and ML phases, pending low-moderate exercise intensities, restricted nutrient availability, and high E2:P4 ratios. P4 increases protein catabolism during the luteal phase by indeterminate mechanisms. Satellite cell function supported by E2-targeted gene expression is countered by P4, explaining greater muscle strengthening from follicular phase-based training. In totality, this integrative review provides causative effects, supported by meta-analyses for quantitative actuality, highlighting research opportunities and evidence-based relevance for female athletes.
Resulted electrical under-skin current and subsequent bioelectrical (ionic) ATP formation elicited by the application of microcurrent. ATP Adenosine Triphosphate, Pi Inorganic Phosphate
Schematic representation of the microcurrent-induced lipolysis. NA noradrenaline, β3-AR beta3 adrenoreceptor, ATP adenosine triphosphate, cAMP cyclic adenosine monophosphate, PKA protein kinase A, TG, DG and, MG tri-, di, and monoglycerides, ATGL, HSL, and MGL lipolytic enzymes, FFA free fatty acids
Muscle protein synthesis activation by the application of microcurrent. NA noradrenaline, β3-AR beta3 adrenoreceptor, ATP adenosine triphosphate, cAMP cyclic adenosine monophosphate, PKA protein kinase A, AKT Ak strain transforming/protein kinase B, ACL ATP citrate lyase, ADP adenosine diphosphate, TSC tuberous sclerosis, Rheb Ras homolog enriched in brain, mRORC1 mammalian target of rapamycin complex 1 characterised by the presence of Raptor, 4E-BP1 factor 4E-binding protein 1, eIF4E eukaryotic translation initiator factor 4E, P70S6K Ribosomal protein S6 kinase beta-1
Effects of MCT on exercise adaptation in humans
Microcurrent is a non-invasive and safe electrotherapy applied through a series of sub-sensory electrical currents (less than 1 mA), which are of a similar magnitude to the currents generated endogenously by the human body. This review focuses on examining the physiological mechanisms mediating the effects of microcurrent when combined with different exercise modalities (e.g. endurance and strength) in healthy physically active individuals. The reviewed literature suggests the following candidate mechanisms could be involved in enhancing the effects of exercise when combined with microcurrent: (i) increased adenosine triphosphate resynthesis, (ii) maintenance of intercellular calcium homeostasis that in turn optimises exercise-induced structural and morphological adaptations, (iii) eliciting a hormone-like effect, which increases catecholamine secretion that in turn enhances exercise-induced lipolysis and (iv) enhanced muscle protein synthesis. In healthy individuals, despite a lack of standardisation on how microcurrent is combined with exercise (e.g. whether the microcurrent is pulsed or continuous), there is evidence concerning its effects in promoting body fat reduction, skeletal muscle remodelling and growth as well as attenuating delayed-onset muscle soreness. The greatest hindrance to understanding the combined effects of microcurrent and exercise is the variability of the implemented protocols, which adds further challenges to identifying the mechanisms, optimal patterns of current(s) and methodology of application. Future studies should standardise microcurrent protocols by accurately describing the used current [e.g. intensity (μA), frequency (Hz), application time (minutes) and treatment duration (e.g. weeks)] for specific exercise outcomes, e.g. strength and power, endurance, and gaining muscle mass or reducing body fat.
Overview of the experimental design. Participants performed three sessions of resistance exercise over three days. Maximal knee joint range of motion, passive torque, muscle shear modulus, and maximal isometric torque were measured before, and at 3, 30, and 60 min after each session of resistance exercise
Example of experimental setup in the measurements of muscle shear modulus and maximal isometric torque (80% of maximal joint range of motion)
Boxplots of time-course changes in maximal joint range of motion (ROM), passive torque, and maximal isometric torque after the resistance exercise sessions. SS short muscle lengths with a short duration (red box), LS long muscle lengths with a short duration (blue box), LL long muscle lengths with a long duration (green box). * pre-exercise vs. 3 min post-exercise, ¶ pre-exercise vs. 30 min post-exercise, § pre-exercise vs. 60 min post-exercise, † 3 min post-exercise vs. 60 min post-exercise, ‡ 30 min post-exercise vs. 60 min post-exercise, ○ group mean value for each measured variable, +  outlier value for each measured variable
Boxplots of time-course changes in the shear modulus of the individual hamstrings after the resistance exercise sessions. SS short muscle lengths with a short duration (red box), LS long muscle lengths with a short duration (blue box), LL long muscle lengths with a long duration (green box), BFlh biceps femoris long head, ST semitendinosus, SM semimembranosus. * pre-exercise vs. 3 min post-exercise, ¶ pre-exercise vs. 30 min post-exercise, † 3 min post-exercise vs. 60 min post-exercise, ○ group mean value for each measured variable, +  outlier value for each measured variable
PurposeA previous study revealed that resistance exercise with eccentric contraction and a wide range of motion (ROM) can acutely decrease muscle stiffness of a specific muscle. To explore further approaches to decrease the stiffness, we examined the acute changes in passive stiffness of the individual hamstring muscles after eccentric-only resistance exercise with different combinations of muscle lengths and exercise durations.Methods Thirteen healthy young male participants performed three sessions of eccentric-only exercises that comprised stiff-leg deadlift with different muscle lengths and exercise durations (duration per repetition × the total number of repetitions) on separate days as follows: (1) short muscle lengths with a short duration (SS); (2) long muscle lengths with a short duration (LS); and (3) long muscle lengths with a long duration (LL). Maximal joint ROM, passive torque, shear modulus of each hamstring muscle, and maximal isometric torque of knee flexion were measured before, and at 3, 30, and 60 min after each session.ResultsThe shear modulus of the semimembranosus was significantly lower at 3 min post-exercise (129.8 ± 22.7 kPa) than at pre-exercise (140.5 ± 19.1 kPa, p < 0.01) in LL, but not in SS or LS. No significant differences were observed in the shear moduli of the biceps femoris long head or semitendinosus between pre-exercise and 3 min post-exercise in any session.Conclusion The combination of long muscle lengths and a long duration during eccentric-only resistance exercise is important to immediately decrease the stiffness (shear modulus) of a specific muscle.
AimThe acute myocellular responses of caffeine supplementation during resistance exercise (RE) have not been investigated. β2-Adrenergic receptors (β2AR) may be a target of the stimulatory effects of caffeine and stimulate bioenergetic pathways including protein kinase A (PKA), and mitogen-activated protein kinases (MAPK).PurposeElucidate the effects of pre-workout supplementation on signaling responses to an acute RE bout.Methods In a randomized, counter-balanced, double-blind, placebo-controlled, within-subject crossover study, ten resistance-trained males (mean ± SD; age = 22 ± 2.4 years, height = 175 ± 7 cm, body mass = 84.1 ± 11.8 kg) consumed a caffeine containing multi-ingredient pre-workout supplement (SUPP) or color and flavor matched placebo (PL) 60 min prior to an acute RE bout of barbell back squats. Pre- and post-exercise muscle biopsies were analyzed for the phosphorylation (p-) of β2AR, PKA, and MAPK (ERK, JNK, p38). Epinephrine was determined prior to supplementation (baseline; BL), after supplementation but prior to RE (PRE), and immediately after RE (POST).ResultsEpinephrine increased at PRE in SUPP (mean ± SE: 323 ± 34 vs 457 ± 68 pmol/l; p = 0.028), and was greatest at POST in the SUPP condition compared to PL (5140 ± 852 vs 2862 ± 498 pmol/l; p = 0.006). p-β2AR and p-MAPK increased post-exercise (p < 0.05) with no differences between conditions (p > 0.05). Pearson correlations indicated there was a relationship between epinephrine and p-β2AR in PL (r = − 0.810; p = 0.008), and p-β2AR and ERK in SUPP (r = 0.941; p < 0.001).Conclusion Consumption of a caffeine containing pre-workout supplement improves performance, possibly through increases in pre-exercise catecholamines. However, the acute myocellular signaling responses were largely similar post-exercise.
Box plots of the RMSE of models predicting left ventricular mass. Box plot and comparison of the root mean squared error (RMSE) of the models predicting LVM. Model 1 used only ECG QRS variables. Model 2 combined ECG QRS and demographic variables. Model 3 used ECG QRS and DEXA variables. Model 4 combined variables from Model 2 and 3. In Model 5 exercise capacity was added to model 4
Purpose: Electrocardiogram (ECG) QRS voltages correlate poorly with left ventricular mass (LVM). Body composition explains some of the QRS voltage variability. The relation between QRS voltages, LVM and body composition in endurance athletes is unknown. Methods: Elite endurance athletes from the Pro@Heart trial were evaluated with 12-lead ECG for Cornell and Sokolow-Lyon voltage and product. Cardiac magnetic resonance imaging assessed LVM. Dual energy x-ray absorptiometry assessed fat mass (FM) and lean mass of the trunk and whole body (LBM). The determinants of QRS voltages and LVM were identified by multivariable linear regression. Models combining ECG, demographics, DEXA and exercise capacity to predict LVM were developed. Results: In 122 athletes (19 years, 71.3% male) LVM was a determinant of the Sokolow-Lyon voltage and product (β = 0.334 and 0.477, p < 0.001) but not of the Cornell criteria. FM of the trunk (β = - 0.186 and - 0.180, p < 0.05) negatively influenced the Cornell voltage and product but not the Sokolow-Lyon criteria. DEXA marginally improved the prediction of LVM by ECG (r = 0.773 vs 0.510, p < 0.001; RMSE = 18.9 ± 13.8 vs 25.5 ± 18.7 g, p > 0.05) with LBM as the strongest predictor (β = 0.664, p < 0.001). DEXA did not improve the prediction of LVM by ECG and demographics combined and LVM was best predicted by including VO2max (r = 0.845, RMSE = 15.9 ± 11.6 g). Conclusion: LVM correlates poorly with QRS voltages with adipose tissue as a minor determinant in elite endurance athletes. LBM is the strongest single predictor of LVM but only marginally improves LVM prediction beyond ECG variables. In endurance athletes, LVM is best predicted by combining ECG, demographics and VO2max.
Scheme for spatiotemporal parameters computation during skipping. Solid lines represent anteroposterior direction of ankle markers position for leading leg and trailing leg during a gait cycle of unilateral skipping. Dotted lines represent vertical direction of heel markers position for leading leg and trailing leg during a gait cycle of unilateral skipping. ltr→ld\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${l}_{tr\to ld}$$\end{document} represents the length of the pendular step. ttr→ld\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${t}_{tr\to ld}$$\end{document} represents the pendular step duration while tld→tr\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${t}_{ld\to tr}$$\end{document} indicate the bouncing step duration. The sum of ttr→ld\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${t}_{tr\to ld}$$\end{document} and tld→tr\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${t}_{ld\to tr}$$\end{document} compute the stride time (tstride\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${t}_{\mathrm{stride}}$$\end{document}). Dashed grey lines shows heel-strikes instants for trailing (tr\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$tr$$\end{document}) and leading (ld\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ld$$\end{document}) legs.
Metabolic power A and cost of transport B as speed function during running and skipping; linear fit and regression equation are represented for each quantity. Big circles show mean values (with standard deviations), while small circles represent individual data. * indicate that speed affects the dependent variable (Kruskal–Wallis, p < 0.05)
Step time asymmetry for skipping and running A and relative step time for skipping B. Big circles show mean values (with standard deviations), while small circles represent individual data
Step length asymmetry for skipping and running A and relative step length for skipping B. Big circles show mean values (with standard deviations), while small circles represent individual data. * indicate that speed affects of the dependent variable (Kruskal–Wallis, p < 0.05)
Leg stiffness as function of speed at different gaits. Big circles show mean values (with standard deviations), while small circles represent individual data. Linear fit and regression equation is represented for each quantity. # indicates significance differences between leg stiffness of skipping limbs, while † show statistical difference between leg stiffness of trailing limb in skipping and running. For running, the stiffness was computed only to the leg that works as a trailing leg during skipping
Purpose Unilateral skipping is an asymmetrical gait only exceptionally used by humans, due to high energetic demands. In skipping, the cost of transport decreases as speed increases, and the spring–mass model coexists with the vaulting pendular one. However, the mechanisms of energy transfers and recovery between the vaulting and the bouncing steps are still unclear in this gait. The objective of this work is to study how spatiotemporal and spring–mass asymmetries impact on metabolic cost, lowering it despite speed augmentation. Methods Kinematics and metabolic rates of healthy subjects were measured during running and skipping on a treadmill at controlled speeds. Results Metabolic power in skipping and running increased with similar slope but different intercepts. This fact determined the different behaviour of the cost of transport: constant in running, decreasing in skipping. In skipping the step time asymmetry remained constant, while the step length asymmetry decreased with speed, almost disappearing at 2.5 m/s⁻¹. Leg stiffness in trailing limb increased with higher slope than in leading limb and running; however, the relative leg stiffness asymmetry remained constant. Conclusions Slow skipping presents short bouncing steps, even shorter than the vaulting, impacting the stride mechanics and the metabolic cost. Faster speeds were achieved by taking longer bouncing steps and a stiffer trailing limb, allowing to improve the effectiveness of the spring–mass mechanism. The step asymmetries’ trends with respect to speed in skipping open the possibility to use this gait as an experimental paradigm to study mechanisms of metabolic cost reduction in locomotion.
Chronological representation of evaluations
Objective To analyze the physical performance, self-perception menstrual symptoms, of physically active eumenorrheic women with endogenous ovarian cycle in two phases of the menstrual cycle. Methods Twenty-six women participated in the study (age 25.8 ± 3.9 years; height 1.64 ± 0.58 m; mass 64 ± 12.32 kg; menarche 11.69 ± 1.28 years). Assessments were performed in two phases of the menstrual cycle (MC), Early-Follicular Phase (FP) and Mid-Luteal Phase (LP), performance was assessed through total time to exhaustion (TTE), complete stages (CE), and final speed (FE), through a graded exercise test (GXT). Information on the participants’ menstrual symptoms and their perceptions of the influence of MC on their performance were also collected. Data normality was assessed using the Shapiro–Wilk test. Paired analyses were conducted (t test or Wilcoxon) to examine the responses between the menstrual phases. The interaction analysis of symptom predictors was performed by multiple linear regression, with a significance level of p ≤ 0.05. Results There was no significant difference in physical performance between the phases during the GXT in TTE (mean difference 8.50; 95% CI − 11.99 to 42; p = 0.36). During FP, women with heavy flow had shorter performance in the GXT (t = − 2.5; p = 0.01), demonstrating an r² = 0.32. In LP, for the women who reported not having the perception of the influence of the menstrual cycle on exercise, the total test time was longer (t = 2.55; p = 0.01), with an r² = 0.45. Conclusion There was no difference in physical performance between FP and LP. However, menstrual flow intensity and perception of cycle interference demonstrated a decrease in TTE.
During a step-change in exercise power output (PO), ventilation ([Formula: see text]) increases with a similar time course to the rate of carbon dioxide delivery to the lungs ([Formula: see text]). To test the strength of this coupling, we compared [Formula: see text] and [Formula: see text] kinetics from ten independent exercise transitions performed within the moderate-intensity domain. Thirteen males completed 3-5 repetitions of ∆40 W step transitions initiated from 20, 40, 60, 80, 100, and 120 W on a cycle ergometer. Preceding the ∆40 W step transitions from 60, 80, 100, and 120 W was a 6 min bout of 20 W cycling from which the transitions of variable ∆PO were examined. Gas exchange ([Formula: see text] and oxygen uptake, [Formula: see text]) and [Formula: see text] were measured by mass spectrometry and volume turbine. The kinetics of the responses were characterized by the time constant (τ) and amplitude (Δ[Formula: see text]/Δ[Formula: see text]). Overall, [Formula: see text] kinetics were consistently slower than [Formula: see text] kinetics (by ~ 45%) and τ[Formula: see text] rose progressively with increasing baseline PO and with heightened ∆PO from a common baseline. Compared to τ[Formula: see text], τ[Formula: see text] was on average slightly greater (by ~ 4 s). Repeated-measures analysis of variance revealed that there was no interaction between τ[Formula: see text] and τ[Formula: see text] in either the variable baseline (p = 0.49) and constant baseline (p = 0.56) conditions indicating that each changed in unison. Additionally, for Δ[Formula: see text]/Δ[Formula: see text], there was no effect of either variable baseline PO (p = 0.05) or increasing ΔPO (p = 0.16). These data provide further evidence that, within the moderate-intensity domain, both the temporal- and amplitude-based characteristics of V̇E kinetics are inextricably linked to those of [Formula: see text].
Structural variables. Femoral artery diameter (panel A) and muscle mass (panel B) in whole (WL) and Amputated(AL) limbs. *p < 0.005; **p < 0.001
Vascular variables. Femoral blood velocity (panel A), shear rate (Panel B), femoral blood flow (panel C), normalized femoral blood (Panel D), vascular conductance (panel E), and carotid-femoral pulse wave velocity (panel F) in whole (WL) and amputated (AL) limbs
Correlation between structural variables: femoral artery diameter and lower limbs muscle mass. Whole limb (○) and amputated limb (●). p = 0.003, r = 0.6561
Purpose Both muscle mass and physical activity are independent mechanisms that play a role in vascular remodeling, however, the direct impact of muscle mass on the structure and function of the vessels is not clear. The aim of the study was to determine the impact of muscle mass alteration on lower limbs arterial diameter, blood flow, shear rate and arterial stiffness. Methods Nine (33 ± 13 yrs) male individuals with a single-leg amputation were recruited. Vascular size (femoral artery diameter), hemodynamics (femoral artery blood flow and shear rate were measured at the level of the common femoral artery in both amputated (AL) and whole limbs (WL). Muscle mass of both limbs, including thigh for AL and thigh and leg for WL, was measured with a DXA system. Results AL muscle mass was reduced compared to the WL (3.2 ± 1.2 kg vs. 9.4 ± 2.1 kg; p = 0.001). Diameter of the femoral artery was reduced in the AL (0.5 ± 0.1 cm) in comparison to the WL (0.9 ± 0.2 cm, p = 0.001). However, femoral artery blood flow normalized for the muscle mass (AL = 81.5 ± 78.7ml min⁻¹ kg⁻¹,WL = 32.4 ± 18.3; p = 0.11), and blood shear rate (AL = 709.9 ± 371.4 s⁻¹, WL = 526,9 ± 295,6; p = 0.374) were non different between limbs. A correlation was found only between muscle mass and femoral artery diameter (p = 0.003, R = 0.6561). Conclusion The results of this study revealed that the massive muscle mass reduction caused by a leg amputation, but independent from the level of physical activity, is coupled by a dramatic arterial diameter decrease. Interestingly, hemodynamics and arterial stiffness do not seem to be impacted by these structural changes.
Circulating cell numbers for individual study participants. CD4⁺ T cells (A), CD8⁺ T cell (B), NK cells (C), and the CD56loCD16⁺ NK cell subset (D) at 15 min of rest, and at 30 min post-exposure. *Denotes significant time effect; #denotes a significant time-by-treatment effect (p ≤ 0.05). PBC partial body cryotherapy, CWI cold water immersion, CON control. Paired numbers from each participant are joined by a line
Phenotype of CD16⁻ and CD16⁺ NK cells in individual participants. Each row in the heatmap indicates the percentage of cells positive for each marker listed on the left, while each column represents an individual participant, grouped as indicated by time of sample and treatment group. Rest 15 min of rest, post immediately post-exposure, PBC partial body cryotherapy, CWI cold water immersion, CON control group
Partial body cryotherapy (PBC) is proposed to alleviate symptoms of exercise-induced muscle damage (EIMD) by reducing associated inflammation. No studies have assessed acute PBC exposure on peripheral blood mononuclear cell mobilisation or compared these with cold water immersion (CWI), which may inform how PBC impacts inflammatory processes. This trial examined the impact of a single PBC exposure on circulating peripheral blood mononuclear cells compared to CWI or a control. 26 males were randomised into either PBC (3 min at − 110 to − 140 °C), CWI (3 min at 9 °C), or control (3 min at 24 °C), with blood samples, heart rate, and blood pressure taken before and after exposure. Cytometric analysis determined that CD8⁺ T-cell populations were significantly elevated after treatments, with PBC increasing CD8⁺ T cells to a greater degree than either CWI or CON. Natural killer cell counts were also elevated after PBC, with the increase attributed specifically to the CD56loCD16⁺ cytotoxic subset. This provides the first evidence for the effect of PBC exposure on redistribution of immune cells. An increase in circulating leukocyte subsets such as CD8⁺ T cells and CD56loCD16⁺ natural killer cells suggests that PBC may induce a transient mobilisation of lymphocytes. PBC may thus enable a more efficient trafficking of these cells from the circulation to the site of initial cellular insult from exercise, potentially accelerating the process of cellular recovery. This provides novel evidence on the use of PBC as a recovery treatment and may also have applicability in other clinical settings involving the recovery of damaged skeletal muscle.
Effects of the contraction intensity on the soleus β-CMC. CMC was computed as the volume in the beta-band (13–32 Hz) during the last 200 ms prior to the neurostimulation onset, in arbitrary units (a.u). Modulations of the soleus β-CMC are shown during lengthening (circle), isometric (triangle) and shortening (square) contractions at 25, 50 and 70% of the maximal soleus (SOL) EMG activity. Empty diamonds represent the mean β-CMC averaged across contraction types, while error bars represent the 95% CI of the mean 25 vs. 50–70%: *** p < 0.01
Effects of the contraction intensity on the EEGCz mean frequency and power spectrum, and on the soleus EMG mean frequency and power spectrum. EEGCz and EMG SOL power spectra (respectively A, C) of one representative subject were computed from the wavelet auto-spectra of the last 200 ms before the neurostimulation during shortening contractions are illustrated. The same wavelet auto-spectra from all subjects were used to compute EEGCz and EMG SOL mean frequencies (respectively B, D). Mean frequency modulations are shown during lengthening (circle), isometric (triangle) and shortening (square) contractions at 25, 50 and 70% of the maximal soleus (SOL) EMG activity. Empty diamonds represent the mean β-CMC averaged across contraction types, while error bars represent the 95% CI of the mean. 25 vs. 50–70%: *** p < 0.01
During isometric contractions, corticomuscular coherence (CMC) may be modulated along with the contraction intensity. Furthermore, CMC may also vary between contraction types due to the contribution of spinal inhibitory mechanisms. However, the interaction between the effect of the contraction intensity and of the contraction type on CMC remains hitherto unknown. Therefore, CMC and spinal excitability modulations were compared during submaximal isometric, shortening and lengthening contractions of plantar flexor muscles at 25, 50, and 70% of the maximal soleus (SOL) EMG activity. CMC was computed in the time–frequency domain between the Cz EEG electrode signal and the SOL or medial gastrocnemius (MG) EMG signals. The results indicated that beta-band CMC was decreased in the SOL only between 25 and 50–70% contractions for both isometric and anisometric contractions, but remained similar for all contraction intensities in the MG. Spinal excitability was similar for all contraction intensities in both muscles. Meanwhile a divergence of the EEG and the EMG signals mean frequency was observed only in the SOL and only between 25 and 50–70% contractions, independently from the contraction type. Collectively, these findings confirm an effect of the contraction intensity on beta-band CMC, although it was only measured in the SOL, between low-level and high-level contraction intensities. Furthermore, the current findings provide new evidence that the observed modulations of beta-band CMC with the contraction intensity does not depend on the contraction type or on spinal excitability variations.
Illustration sample of raw surface EMG signals from one participant during running on grass (column A), concrete (column B) and treadmill (column C). The black and white bands show 50% of running cycle, respectively
Panel A to C shows reconstruction quality (variation accounted for—VAF) from individual participants as a function of increased number of motor modules. The horizontal dash line in each panel corresponds to VAF at 0.9, and the vertical solid line correspond to the extraction of four motor modules. Panel D shows the average number of synergies extracted for a threshold between 0.7 and 1 (red line) and number of clusters needed to group them (blue line). The horizontal dash line depicts the number EMGs that were acquired (12 muscles) and signifies the maximum number of synergies that can be extracted. The yellow line corresponds to four clusters number
Motor modules extracted from 50 consecutive running cycles from grass, concrete, and treadmill running. In (A), individual module weightings are grouped for each muscle and running surface. In (B), mean (thick solid lines) and ± 1 standard deviation (shaded areas) for each activation signal related to the four modules. Vertical line indicates 50% of the running cycle
Motor module temporal structure across running conditions. In (A), the method used to characterize temporal activity. Activity duration (B), activity magnitude (C) and activity consistency (D) are represented as mean (SD) while running on grass (GRA), concrete (CCT) and treadmill (TRD). *Denotes significant differences in comparison to treadmill running (p < 0.05)
Mean (SD) of module activations from M1 to M4 across different conditions (First three rows). The solid lines represent averaged values and shaded areas represent ± 1 standard deviation. The black solid line traces below the data, second row, correspond to the SPM results
Running is an exercise that can be performed in different environments that imposes distinct foot–floor interactions. For instance, running on grass may help reducing instantaneous vertical impact loading, while compromising natural speed. Inter-muscular coordination during running is an important factor to understand motor performance, but little is known regarding the impact of running surface hardness on inter-muscular coordination. Therefore, we investigated whether inter-muscular coordination during running is influenced by running surface. Surface electromyography (EMG) from 12 lower limb muscles were recorded from young male individuals (n = 9) while running on grass, concrete, and on a treadmill. Motor modules consisting of weighting coefficients and activation signals were extracted from the multi-muscle EMG datasets representing 50 consecutive running cycles using non-negative matrix factorization. We found that four motor modules were sufficient to represent the EMG from all running surfaces. The inter-subject similarity across muscle weightings was the lowest for running on grass (r = 0.76 ± 0.11) compared to concrete (r = 0.81 ± 0.07) and treadmill (r = 0.78 ± 0.05), but no differences in weighting coefficients were found when analyzing the number of significantly active muscles and residual muscle weightings (p > 0.05). Statistical parametric mapping showed no temporal differences between activation signals across running surfaces (p > 0.05). However, the activation duration (% time above 15% peak activation) was significantly shorter for treadmill running compared to grass and concrete (p < 0.05). These results suggest predominantly similar neuromuscular strategies to control multiple muscles across different running surfaces. However, individual adjustments in inter-muscular coordination are required when coping with softer surfaces or the treadmill’s moving belt.
Experimental sitting protocol. SO sitting only condition, SSt sitting plus standing condition, ES exercise plus sitting condition, ESSt exercise plus sitting and standing condition. Interventions and times of measurement are represented by a timeline, with 180 min of continuous sitting with or without intermittent standing for 10-min durations every 30 min, and/or prior aerobic exercise for 30 min at a moderate intensity (see key)
Carotid–femoral pulse wave velocity (cfPWV) compared across time and within conditions. SO sitting only condition, SSt sitting plus standing condition, ES exercise plus sitting condition, ESSt exercise plus sitting and standing condition. †Represents significantly lower cfPWV for condition SSt compared to SO at post-intervention (p < 0.05). *Represents significantly greater cfPWV compared to pre-intervention within the specific condition (p < 0.05)
Brachial (left) and central (right) systolic (top row), diastolic (middle row), and mean (bottom row) blood pressures compared across time within each condition. SO sitting only condition, SSt sitting plus standing condition, ES exercise plus sitting condition, ESSt exercise plus sitting and standing condition. † and ‡Represents significantly greater pressure for condition SO compared to ES and ESSt, respectively, at the specific time point (p < 0.05). *Represents significantly greater pressure at 3-h intervention compared to pre-intervention within condition SO, respectively (p < 0.05)
Introduction Adverse vascular responses can occur during prolonged sitting, including stiffening of the aortic artery which may contribute to cardiovascular disease. Few studies have investigated the impact of intermittent standing and/or prior exercise as strategies to attenuate these potentially deleterious vascular changes. Purpose To investigate central vascular health responses during prolonged sitting, with and without intermittent standing and/or prior exercise. Methods Fifteen males aged 18 to 31 years were recruited. Subjects completed a control condition [Sitting Only (SO)], and three randomized strategy conditions [Sitting Plus Standing (SSt), Exercise Plus Sitting (ES), Exercise Plus Sitting Plus Standing (ESSt)]. For all conditions, measurements of carotid–femoral pulse wave velocity (cfPWV) were taken at pre- and post-intervention, and brachial and central blood pressure (BP) at pre-, 1-h, 2-h, and 3-h intervention. Results cfPWV significantly increased from pre- to post-intervention for all conditions (all p ≤ 0.043), as did brachial mean arterial pressure (MAP) and diastolic BP, and central MAP and diastolic BP for the control condition (all p ≤ 0.022). Brachial and central systolic BP were significantly higher during SO compared to ESSt at 1 h, and compared to ES for central systolic BP (all p ≤ 0.036). Conclusions Strategies of intermittent standing and/or prior exercise may not prevent aortic stiffening during sitting but may attenuate BP elevations in the brachial and aortic arteries. Future research should investigate causal mechanistic links between sitting and aortic stiffening, and other attenuation strategies.
The lack of a testable model explaining how ventilation is regulated in different exercise conditions has been repeatedly acknowledged in the field of exercise physiology. Yet, this issue contrasts with the abundance of insightful findings produced over the last century and calls for the adoption of new integrative perspectives. In this review, we provide a methodological approach supporting the importance of producing a set of evidence by evaluating different studies together—especially those conducted in ‘real’ exercise conditions—instead of single studies separately. We show how the collective assessment of findings from three domains and three levels of observation support the development of a simple model of ventilatory control which proves to be effective in different exercise protocols, populations and experimental interventions. The main feature of the model is the differential control of respiratory frequency (fR) and tidal volume (VT); fR is primarily modulated by central command (especially during high-intensity exercise) and muscle afferent feedback (especially during moderate exercise) whereas VT by metabolic inputs. Furthermore, VT appears to be fine-tuned based on fR levels to match alveolar ventilation with metabolic requirements in different intensity domains, and even at a breath-by-breath level. This model reconciles the classical neuro-humoral theory with apparently contrasting findings by leveraging on the emerging control properties of the behavioural (i.e. fR) and metabolic (i.e. VT) components of minute ventilation. The integrative approach presented is expected to help in the design and interpretation of future studies on the control of fR and VT during exercise.
Examples of gastrocnemius medialis shear modulus measurements at starting angle (0°), common maximal DF angle, and absolute maximal DF angle of one participant before (PRE) and after acute stretching (POST)
Mean RMS EMG values (SD) for TA and GL muscles in paretic leg for PRE and POST
Mean (standard deviation) torque–angle relationships during passive dorsiflexion from − 30° plantar flexion to maximal DF angle for paretic leg in PRE- and POST-stretch conditions
Mean (standard deviation) shear modulus–angle relationships from − 30° plantar flexion to maximal DF angle a and from slack angle to maximal DF angle; b during passive dorsiflexion for paretic leg in PRE- and POST-stretch conditions. The mean slack angle is provided for each leg (white circle and triangle for paretic leg in PRE- and POST-stretch conditions, respectively). a Full line ellipse represents the comparison at a common ankle angle (i.e., maximal DF angle at PRE) and dotted ellipse represents comparison at maximal DF angle of both legs. b Dotted ellipse represents comparison at maximal DF angle from slack angle of both legs
Purpose The aim of this study was to investigate the effects of an acute high-intensity, long-duration passive stretching session of the plantar flexor muscles, on maximal dorsiflexion (DF) angle and passive stiffness at both ankle joint and gastrocnemius medialis (GM) muscle levels in children with unilateral cerebral palsy (CP). Methods 13 children [mean age: 10 years 6 months, gross motor function classification system (GMFCS): I] with unilateral CP underwent a 5 min passive stretching session at 80% of maximal DF angle. Changes in maximal DF angle, slack angle, passive ankle joint and GM muscle stiffness from PRE- to POST-intervention were determined during passive ankle mobilization performed on a dynamometer coupled with shear wave elastography measurements (i.e., ultrasound) of the GM muscle. Results Maximal DF angle and maximal passive torque were increased by 6.3° (P < 0.001; + 50.4%; 95% CI 59.9, 49.9) and 4.2 Nm (P < 0.01; + 38.9%; 95% CI 47.7, 30.1), respectively. Passive ankle joint stiffness remained unchanged (P = 0.9; 0%; 95% CI 10.6, − 10.6). GM muscle shear modulus was unchanged at maximal DF angle (P = 0.1; + 34.5%; 95% CI 44.7, 24.7) and at maximal common torque (P = 0.5; − 4%; 95% CI − 3.7, − 4.3), while it was decreased at maximal common angle (P = 0.021; − 35%; 95% CI − 11.4, − 58.5). GM slack angle was shifted in a more dorsiflexed position (P = 0.02; + 20.3%; 95% CI 22.6, 18). Conclusion Increased maximal DF angle can be obtained in the paretic leg in children with unilateral CP after an acute bout of stretching using controlled parameters without changes in passive stiffness at joint and GM muscle levels. Clinical trial number NCT03714269.
Time course of finger skin temperature and skin blood flow during hand cold immersion. Values are mean ± SD. SkBF: skin blood flow, AU: arbitrary unit (n = 20)
Time course of skin temperature on non-immersed body region. Values are mean ± SD. Tsk: mean skin temperature, Thand: hand skin temperature, Tpro-dis: difference between proximal (average of forehead and chest) and distal (average of hand and foot) skin temperatures. For clarity non of the temperature data displayed here are from the immersed limb. * P < 0.05, significant difference between conditions. †P < 0.1, a moderate trend toward significance between conditions. P values of multiple paired T-tests are corrected with false discovery rate (FDR); n = 20
Time course of thermal sensation of the whole-body and immersed hand, thermal comfort and pain sensation of the immersed hand. Scales are explained in the method. Values are mean ± SD (n = 20)
Time course of skin temperature, skin blood flow, cutaneous vascular conductance in finger and mean arterial blood pressure during rewarming. Values are mean ± SD. SkBFfing: skin blood flow in finger, AU: arbitrary unit, CVCfing: cutaneous vascular conductance in finger, MAP: mean arterial blood pressure. *P < 0.05, significant difference between conditions. P values of multiple paired T-tests are corrected with false discovery rate (FDR); n = 20
Relationship between finger temperature rewarming speeds in water and beet conditions. Rewarming speed is calculated from 1 min to 5, 10, 15, and 20 min after hand immersion. Dotted line in the figures illustrated y = x (n = 20)
Purpose Vasoactive ingredients in beetroot (BR) such as nitrate are known to induce vasodilation in temperate conditions. This study investigated the effect of BR ingestion on cold induced vasodilation (CIVD) and rewarming of finger skin temperature (Tfing) during and after hand immersion in cold water. Methods Twenty healthy males (mean ± SD; age 22.2 ± 0.7 years, height 172.6 ± 6.0 cm, body mass 61.3 ± 11.7 kg) repeated a hand cold water immersion test twice with prior BR or water beverage ingestion (randomised order). They rested for 2 h in thermoneutral conditions (27 °C, 40% relative humidity) after consuming the beverage, then immersed their non-dominant hand in 8 °C water for 30 min. They then rewarmed their hand in the ambient air for 20 min. Skin temperature at seven body sites, Tfing, finger skin blood flow (SkBFfing), and blood pressure were measured. Results During hand immersion parameters of CIVD (Tfing and SkBFfing) were not different between BR and water conditions although skin temperature gradient from proximal to distal body sites was significantly smaller with BR (P < 0.05). During rewarming, SkBFfing and cutaneous vascular conductance were significantly higher with BR than with water (P < 0.05). The rewarming speed in Tfing and SkBFfing was significantly faster with BR at 15- (BR 1.24 ± 0.22 vs water 1.11 ± 0.26 °C/min) and 20-min rewarming (P < 0.05). Additionally, individuals with slower rewarming speed with water demonstrated accelerated rewarming with BR supplementation. Conclusion BR accelerated rewarming in Tfing and SkBFfing after local cold stimulus, whereas, CIVD response during hand cold immersion was not affected by BR ingestion.
Positive correlation between flow-mediated dilation (FMD%) and eNOS Ser¹¹⁷⁷ phosphorylation (peNOS Ser¹¹⁷⁷) in endothelial cells (ECs) obtained from radial arteries of coronary artery disease patients. Representative images of the immunofluorescence images of peNOS Ser¹¹⁷⁷ from CAD patients with low and high FMD are shown. AU: arbitrary units EC protein expression data are reported as ratios to human umbilical vein endothelial cells (HUVEC) protein expression
Positive correlation between flow-mediated dilation (FMD%) with p16 (a) and p21 (b) protein expression in endothelial cells (ECs) obtained from radial arteries of coronary artery disease patients. Representative images of the immunofluorescence images of p16 (a) and p21 (b) from CAD patients with low and high FMD are shown. AU arbitrary units EC protein expression data are reported as ratios to human umbilical vein endothelial cells (HUVEC) protein expression, p16 cyclin-dependent kinase inhibitor 2A, p21 cyclin-dependent kinase inhibitor 1
Positive relations between eNOS Ser¹¹⁷⁷ phosphorylation with NOX2 (a) and senescence marker p21 (b) of endothelial cells (ECs) obtained from radial artery of coronary artery disease patients. NFκB is correlated with ET-1 (c) and NOX2 (d). AU arbitrary units EC protein expression data are reported as ratios to human umbilical vein endothelial cells (HUVEC) protein expression; NOX2: NADPH oxidase subunit 2, p21 cyclin-dependent kinase inhibitor 1, NFκB nuclear factor kappa-light-chain-enhancer of activated B cells, ET-1 endothelin-1, peNOS phospho-endothelial nitric oxide synthase
Positive correlations between senescence and oxidative stress expression of endothelial cells (ECs) obtained from radial artery of coronary artery disease patients. NT expression is related to p16 (a), p21 (b) and p53 (c), NOX2 expression is correlated to p21 (d) and p53 (e), and p21 expression is associated with p53 (f). AU arbitrary units EC protein expression data are reported as ratios to human umbilical vein endothelial cells (HUVEC) protein expression, NT nitrotyrosine, p16 Cyclin-dependent kinase inhibitor 2A, p21 cyclin-dependent kinase inhibitor 1, p53 tumor protein 53, NOX2 NADPH oxidase subunit 2
Purpose Endothelial dysfunction is an early and integral event in the development of atherosclerosis and coronary artery disease (CAD). Reduced NO bioavailability, oxidative stress, vasoconstriction, inflammation and senescence are all implicated in endothelial dysfunction. However, there are limited data examining associations between these pathways and direct in vivo bioassay measures of endothelial function in CAD patients. This study aimed to examine the relationships between in vivo measures of vascular function and the expression of atherogenic risk-modulating proteins in endothelial cells (ECs) isolated from the radial artery of CAD patients. Methods Fifty-six patients with established CAD underwent trans-radial catheterization. Prior to catheterization, radial artery vascular function was assessed using a) flow-mediated dilation (FMD), and b) exercise-induced dilation in response to handgrip (HE%). Freshly isolated ECs were obtained from the radial artery during catheterization and protein content of eNOS, NAD(P)H oxidase subunit NOX2, NFκB, ET-1 and the senescence markers p53, p21 and p16 were evaluated alongside nitrotyrosine abundance and eNOS Ser¹¹⁷⁷ phosphorylation. Results FMD was positively associated with eNOS Ser¹¹⁷⁷ phosphorylation (r = 0.290, P = 0.037), and protein content of p21 (r = 0.307, P = 0.027) and p16 (r = 0.426, P = 0.002). No associations were found between FMD and markers of oxidative stress, vasoconstriction or inflammation. In contrast to FMD, HE% was not associated with any of the EC proteins. Conclusion These data revealed a difference in the regulation of endothelium-dependent vasodilation measured in vivo between patients with CAD compared to previously reported data in subjects without a clinical diagnosis, suggesting that eNOS Ser¹¹⁷⁷ phosphorylation may be the key to maintain vasodilation in CAD patients.
Representative magnetic resonance images (MRI) of right whole thigh muscle cross-sectional area (CSA) for baseline and post intervention (PI) time periods. A total of 14 slices were anatomically organized and matched between time points using Image J software to ensure that the changes in muscle CSA were accurately captured between two different time points (Participant ID: 004). Matching of slices between baseline and PI was primarily of identifying similar anatomical landmarks
Exploratory studies of mRNA expression of genes that lead to muscle hypertrophy in one high-responder participant compared to five low-responders. The high-responder has increased expression of four genes associated with muscle hypertrophy. The pathway includes the increase docking of IRS-1 to IGF-1 receptors, which triggers the downstream Akt and mTOR activity. It is obvious that the low-responders have one or more mRNA levels that either did not change or showed decrease after NMES-RT
Exploratory studies of mRNA expression of genes showing biomarkers of protein degradation in one high-responder participant compared to five low-responders. This includes myostatin, muscle-specific RING finger protein1 (MuRF-1), MAFbx32, and pyruvate kinase enzyme (PDK4) regulator (target gene of FOXO1; a key regulator of the expression of MuRF-1 and MAFBx32). The high responder showed decreases in almost all the mRNA expressions responsible for protein degradation. While MAFbx32 mRNA was increased, the protein expression was greatly reduced following NMES-RT
The purpose of the study was to identify potential predictors of muscle hypertrophy responsiveness following neuromuscular electrical stimulation resistance training (NMES-RT) in persons with chronic spinal cord injury (SCI). Data for twenty individuals with motor complete SCI who completed twice weekly NMES-RT lasting 12–16 weeks as part of their participation in one of two separate clinical trials were pooled and retrospectively analyzed. Magnetic resonance imaging (MRI) was used to measure muscle cross-sectional area (CSA) of the whole thigh and knee extensor muscle before and after NMES-RT. Muscle biopsies and fasting biomarkers were also measured. Following the completion of the respective NMES-RT trials, participants were classified into either high-responders (n = 8; muscle CSA > 20%) or low-responders (n = 12; muscle CSA < 20%) based on whole thigh muscle CSA hypertrophy. Whole thigh muscle and knee extensors CSAs were significantly greater (P < 0.0001) in high-responders (29 ± 7% and 47 ± 15%, respectively) compared to low-responders (12 ± 3% and 19 ± 6%, respectively). There were no differences in total caloric intake or macronutrient intake between groups. Extensor spasticity was lower in the high-responders compared to the low-responders as was the dosage of baclofen. Prior to the intervention, the high-responders had greater body mass compared to the low-responders with SCI (87.8 ± 13.7 vs. 70.4 ± 15.8 kg; P = 0.012), body mass index (BMI: 27.6 ± 2.7 vs. 22.9 ± 6.0 kg/m²; P = 0.04), as well as greater percentage in whole body and regional fat mass (P < 0.05). Furthermore, high-responders had a 69% greater increase (P = 0.086) in total Akt protein expression than low-responders. High-responders also exhibited reduced circulating IGF-1 with a concomitant increase in IGFBP-3. Exploratory analyses revealed upregulation of mRNAs for muscle hypertrophy markers [IRS-1, Akt, mTOR] and downregulation of protein degradation markers [myostatin, MurF-1, and PDK4] in the high-responders compared to low-responders. The findings indicate that body composition, spasticity, baclofen usage, and multiple signaling pathways (anabolic and catabolic) are involved in the differential muscle hypertrophy response to NMES-RT in persons with chronic SCI.
Placement of electrical muscle stimulation device. A Stimulation of the quadriceps muscle and B stimulation of the entire lower limbs
Protocol of electrical muscle stimulation. The repetition time of pulse series varied between 50 and 250 ms
Comparison of serum BDNF values between pre- and post-treatment in the control condition (A). Data show differences between post- and pre-serum BDNF values. Data shown as the mean ± SEM (B)
Comparison of BDNF levels in stimulation of the quadriceps muscle and the entire lower limbs. Data show differences each period and pre-serum BDNF values. Data shown as the mean ± SEM. *p < 0.05, compared with pre. †p < 0.05, compared with stimulation of the quadriceps muscle ant the entire lower limbs
Purpose Electrical muscle stimulation (EMS) is known to be effective at stimulating brain-derived neurotrophic factor (BDNF) levels, but the relationship between the volume of muscle stimulated and BDNF levels is not clear. The purpose of this study was to quantify BDNF as a function of muscle volume stimulated in young adults. Methods Twelve young adults (male, n = 9, age = 27.3 ± 5.5 years) were enrolled in this study. Participants completed three testing conditions in randomized order: 23 min of maximum tolerated bilateral stimulation of (1) the quadriceps muscle or (2) the musculature of the entire lower limbs and (3) control testing and retesting after 23 min without an intervention. Blood samples were collected before, immediately after, 20 min after, and 40 min after the intervention when EMS was applied to the thighs or the entire lower limb conditions. Serum obtained from blood collection was used for BDNF analysis. Results The delta value of BDNF for the test and retest in the control condition was − 42.1 ± 73.8 pg/mL, and there was no significant difference between the test and retest BDNF. Compared to stimulation of the quadriceps muscle, stimulation of the entire lower limbs produced significantly higher BDNF at 20 min post-treatment than those at pre-treatment or 40 min post-treatment, and BDNF was also significantly higher immediately post-treatment than those at pre-treatment. Only stimulation of the quadriceps muscle did not induce a significant change between pre- and post-treatment. Conclusion Our findings suggest that the volume of muscle stimulation is important for increased BDNF.
Purpose Following resistance exercise, uncertainty exists as to whether the regular application of cold water immersion attenuates lean muscle mass increases in athletes. The effects of repeated post-resistance exercise cold versus hot water immersion on body composition and neuromuscular jump performance responses in athletes were investigated. Methods Male, academy Super Rugby players ( n = 18, 19.9 ± 1.5 y, 1.85 ± 0.06 m, 98.3 ± 10.7 kg) participated in a 12-week (4-week × 3-intervention, i.e., control [CON], cold [CWI] or hot [HWI] water immersion) resistance exercise programme, utilising a randomised cross-over pre–post-design. Body composition measures were collected using dual-energy X-ray absorptiometry prior to commencement and every fourth week thereafter. Neuromuscular squat (SJ) and counter-movement jump (CMJ) performance were measured weekly. Linear mixed-effects models were used to analyse main (treatment, time) and interaction effects. Results There were no changes in lean ( p = 0.960) nor fat mass ( p = 0.801) between interventions. CON ( p = 0.004) and CWI ( p = 0.003) increased ( g = 0.08–0.19) SJ height, compared to HWI. There were no changes in CMJ height ( p = 0.482) between interventions. Conclusion Repeated post-resistance exercise whole-body CWI or HWI does not attenuate (nor promote) increases in lean muscle mass in athletes. Post-resistance exercise CON or CWI results in trivial increases in SJ height, compared to HWI. During an in-season competition phase, our data support the continued use of post-resistance exercise whole-body CWI by athletes as a recovery strategy which does not attenuate body composition increases in lean muscle mass, while promoting trivial increases in neuromuscular concentric-only squat jump performance.
PurposeThe present study investigated the effects of adding heat stress to repeated-sprint training in hypoxia on performance and physiological adaptations in well-trained athletes.Methods Sixteen canoe/kayak sprinters conducted 2 weeks of repeated-sprint training consisting of three sets of 5 × 10 s sprints with 20 s active recovery periods under conditions of either normobaric hypoxia (RSH, FiO2: 14.5%, ambient temperature: 18 ℃, n = 8) or combined heat and normobaric hypoxia (RSHH, FiO2: 14.5%, ambient temperature: 38 ℃, n = 8). Before and after training, the 10 × 10 s repeated-sprint ability (RSA) test and 500 m time trial were performed on a canoe/kayak ergometer.ResultsPeak and average power outputs during the RSA test were significantly improved after training in both RSH (peak power: + 21.5 ± 4.6%, P < 0.001; average power: + 12.5 ± 1.9%, P < 0.001) and RSHH groups (peak power: + 18.8 ± 6.6%, P = 0.005; average power: + 10.9 ± 6.8%, P = 0.030). Indirect variables of skeletal muscle oxygen extraction (deoxygenated hemoglobin) and blood perfusion (total hemoglobin) during the RSA test were significantly increased after training in the RSH group (P = 0.041 and P = 0.034, respectively) but not in the RSHH group. In addition, finish time during the 500 m time trial was significantly shortened after the training only in the RSH group (RSH: − 3.9 ± 0.8%, P = 0.005; RSHH: − 3.1 ± 1.4%, P = 0.078).Conclusion Adding heat stress to RSH does not enhance performance improvement and may partially mask muscle tissue adaptation.
Stratified randomization by gender and angiotensin-converting enzyme genotype (D/D, I/D, and I/I) was applied to allocate the study participants to angiotensin-converting enzyme inhibitor (ACEi) or placebo treatment
Values are presented as means (with 95% confidence intervals) from a linear mixed-model with time, treatment and time × treatment as explanatory variables. The figure shows citrate synthase maximal activity measured pre and post intervention in m. vastus lateralis (a) and m. deltoideus (b) in participants treated with an angiotensin-converting enzyme inhibitor (ACEi) or placebo. The result of the post hoc analysis is indicated by *P < 0.05 and **P < 0.001 compared with pre-intervention
Values are presented as means (with 95% confidence intervals) from a linear mixed-model with time, treatment and time × treatment as explanatory variables. The figure shows 3-hydroxyacyl-CoA dehydrogenase maximal activity measured pre and post intervention in m. vastus lateralis (A) and m. deltoideus posterior (B) in participants treated with an angiotensin-converting enzyme inhibitor (ACEi) or placebo. The result of the post hoc analysis is indicated by *P < 0.05 compared with pre-intervention and †P < 0.05 compared with placebo
Values are presented as means (with 95% confidence intervals) from a linear mixed-model with time, treatment and time × treatment as explanatory variables. The figure shows phosphofructokinase maximal activity measured pre and post intervention in m. vastus lateralis (A) and m. deltoideus posterior (B) in participants treated with an angiotensin-converting enzyme inhibitor (ACEi) or placebo. The result of the post hoc analysis is indicated by *P < 0.05 and **P < 0.001 compared with pre-intervention
Purpose Angiotensin-converting enzyme (ACE) inhibitor treatment is widely applied, but the fact that plasma ACE activity is a potential determinant of training-induced local muscular adaptability is often neglected. Thus, we investigated the hypothesis that ACE inhibition modulates the response to systematic aerobic exercise training on leg and arm muscular adaptations. Methods Healthy, untrained, middle-aged participants (40 ± 7 yrs) completed a randomized, double-blinded, placebo-controlled trial. Participants were randomized to placebo (PLA: CaCO3) or ACE inhibitor (ACEi: enalapril) for 8 weeks and completed a supervised, high-intensity exercise training program. Muscular characteristics in the leg and arm were extensively evaluated pre and post-intervention. Results Forty-eight participants (nACEi = 23, nPLA = 25) completed the trial. Exercise training compliance was above 99%. After training, citrate synthase, 3-hydroxyacyl-CoA dehydrogenase and phosphofructokinase maximal activity were increased in m. vastus lateralis in both groups (all P < 0.05) without statistical differences between them (all time × treatment P > 0.05). In m. deltoideus, citrate synthase maximal activity was upregulated to a greater extent (time × treatment P < 0.05) in PLA (51 [33;69] %) than in ACEi (28 [13;43] %), but the change in 3-hydroxyacyl-CoA dehydrogenase and phosphofructokinase maximal activity was similar between groups. Finally, the training-induced changes in the platelet endothelial cell adhesion molecule-1 protein abundance, a marker of capillary density, were similar in both groups in m. vastus lateralis and m. deltoideus. Conclusion Eight weeks of high-intensity whole-body exercise training improves markers of skeletal muscle mitochondrial oxidative capacity, glycolytic capacity and angiogenesis, with no overall effect of pharmacological ACE inhibition in healthy adults.
Schematic representation of the measurements performed before (PRE ECC), immediately after (POST ECC) and 24 h after (POST24 ECC) the eccentric bouts. This design was repeated across two experimental sessions performed 1 week apart to investigate potential repeated bout effects on neuromuscular function and position sense parameters. Please refer to the text for more details. EMG electromyography, KF knee flexors, MVIC Maximal voluntary isometric contraction, 1RM ECC eccentric unilateral 1 repetition maximum
Bilateral joint position-matching (JPM) tasks used in the present study to evaluate knee position sense at 40° and 70° of knee flexion in both seated (upper panel, a JPMS40 and b JPMS70) and prone (lower panel, c JPMP40, and d JPMP70) positions. Knee position sense was evaluated at short and long KF lengths during JPM tasks at 70° and at 40°, respectively. KF muscles were antagonistic during the seated JPM tasks, while they were agonistic during the prone JPM tasks. Note that 0° corresponds to full knee extension
Effect of the first (ECC1) and the second (ECC2) bout of eccentric contractions on knee flexor neuromuscular function. a MVIC torque, central (i.e., b VA and c CAR) and peripheral (d Dt100Hz, e Dt10Hz and f Twpot) fatigue parameters before (PRE), immediately after (POST) and 24 h after (POST24) ECC1 (blue bars) and ECC2 (yellow bars). Means ± SD values of 16 participants are shown. Only significant main effects of the time point are displayed in the figure with POST values significantly different from PRE values (*p < 0.05, **p < 0.01 and ***p < 0.001). MVIC maximal voluntary isometric contraction, VA voluntary activation level, CAR central activation ratio, Dt100Hz potentiated doublet amplitude at 100 Hz, Dt10Hz potentiated doublet amplitude at 10 Hz and Twpot potentiated single twitch
Immediate and long-lasting effects of knee flexor eccentric contractions on knee position sense. Position-matching errors measured before (PRE), immediately after (POST) and 24 h after (POST24) two bouts of eccentric contractions during bilateral joint position-matching (JPM) tasks in both seated (JPMS, upper panel a) and prone (JPMP, upper panel b) positions at two tested angles (40° of knee flexion, JPMS40 and JPMP40; 70° of knee flexion, JPMS70 and JPMP70). Pooled data (means ± standard error of the mean) of the first and second eccentric bouts are shown for 16 participants. Only significant main effects of the time point are displayed. **Significantly different from PRE at p < 0.01
Purpose This study examined eccentric-induced fatigue effects on knee flexor (KF) neuromuscular function and on knee position sense. This design was repeated across two experimental sessions performed 1 week apart to investigate potential repeated bout effects. Methods Sixteen participants performed two submaximal bouts of KF unilateral eccentric contractions until reaching a 20% decrease in maximal voluntary isometric contraction force. Knee position sense was evaluated with position-matching tasks in seated and prone positions at 40° and 70° of knee flexion so that KF were either antagonistic or agonistic during the positioning movement. The twitch interpolation technique was used to assess KF neuromuscular fatigue. Perceived muscle soreness was also assessed. Measurements were performed before, immediately (POST) and 24 h after (POST24) each eccentric bout. Results No repeated bout effect on neuromuscular function and proprioceptive parameters was observed. At POST, central and peripheral factors contributed to the force decrement as shown by significant decreases in voluntary activation level (− 3.8 ± 4.8%, p < 0.01) and potentiated doublet torque at 100 Hz (− 10 ± 15.8%, p < 0.01). At this time point, position-matching errors significantly increased by 1.7 ± 1.9° in seated position at 40° (p < 0.01). At POST24, in presence of muscle soreness (p < 0.05), although KF neuromuscular function had recovered, position-matching errors increased by 0.6 ± 2.6° in prone position at 40° (p < 0.01). Conclusion These results provide evidence that eccentric-induced position sense alterations may arise from central and/or peripheral mechanisms depending on the testing position.
In the mid-nineteenth century, the concept of muscle behaving like a stretched spring was developed. This elastic model of contraction predicted that the energy available to perform work was established at the start of a contraction. Despite several studies showing evidence inconsistent with the elastic model, it persisted into the twentieth century. In 1923, W. O. Fenn published a paper in which he presented evidence that appeared to clearly refute the elastic model. Fenn showed that when a muscle performs work it produces more heat than when contracting isometrically. He proposed that energy for performing work was only made available in a muscle as and when that work was performed. However, his ideas were not adopted and it was only after 15 years of technical developments that in 1938 A. V. Hill performed experiments that conclusively disproved the elastic model and supported Fenn’s conclusions. Hill showed that the rate of heat production increased as a muscle made the transition from isometric to working contraction. Understanding the basis of the phenomenon observed by Fenn and Hill required another 40 years in which the processes that generate force and work in muscle and the associated scheme of biochemical reactions were established. Demonstration of the biochemical equivalent of Hill’s observations—changes in rate of ATP splitting when performing work—in 1999 was possible through further technical advances. The concept that the energy, from ATP splitting, required to perform work is dynamically modulated in accord with the loads a muscle encounters when contracting is key to understanding muscle energetics.
Regression plots for all participants a Values of VT1 vs. HRVT1 for VO2; b Values of VT1 vs. HRVT1 for HR; c Values of VT2 vs. HRVT2 for VO2; d Values of VT2 vs. HRVT2 for HR. SEE, standard error of estimate; R², coefficient of determination
Bland Altman plots of values of a VT1 vs. HRVT1 for VO2; b VT1 vs. HRVT1 for HR; c VT2 vs. HRVT2 for VO2; d VT2 vs. HRVT2 for HR. Center line in each plot represents the mean difference between each paired value, the top and bottom lines are 1.96 standard deviations from the mean difference
Studies highlight the usage of non-linear time series analysis of heart rate variability (HRV) using the short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA-alpha1) during exercise to determine aerobic and anaerobic thresholds. The present study aims to further verify this approach in women. Gas exchange and HRV data were collected from 26 female participants with different activity levels. Oxygen uptake (VO2) and heart rate (HR) at first (VT1) and second ventilatory thresholds (VT2) were compared with DFA-alpha1-based thresholds 0.75 (HRVT1) and 0.50 (HRVT2). Results: VO2 at VT1 and VT2 were 25.2 ml/kg/min (± 2.8) and 31.5 ml/kg/min (± 3.6) compared with 26.5 ml/kg/min (± 4.0) and 31.9 ml/kg/min (± 4.5) for HRVT1 and HRVT2, respectively (ICC3,1 = 0.77, 0.84; r = 0.81, 0.86, p < 0.001). The mean HR at VT1 was 147 bpm (± 15.6) and 167 bpm (± 12.7) for VT2, compared with 152 bpm (± 15.5) and 166 bpm (± 13.2) for HRVT1 and HRVT2, respectively (ICC3,1 = 0.87, 0.90; r = 0.87, 0.90, p < 0.001). Bland–Altman analysis for VT1 vs. HRVT1 showed a mean difference of − 1.3 ml/kg/min (± 2.4; LoA: 3.3, − 6.0 ml/kg/min) for VO2 and of − 4.7 bpm (± 7.8; LoA: 10.6, − 20.0 bpm) for HR. VT2 vs. HRVT2 showed a mean difference of − 0.4 ml/kg/min (± 2.3; LoA: 4.1, − 4.9 ml/kg/min) for VO2 and 0.5 bpm (± 5.7; LoA: 11.8, − 10.8 bpm) for HR. DFA-alpha1-based thresholds showed good agreement with traditionally used thresholds and could be used as an alternative approach for marking organismic transition zones for intensity distribution in women.
Purpose This review recalls the principles developed over a century to describe trans-capillary fluid exchanges concerning in particular the lung during exercise, a specific condition where dyspnea is a leading symptom, the question being whether this symptom simply relates to fatigue or also implies some degree of lung edema. Method Data from experimental models of lung edema are recalled aiming to: (1) describe how extravascular lung water is strictly controlled by “safety factors” in physiological conditions, (2) consider how waning of “safety factors” inevitably leads to development of lung edema, (3) correlate data from experimental models with data from exercising humans. Results Exercise is a strong edemagenic condition as the increase in cardiac output leads to lung capillary recruitment, increase in capillary surface for fluid exchange and potential increase in capillary pressure. The physiological low microvascular permeability may be impaired by conditions causing damage to the interstitial matrix macromolecular assembly leading to alveolar edema and haemorrhage. These conditions include hypoxia, cyclic alveolar unfolding/folding during hyperventilation putting a tensile stress on septa, intensity and duration of exercise as well as inter-individual proneness to develop lung edema. Conclusion Data from exercising humans showed inter-individual differences in the dispersion of the lung ventilation/perfusion ratio and increase in oxygen alveolar-capillary gradient. More recent data in humans support the hypothesis that greater vasoconstriction, pulmonary hypertension and slower kinetics of alveolar-capillary O2 equilibration relate with greater proneness to develop lung edema due higher inborn microvascular permeability possibly reflecting the morpho-functional features of the air–blood barrier.
Metabolic responses: Glycaemia (A), RQ (B), CHz oxidation rates (C) and fat oxidation rates (D) during fasting and post-meal conditions in active and inactive men.*, **, ***: significantly different from ACT group at p < 0.05, p < 0.01 and p < 0.001, respectively. ACT active group, INACT inactive group, T0 at the end of breakfast ingestion, T15 15 min after the end of breakfast ingestion, T30 30 min after the end of breakfast ingestion, T45 45 min after the end of breakfast ingestion, T60 60 min after the end of breakfast ingestion, RQ respiratory quotient, CHO carbohydrates
Heart rate variability responses: Heart rate (A) and RMSSD (B) during fasting and post-meal conditions in active and inactive men. *, **, ***: significantly different from ACT group at p < 0.05, p < 0.01 and p < 0.001, respectively. ACT active group, INACT inactive group, T0 at the end of breakfast ingestion, T15 15 min after the end of breakfast ingestion, T30 30 min after the end of breakfast ingestion, T45 45 min after the end of breakfast ingestion, T60 60 min after the end of breakfast ingestion, HR heart rate, RMSSD square root of the sum of successive differences between adjacent normal R–R intervals squared
Purpose Post-meal cardiometabolic responses are critical for health, and may be influenced by physical activity. The objective of this study was to investigate the effect of habitual physical activity level on the metabolic, autonomic nervous system and cardiovascular responses to a balanced meal in healthy men. Methods 12 active and 12 inactive healthy males, matched for age and body composition, attended the laboratory in fasting condition. Participants were asked to sit quietly and comfortably in an armchair for the whole duration of the experiment (~ 2h30). Metabolic, autonomic nervous system and cardiovascular measurements were performed in fasting conditions, and at regular intervals until one hour after the end of a balanced breakfast. Results No significant difference was observed between groups in glycaemia or energy expenditure throughout the experiment. Fat oxidation rate was significantly higher one-hour post-meal in active vs inactive men (Respiratory Quotient: 0.78 ± 0.04 vs 0.88 ± 0.03; p < 0.01). Heart rate was significantly lower in active compared to inactive individuals (p < 0.001) throughout the experiment and active participants displayed significantly enhanced vagal tone one-hour post-meal (square root of the sum of successive differences between adjacent normal R–R intervals squared: 72.4 ± 27.9 vs 46.4 ± 14.1 ms; p < 0.05). Conclusion In healthy men, habitual physical activity level seems discriminant to decipher specific profiles in terms of cardiometabolic responses to a meal. Overall, it may suggest pre-signal cardiometabolic impairments in healthy inactive individuals and highlight the need to consider primary prevention in inactive subjects as a key factor for health management.
Flow diagram of the study
Contraction/relaxation durations of the EMS session (A) and the experimental protocol of EMS training (B) EMS, electromyostimulation training
Effect of EMS training on echo intensity in the vastus lateralis (A) and rectus femoris (B) EMS, electromyostimulation training
Purpose Electromyostimulation (EMS) induces a short-term change in muscle metabolism, and EMS training induces long-term improvements of muscle atrophy and function. However, the effects of EMS training on intramuscular fat in older adults are still poorly known. The purpose of this study was to examine whether the intramuscular fat index and biochemical parameters change with EMS training of the quadriceps femoris muscles in older adults. Methods Nineteen non-obese older men and women performed EMS training of the quadriceps femoris for 12 weeks (3 times/week; single session for 30 min). The intramuscular fat content index was estimated by echo intensity of the vastus lateralis and rectus femoris muscles on ultrasonography, and muscle thickness was also measured. Muscle strength was assessed as the maximal voluntary contraction during isometric knee extension. Echo intensity, muscle thickness, and muscle strength were measured before and after EMS training. A rested/fasting blood samples were collected before and after EMS training for measuring plasma glucose, insulin, free fatty acid, triglyceride, and interleukin-6 concentrations. To examine the acute effect of a single-EMS session on biochemical parameters, blood samples were taken before and after the EMS session. Results EMS training did not significantly change echo intensity in muscles, muscle thickness, muscle strength, or biochemical parameters. Regarding the acute effect on blood lipid concentrations, a single-EMS session increased free fatty acid and glucose concentrations. Conclusion EMS sessions had an acute effect of increasing free fatty acid and glucose concentrations, but EMS training intervention did not improve intramuscular fat content.
Schematic representation of the applied protocols. In protocol A, after a square transition of 6 min followed by 5 min of recovery, a series of five identical transitions followed. Each exercise phase was separated by increasing times of recovery from 30 to 120 s. In protocol B, the order of the times of recovery was reverted
V˙O2A\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{\text{A}}}}$$\end{document} kinetics of a typical subjects after interpolation and over-imposition of the single repetitions together with the fitted mono-exponential functions and the resulting τ
τ of V˙O2A\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{\text{A}}}}$$\end{document} kinetics as a decreasing function of the recovery time. The decay can be described according to a first-order decaying function
A Estimated [PCr] (full circles) and ∆[PCr] (open circles) prevailing before the onset of square-wave exercise as a function of the time of recovery. Big circles (at time of recovery of 300 s) refer to the control conditions. [PCr] at rest and after 300 s of recovery was assumed equal to 25 mmol kg⁻¹ of fresh muscle; ∆[PCr] values at rest and after a complete recovery were used to obtain a single mean value: Bτ as a function of [PCr] prevailing at the end of recovery before the onset square-wave transitions; Cτ as a function of ∆[PCr] consumed during the transient phase of each square-wave transitions
Purpose τ of the primary phase of $$\dot{V}{\text{O}}_{{2{\text{A}}}}$$ V ˙ O 2 A kinetics during square-wave, moderate-intensity exercise mirrors that of PCr splitting ( τ PCr). Pre-exercise [PCr] and the absolute variations of PCr (∆[PCr]) occurring during transient have been suggested to control τ PCr and, in turn, to modulate $$\dot{V}{\text{O}}_{{2{\text{A}}}}$$ V ˙ O 2 A kinetics. In addition, $$\dot{V}{\text{O}}_{{2{\text{A}}}}$$ V ˙ O 2 A kinetics may be slower when exercise initiates from a raised metabolic level, i.e., from a less-favorable energetic state. We verified the hypothesis that: (i) pre-exercise [PCr], (ii) pre-exercise metabolic rate, or (iii) ∆[PCr] may affect the kinetics of muscular oxidative metabolism and, therefore, τ . Methods To this aim, seven active males (23.0 yy ± 2.3; 1.76 m ± 0.06, $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max : 3.32 L min ⁻¹ ± 0.67) performed three repetitions of series consisting of six 6-min step exercise transitions of identical workload interspersed with different times of recovery: 30, 60, 90, 120, 300 s. Results Mono-exponential fitting was applied to breath-by-breath $$\dot{V}{\text{O}}_{{2{\text{A}}}}$$ V ˙ O 2 A , so that τ was determined. τ decays as a first-order exponential function of the time of recovery ( τ = 109.5 × e (− t /14.0) + 18.9 r ² = 0.32) and linearly decreased as a function of the estimated pre-exercise [PCr] ( τ = − 1.07 [PCr] + 44.9, r ² = 0.513, P < 0.01); it was unaffected by the estimated ∆[PCr]. Conclusions Our results in vivo do not confirm the positive linear relationship between τ and pre-exercise [PCr] and ∆[PCr]. Instead, $$\dot{V}{\text{O}}_{{2{\text{A}}}}$$ V ˙ O 2 A kinetics seems to be influenced by the pre-exercise metabolic rate and the altered intramuscular energetic state.
Study design. All participants performed an incremental test (A). Then, they performed three to five high-intensity trials to estimate their velocity–duration relationship (B), used to prescribe the intensities of all the following sessions. The high intensity was set as the velocity that was supposed to lead to exhaustion in 6 min (CV6), while low intensity was the velocity corresponding to the 66% of critical velocity (66%CV). The tests C, D and E were used to measure how much the timing of the first recovery bout [after 30 s, (C); 3 min, (D); or Tlim, (E)] influences the reconstruction rate of D’. Finally, the subjects performed the three HIIT protocols: Long intervals HIIT (LIHIIT), (F); high-intensity decremented interval training (HIDIT), (G); Short intervals (SIHIIT), (H)
Reconstitution as a percentage of D’ during 2 min of recovery at velocity corresponding to 66% of CV, timed after 30 s (Rec30sec), 3 min (Rec3min) and after exhaustions (RecTlim) at the intensity of CV6 (the velocity that was supposed to lead to exhaustion in 6 min). *significantly different (P < 0.05)
Time > 90% V˙O2max\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{\text{V}}\text{O}}_{{{\text{2max}}}}$$\end{document} (A) and Tlim (B) during HIIT protocols with short intervals (SIHIIT), with decreasing duration of intervals (HIDIT) and with long intervals (LIHIIT) with same mean speed as high intensity, low intensity and the ratio of the durations of high/low intensities are identical. *Significantly different (P < 0.05)
Purpose Accumulating the time near maximum aerobic power $$\left( {{\dot{\text{V}}\text{O}}_{{{\text{2max}}}} } \right)$$ V ˙ O 2max is considered to be the most effective way to improve aerobic capacity. The aims of this study were: (1) to verify whether postponing the first recovery interval improves time to exhaustion during a high-intensity interval training (HIIT) test, and (2) to verify whether a HIIT protocol with decreasing interval duration (HIDIT) is more effective in accumulating time near $${\dot{\text{V}}\text{O}}_{{{\text{2max}}}}$$ V ˙ O 2max compared with two classical protocols with short intervals (SI HIIT ) and long intervals (LI HIIT ). Methods Nine active males (35 ± 11 years, $${\dot{\text{V}}\text{O}}_{{{\text{2max}}}}$$ V ˙ O 2max 52 ± 5 mL·min ⁻¹ ·kg ⁻¹ ) performed a graded exercise test on an athletic track. Critical velocity and D’ were estimated from three to five high-intensity trials to exhaustion. Then, the subjects performed three trials with a single recovery interval after 30 s (Rec 30s ), after 3 min (Rec 3min ) and after exhaustion (Rec Tlim ) to verify whether postponing the first recovery interval enhances the time to exhaustion. Finally, the subjects performed the three HIIT protocols mentioned above. Results The time to exhaustion was significantly greater in Rec Tlim (464 ± 67 s) than in Rec 3min (388 ± 48 s) ( p < 0.0078) and Rec 30s (308 ± 44 s) ( p > 0.0001). Additionally, it was significantly greater in Rec 3min than in Rec 30s ( p = 0.0247). Furthermore, the time accumulated near $${\dot{\text{V}}\text{O}}_{{{\text{2max}}}}$$ V ˙ O 2max was significantly longer in HIDIT (998 ± 129 s) than in SI HIIT (678 ± 116 s) ( p = 0.003) and LI HIIT (673 ± 115 s) ( p < 0.031). Conclusions During the trials, postponing the first recovery interval was effective in improving the time to exhaustion. Moreover, HIDIT was effective in prolonging the time near $${\dot{\text{V}}\text{O}}_{{{\text{2max}}}}$$ V ˙ O 2max .
V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2 versus time relationship during the graded exercise test (GXT), 5-min rest, and verification bout for test 1 (A) and test 2 (B) for a representative subject who demonstrated a V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2 from the GXT (V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT) which was greater than V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2 from the verification bout (V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification) by more than the minimal difference to be considered real (MD); and test 1 (C) and test 2 (D) for a representative subject who demonstrated a V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT and V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification which were within the MD. *The first 5 min of data from the warm-up have been excluded. The nonlinear portion reflects the initial V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2 kinetics to the start of exercise
Purpose A square-wave verification bout to confirm maximal oxygen uptake (V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2max) from a graded exercise test (GXT) has been recommended. This study ascertained if a verification bout is necessary to determine V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2max in moderately trained men. Methods Ten men (24 ± 4 years) completed familiarization and two treadmill GXTs, followed by a submaximal verification bout to determine V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT and V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification (highest V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2 from each testing method). After completing the GXT, subjects rested for 5 min then performed a verification bout at 90% speed and 50% incline at termination of the GXT. The analyses included a 2-way repeated-measures ANOVA, intra-class correlation coefficients (ICC2,1), standard errors of the measurement (SEM), minimal differences (MD), and coefficients of variation (CoV). Results There was no test (test 1 vs test 2) × method (GXT vs verification) interaction (p = 0.584), or main effect for test (p = 0.320), but there was a main effect for method (p = 0.011). The V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT (50.9±3.0 mL·kg⁻¹·min⁻¹) was greater than V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification (46.9 ± mL·kg⁻¹·min⁻¹). The V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT (ICC = 0.988, SEM = 1.0 mL·kg⁻¹ min⁻¹, MD = 2.9 mL kg⁻¹ min⁻¹, CoV = 2.03%) and V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification (ICC = 0.976, SEM = 1.0 mL·kg⁻¹ min⁻¹, MD = 2.7 mL·kg⁻¹·min⁻¹, CoV = 2.03%) demonstrated “excellent” reliability. No subject exceeded the MD for V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT test–retest or for V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification test–retest, but 50% of subjects had a V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT that was greater than the V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification (> MD). Conclusion While V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT and V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2verification demonstrated excellent reliability, V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT from a stand-alone GXT provided higher estimates of V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2 and, therefore, should be considered V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2max. The lack of test–retest differences in V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2GXT above the MD indicated that subjects achieved their highest V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2 (V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2max) from a standalone GXT. Therefore, the verification bout may not be required to confirm V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\mathrm{V}}$$\end{document}O2max in this population.
Exploded view of FLEX (panel a) and STIFF (panel b) prototypes. The plates were embedded in the middle of the midsole. The plate material was the only feature differing in-between the two prototypes
Distribution of runners according to MAS (Maximal Aerobic Speed), height, weight, and age across the sample (n = 96). The orange and gray areas represent, respectively, the density curve (Gaussian curve) for women and men according to the studied parameters. Dotted lines represent the median distribution
Individual (gray lines between white circles) metabolic energy expenditure (W/kg) in the two shoe interventions STIFF (17 N/mm) and FLEX (10.4 N/mm). Gray squares represent mean in each condition
Individual relative differences in metabolic energy expenditure (W/kg) between FLEX (10.4 N/mm) and STIFF (17 N/mm). A negative difference indicates RE improvement in STIFF. Cluster 1 is denoted by blue circles. Cluster 2 is denoted by red circles. Cluster 3 is denoted by white circles. Gray shaded area delimited by dotted line shows the SWC (smallest worthwhile change) of metabolic energy expenditure
Mechanical properties and shoe mass for the two shoe condi- tions (for 8.5 UK sample)
Background: Shoe longitudinal bending stiffness is known to influence running economy (RE). Recent studies showed divergent results ranging from 3% deterioration to 3% improvement in RE when bending stiffness increases. The variability of these results highlights inter-individual differences. Thus, our purpose was to study the runner-specific metabolic responses to changes in shoe bending stiffness. Methods: After assessing their maximal oxygen consumption ([Formula: see text] max) and aerobic speed (MAS) during a first visit, 96 heterogeneous runners performed two treadmill 5 min runs at 75% [Formula: see text] max with two different prototypes of shoes on a second day. Prototypes differed only by their forefoot bending stiffness (17 N/mm vs. 10.4 N/mm). RE and stride kinematics were recorded during each trial. A clustering analysis was computed by comparing the measured RE and the technical measurement error of our gas exchange analyzer to identify functional groups of runners, i.e., responding similarly to footwear interventions. ANOVAs were then computed on biomechanical and morphological variables to compare the functional groups. Results: Considering the whole sample (n = 96), there was no significant difference in RE between the two conditions. Cluster 1 (n = 29) improves RE in the stiffest condition (2.7 ± 2.1%). Cluster 2 (n = 26) impairs RE in the stiffest condition (2.7 ± 1.3%). Cluster 3 (n = 41) demonstrated no change in RE (0.28 ± 0.65%). Cluster 1 demonstrated 1.7 km·h-1 greater MAS compared to cluster 2 (p = 0.014). Conclusion: The present study highlights that the effect of shoe bending stiffness on RE is runner-specific. High-level runners took advantage of increased bending stiffness, whereas medium-level runners did not. Finally, this study emphasizes the importance of individual response examination to understand the effect of footwear on runner's performance.
Changes of the concentration of various cytokines, chemokines, matrix metallopeptidases, membrane proteins, Ca²⁺-binding proteins, growth factors, and enzymes pre and post-acute exercise in capillary plasma taken from the earlobe. Number of subjects (n), results from the pairwise T test as well as Wilcoxon-Test: *mean p < 0.05, **means p < 0.01, ****means p < 0.0001. Raw data are shown
Bland–Altman plots for IL-1β (A), IL-8 (B), IL-17A (C), IFN-y (D), CCL-2 (E), MMP-9 (F), and SPARC (G). Raw data are shown. PRE samples taken before exercise; POST samples taken after exercise
Purpose The present study aims to investigate the acute response of potential exercise-sensitive biomarkers in capillary plasma to an acute incremental running test. In a second step, their concentration was compared to the changes in the venous serum. Methods Thirty-seven active young female and male adults completed a VO2max ramp test on a treadmill. Before and after exercise, capillary blood from the earlobe and venous blood were taken and synchronized. Concentrations of Interleukin- (IL-) 1β, IL-1ra, IL-6, IL-8, IL-17A, Interferon (IFN)-y, CC-chemokine ligand (CCL)-2, Matrix metallopeptidase (MMP)-9, Secreted protein acidic and rich in cysteine (SPARC), Cluster of differentiation (CD)163, S100 Ca²⁺ -binding protein (S100) A8, S100A9, S100B, Brain-derived neurotrophic factor (BDNF), and Myeloperoxidase (MPO) were determined by magnetic bead-based multiplex assay. Results Capillary plasma concentrations of IL-1β, IL-6, IL-8, IL-17A, IFN-y, CCL-2, MMP-9, SPARC, CD163, S100A9, S100B, and BDNF increased after exercise (p < 0.05). Comparing the values from capillary plasma and venous serum, ICCs classified as good were found for IFN-y (post), while the ICCs for IL-1β, IL-8, IL-17A, CCL-2, MMP-9 (post), SPARC, and BDNF (post) were classified as moderate. For all other parameters, only weak ICCs were found. Conclusion As in the venous serum, there was an increase in most markers in the capillary plasma. However, acceptable to low associations can be found in the concentration levels of these proteins between the compartments. Thus, this source of blood sampling could find some biomarker applications in sports practice.
Purpose Divers can experience cognitive impairment due to inert gas narcosis (IGN) at depth. Brain-derived neurotrophic factor (BDNF) rules neuronal connectivity/metabolism to maintain cognitive function and protect tissues against oxidative stress (OxS). Dopamine and glutamate enhance BDNF bioavailability. Thus, we hypothesized that lower circulating BDNF levels (via lessened dopamine and/or glutamate release) underpin IGN in divers, while testing if BDNF loss is associated with increased OxS. Methods To mimic IGN, we administered a deep narcosis test via a dry dive test (DDT) at 48 msw in a multiplace hyperbaric chamber to six well-trained divers. We collected: (1) saliva samples before DDT (T0), 25 msw (descending, T1), 48 msw (depth, T2), 25 msw (ascending, T3), 10 min after decompression (T4) to dopamine and/or reactive oxygen species (ROS) levels; (2) blood and urine samples at T0 and T4 for OxS too. We administered cognitive tests at T0, T2, and re-evaluated the divers at T4. Results At 48 msw, all subjects experienced IGN, as revealed by the cognitive test failure. Dopamine and total antioxidant capacity (TAC) reached a nadir at T2 when ROS emission was maximal. At decompression (T4), a marked drop of BDNF/glutamate content was evidenced, coinciding with a persisting decline in dopamine and cognitive capacity. Conclusions Divers encounter IGN at – 48 msw, exhibiting a marked loss in circulating dopamine levels, likely accounting for BDNF-dependent impairment of mental capacity and heightened OxS. The decline in dopamine and BDNF appears to persist at decompression; thus, boosting dopamine/BDNF signaling via pharmacological or other intervention types might attenuate IGN in deep dives.
Schematic overview of the experimental protocol and electrodes for neuromuscular electrical stimulation (NMES). VOL, vigorous voluntary exercise; VOLES, moderate-intensity voluntary exercise with superimposed neuromuscular electrical stimulation (NMES); PRE and POST, before and after training interventions, respectively
Representative original recording data of oxygen consumption (Upper panels) and heart rate (Bottom panels) from the groups of vigorous voluntary exercise (VOL) (Left panels) and moderate-intensity voluntary exercise with superimposed neuromuscular electrical stimulation (NMES) (VOLES) (Right panels). Gray and black lines indicate PRE and POST
Rating of perceived exertion (RPE) and heart rate (HR) during training sessions for vigorous voluntary exercise (VOL) and moderate-intensity voluntary exercise with superimposed neuromuscular electrical stimulation (NMES) (VOLES). The lines within boxes, boxes, and bars indicate median values, 25 and 75% quartiles, and range of data, respectively. * p < 0.05 between VOL and VOLES
Introduction Neuromuscular electrical stimulation (NMES) induces involuntary muscle contraction, preferentially promotes anaerobic metabolism, and is applicable for increasing exercise intensity. This study aimed to assess whether superimposing NMES onto moderate-intensity voluntary exercise imitates physiological adaptations that occur in response to vigorous voluntary exercise. Methods Eight participants trained with a cycling ergometer at 100% of the ventilatory threshold (VT) (73.3% of peak oxygen consumption) (VOL), and another nine participants trained with the cycling ergometer at 75% of VT (56.2% of peak oxygen consumption) with subtetanic NMES applied to the gluteus and thigh muscles (VOLES), matched to VOL training sessions, for nine weeks. Results Rating of perceived exertion (RPE) in VOLES (12.00 ± 1.50) was significantly lower than in VOL (14.88 ± 1.81) (p < 0.05) during training sessions. Peak power output during the exercise tolerance test was increased in VOL and VOLES following interventions. Oxygen consumption and heart rate (HR) at VT and blood lactate concentration (BLC) at < VT were decreased from before (PRE) to after (POST) training interventions for both VOL and VOLES. There were no significant differences in absolute changes from PRE to POST for peak power output and oxygen consumption, HR, and BLC at a submaximal intensity between VOL and VOLES. Conclusion Our results suggest that both superimposing subtetanic NMES onto moderate-intensity voluntary exercise and vigorous voluntary intensity exercise induce the improvement in cardiovascular and metabolic systems, but the adaptation of former method is provided without perceived strenuous exertion.
PurposeThis study attempted to clarify the relationships between marathon time and monthly training volume, training frequency and the longest (LRD) or average running distance per workout (ARD), as well as their interactions.Methods Male recreational runners (n = 587) participating in the Hokkaido Marathon 2017 completed a questionnaire before the race; of these, 494 finished the race. We assessed age, running career, body height, body weight, body mass index (BMI), monthly training volume, training frequency, the LRD and the ARD. These indicators were each divided into 4 or 5 homogeneous subgroups to determine whether the other indicators in each subgroup predicted marathon time.ResultsIn the training frequency subgroups, there were significant correlations between monthly training volume, the LRD or the ARD and marathon time, except for the subgroup that trained 2 times per week or less; in this subgroup, the relationship between the ARD and marathon time was not significant. In all monthly training volume subgroups, there were no significant relationships between training frequency, the LRD or the ARD and marathon time. In the ≥ 21 km LRD and ≥ 10 km ARD subgroups, there were significant correlations between monthly training volume and marathon time (all P < 0.01); these correlations were not significant in the 1–20 km LRD and < 10 km ARD subgroups.Conclusion These results indicate that monthly training volume is the most important factor in predicting marathon time and that the influence of monthly training volume is only significant if the running distance per workout exceeded a certain level.
Flowchart for the study. MCT: mixed circuit training; CTL: non-exercise control session
A–C Mean ± SD AC, br-PWV, and RI1,2 pre- and post-CTL and bouts of MCT, and the ICCs for the recovery from the two bouts of MCT. AC: arterial compliance; br-PWV: brachial-radial pulse wave velocity; RI1,2: reflection index; MCT: mixed circuit training; CTL: non-exercise control session; ICC2,1: intra-class correlation coefficient *: Significant difference between CTL vs. 1st MCT and 2nd MCT (P < 0.05). P-values indicate significant differences between pre- vs. post-intervention
Mean ± SD AASI after CTL and the 1st and 2nd bouts of MCT, and the ICC for the recovery from the two bouts of MCT. AASI: ambulatory arterial stiffness index; MCT: mixed circuit training; CTL: non-exercise control session; ICC2,1: intra-class correlation coefficient. *: Significant difference in the change from pre to post between CTL vs. 1st MCT and 2nd MCT (P < 0.05)
PurposeInvestigate whether a single bout of mixed circuit training (MCT) can elicit changes in arterial stiffness in patients with chronic stroke. Second, to assess the between-day reproducibility of post-MCT arterial stiffness measurements.Methods Seven participants (58 ± 12 years) performed a non-exercise control session (CTL) and two bouts of MCT on separate days in a randomized counterbalanced order. The MCT involved 3 sets of 15 repetition maximum for 10 exercises, with each set separated by 45-s of walking. Brachial-radial pulse wave velocity (br-PWV), radial artery compliance (AC) and reflection index (RI1,2) were assessed 10 min before and 60 min after CTL and MCT. Ambulatory arterial stiffness index (AASI) was calculated from 24-h recovery ambulatory blood pressure monitoring.ResultsCompared to CTL, after 60 min of recovery from the 1st and 2nd bouts of MCT, lower values were observed for br-PWV (mean diff = − 3.9 and − 3.7 m/s, respectively, P < 0.01; ICC2,1 = 0.75) and RI1,2 (mean diff = − 16.1 and − 16.0%, respectively, P < 0.05; ICC2,1 = 0.83) concomitant with higher AC (mean diff = 1.2 and 1.0 × 10–6 cm5/dyna, respectively, P < 0.01; ICC2,1 = 0.40). The 24-h AASI was reduced after bouts of MCT vs. CTL (1st and 2nd bouts of MCT vs. CTL: mean diff = − 0.32 and − 0.29 units, respectively, P < 0.001; ICC2,1 = 0.64).ConclusionA single bout of MCT reduces arterial stiffness during laboratory (60 min) and ambulatory (24 h) recovery phases in patients with chronic stroke with moderate-to-high reproducibility.Trial registration: identifier RBR-5dn5zd.
Time spent > 90%V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\text{V}}$$\end{document}O2max (a) and %V˙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{\text{V}}$$\end{document}O2max (b) during each 3 × 6 min bout for running (closed circle) and cycling (closed square) HIIT. Values are mean (bars; white = running, grey = cycling) and individual responses
Differential rating of perceived exertion (dRPE) for overall exertion (dRPE-O; closed circle), leg-muscle exertion (dRPE-L; closed square) and breathlessness (dRPE-B; closed triangle) during running and cycling HIIT sessions. Values are mean (bars; overall = grey, leg = white, breathlessness = diagonal) and individual responses. *denotes difference between exercise modes (p < 0.05)
MVC before and after running and cycling-based HIIT sessions. Values are mean (bars; running = grey, cycling = white) and lines are individual responses. *Indicates different to before value (p < 0.05)
Physiological responses to maximal running and cycling tests. Data are mean ± SD
Purpose The acute physiological, perceptual and neuromuscular responses to volume-matched running and cycling high intensity interval training (HIIT) were studied in team sport athletes. Methods In a randomized cross-over design, 11 male team sport players completed 3 × 6 min (with 5 min between sets) repeated efforts of 15 s exercising at 120% speed (s $$\dot{\text{V}}$$ V ˙ O 2max ) or power (p $$\dot{\text{V}}$$ V ˙ O 2max ) at $$\dot{\text{V}}$$ V ˙ O 2max followed by 15 s passive recovery on a treadmill or cycle ergometer, respectively. Results Absolute mean $$\dot{\text{V}}$$ V ˙ O 2 (ES [95% CI] = 1.46 [0.47–2.34], p < 0.001) and heart rate (ES [95% CI] = 1.53 [0.53–2.41], p = 0.001) were higher in running than cycling HIIT. Total time at > 90% $$\dot{\text{V}}$$ V ˙ O 2max during the HIIT was higher for running compared to cycling (ES [95% CI] = 1.21 [0.26–2.07], p = 0.015). Overall differential RPE (dRPE) (ES [95% CI] = 0.55 [− 0.32–1.38], p = 0.094) and legs dRPE (ES [95% CI] = − 0.65 [− 1.48–0.23], p = 0.111) were similar, whereas breathing dRPE (ES [95% CI] = 1.01 [0.08–1.85], p = 0.012) was higher for running. Maximal isometric knee extension force was unchanged after running (ES [95% CI] = − 0.04 [− 0.80–0.8], p = 0.726) compared to a moderate reduction after cycling (ES [95% CI] = − 1.17 [− 2.02–0.22], p = 0.001). Conclusion Cycling HIIT in team sport athletes is unlikely to meet the requirements for improving run-specific metabolic adaptation but might offer a greater lower limb neuromuscular load.
Example of a typical line of best fit for one of the study participants (boy, mass = 49.2 kg) from the first submaximal 20mSRT. The graph shows the strong linear relationship between exercise intensity (i.e., speed) and RPE. The line of best fit had an R² of 0.95. Predicted maximum speed according to the linear model equation at RPE 9 and 10 were 13.3 km h⁻¹ and 14 km h⁻¹, respectively. The actual maximum speed achieved in the maximal SRT for this boy was 13.5 km h⁻¹. Maximal treadmill speed from the GXT was also 13.5 km h⁻¹ with VO2 peak 53 mL kg⁻¹ min⁻¹
Affective responses (mean ± SE) for boys and girls, pre and end-test for all tests. GXT graded exercise test, sub-max.T1 submaximal 20-m Shuttle-run test (1st trial), sub-max.T2 submaximal 20-m Shuttle-run test (2nd trial), max.20mSRT maximal 20-m Shuttle-run test
Comparison of mean estimated VO 2peak from various predic- tion equations compared to the GXT
Purpose To determine the validity and test–retest reliability of using ratings of perceived exertion (RPE) elicited during a submaximal 20-m Shuttle Run Test (20mSRT) to predict VO 2peak in children and investigate acute affective responses. Methods Twenty-five children (14 boys; age, 12.8 ± 0.7 years; height, 162.0 ± 9.3 cm; mass, 49.9 ± 7.7 kg) completed four exercise tests (GXT, 2 submaximal 20mSRT, maximal 20mSRT). The Eston–Parfitt RPE scale was used, and affect was measured with the Feeling Scale. Submaximal 20mSRT were terminated upon participants reporting RPE7. The speed-RPE relationship from the submaximal 20mSRTs was extrapolated to RPE9 and 10 to predict peak speed and then used to estimate VO 2peak . Results Repeated measures ANOVA to examine the validity of using submaximal RPE to predict VO 2peak resulted in a Gender main effect (boys = 46.7 ± 5.1 mL kg ⁻¹ min ⁻¹ ; girls = 42.0 ± 5.1 mL kg ⁻¹ min ⁻¹ ) and Method main effect ( p < 0.01). There were significant differences between measured and estimated VO 2peak from the maximal 20mSRT, but not between measured and estimated VO 2peak at RPE9 and RPE10. Intraclass correlation analysis revealed excellent reliability (~ 0.9) between the two submaximal 20mSRTs. Significant differences ( p < 0.05) in end-test affect were reported between submaximal and maximal trials in girls, but not in boys, with girls feeling less negative at the end of the submaximal trials. Conclusions The results of this study provide evidence that RPE reported during a submaximal 20mSRT can be used to predict VO 2peak accurately and reliably. In this study, the submaximal 20mSRT ending at RPE7, provided better predictions of VO 2peak while minimising aversive end-point affect, especially in girls.
Top-cited authors
Nicola Maffiuletti
  • Schulthess Clinic, Zürich
Martin Buchheit
  • Paris Saint Germain Football Club
Peter Krustrup
  • University of Southern Denmark
Anthony J Blazevich
  • Edith Cowan University
Michael Bemben
  • University of Oklahoma