Muscle pre-activation using photobiomodulation attenuates slow component amplitude during running in heavy domain

doi:10.21203/rs.3.rs-4946944/v1

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Muscle pre-activation using photobiomodulation attenuates slow component amplitude during running in heavy domain

https://doi.org/10.21203/rs.3.rs-4946944/v1

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Photobiomodulation (PBM) using light emitting diode (LED) or laser sources has been associated with physical exercise, affecting positively the uptake, transportation, and use of oxygen (O₂). Therefore, the objective of the present study was to verify the effect of PBM with application of LED on the response of the fundamental and slow components of the oxygen uptake (V̇O₂) kinetics during the rest-to-work running exercise transition in heavy domain. Twenty-six healthy, physically active, young men, aged between 20 and 30 years volunteered to take part in this study. Participants performed a maximal incremental running tests on a motorized treadmill to determine the gas exchange threshold and maximal oxygen uptake (V̇O_2max) and using these data they went through two running conditions on square wave transitions in a heavy intensity domain: placebo (PLA) and LED. For each square wave test, heart rate (HR), rating of perceived exertion (RPE) and gas exchanges were monitored. PLA and LED conditions were compared using the dependent Student t-test, using the statistical significance was set at P < 0.05. The main results showed an increase in V̇O₂, reduction in RPE and HR during heavy intensity constant exercise performed after the application of LED, when compared to the placebo condition. Furthermore, the analysis of V̇O₂ kinetics also showed the reduction in the contribution of the V̇O₂ slow component in response to the intervention with LED. In conclusion, LED induced ergogenic effect for the aerobic performance on the heavy domain.

Phototherapy

Light Emitting Diodes

Treadmill Running

Oxygen Uptake Kinetics

Aerobic Exercise

Photobiomodulation (PBM) using light emitting diode (LED) or laser sources has been widely associated with physical exercise, affecting positively the system of uptake, transportation, and use of oxygen (O₂), due to prior modulation on oxidative metabolism enzymes during the electron transport chain and improvements in peripheral perfusion [1–4]. These changes resulted in an increase absolute and relative maximal oxygen uptake (V̇O_2max) during progressive exercise, in healthy adult and athletes, better cardiovascular efficiency and greater speed of adjustment in the O₂ supply/demand relationship at the beginning of exercise performed in severe intensity domain [1, 5].

The change in physical performance during sustainable high-intensity exercise (i.e., heavy exercise, or above the lactate/ventilatory threshold) is associated with the speed of integration between the functions of the pulmonary and muscular cardiovascular systems in an attempt to increase peripheral diffusion and tissue perfusion of O₂, as well as the adjustment of the oxidative system to muscular energy demand, that is reduction of metabolic inertia [6].

Such adjustments, when described by V̇O₂ kinetics, would reflect a succession of events underlying the delay of fatigue process, such as lower O₂ deficit at the beginning of the rest-exercise transition (due to the time and amplitude of the response of the fundamental component – A₁'), latter recruitment of type II fibers with low oxidative efficiency and maintenance of blood lactate concentration under control, but high (due to the time and amplitude of the response of the slow component, CL), mainly during exercise in the heavy domain [6, 7].

Different intervention protocols failed to observe significant changes in the adjustment speed and amplitude of the A₁' component response resulting from a lower oxidative inertia, whether due to acute physiological modulations (previous exercise) or modulating substances such as nitric oxide [8–10]. However, the modulation of O₂ perfusion and diffusion appears to be less, but satisfactorily associated with changes in A₁' and CL responses, probably by favoring a greater participation of type I fibers in the rest-to-work exercise transition both in the heavy and severe domain [6, 7].

Therefore, the objective of the present study was to verify the effect of PBM with application of LED on the response of the fundamental and slow components of the V̇O₂ kinetics during the rest-to-work running exercise transition in heavy domain. Given the effects of PBM application on peripheral vasodilation, O₂ dissociation and enzymatic activity in mitochondria, it is assumed that this intervention will tend to modify the response time of oxidative metabolism, therefore highlighting the applicability of LED in modulate tolerance during high intensity aerobic exercise of by accelerating the fundamental component and reducing the amplitude of the slow component.

Subjects

Twenty-six healthy, physically active, young men, aged between 20 and 30 years volunteered to take part in this study. The characteristics of the subjects were (mean ± SD): age 27.8±1.7 years, body weight 78.6±9.1 kg, height 178.1±5.9 cm, body mass index (BMI) 24.9±2.4 kg·m^-2 and body fat 17.5±4.0 %. Inclusion criteria included the absence of any previous lower limbs’ musculoskeletal injury in the previous three months, the use of any kind of anti-inflammatory medicine, nutritional supplements, or pharmacological agents with ergogenic effect, and undertake systematic running training.

Compliance with ethical standards

The Human Research Ethics Committee of State University of Maringá approved this study (#147362/2012, CAAE 08636412.5.000.0104). All research was conducted ethically according to the Helsinki Declaration. Each participant was informed of the risks and benefits of participation and signed written informed consent documentation before participating., they were free do abandon the study at any time, without any onus or bonus.

Design

The participants had anthropometric variables measured by a single evaluator with expertise in such assessments. Body weight and height were measured using standardized procedures and body fat was determined by the seven folds equation by Jackson and Pollock [11]. Prior to testing, written informed consent was obtained from all participants. The experimental protocol was approved by the university’s ethics committee (#147.362/2012).

Participants underwent to the climate laboratory (temperature = 20–22°C and relative humidity = 50–60%) four times, on different days and at the same time of the day, for familiarization with the motorized treadmill, one incremental load test to determine the parameters for two square wave testes in the experimental conditions: placebo (PLA) and LED application.

The experimental conditions were performed in random order with double blind control and the assistance of a second researcher turning the device on or not for energy emission. During the LED sessions subjects remained seated, and to avoid the identification of the experimental condition by means of audible or visual signals emitted by the device the subjects were blindfolded and used headphone.

The minimum interval between tests were 48 and the maximum 72 hours for a maximum period of two weeks. Participants were instructed to follow the same nutritional routine and abstain from alcohol and stimulating drinks the 24 hours prior to testing, and avoid strenuous exercise during the project period.

Incremental test and metabolic measurements

The incremental and square wave running tests were performed on a motorized treadmill (Super ATL Inbrasport^®, Porto Alegre, Brazil), with the gradient set at 1%. For the incremental test, after a warm-up that consisted of walking at 6 km·h^-1for 3 min, the protocol started with an initial speed of 8 km·h^-1, followed by an increase of 1 km·h^-1every 3 min between each successive stage until volitional exhaustion. Consistently across each trial, participants were strongly encouraged, verbally, to invest maximum effort [12].

Gas exchange was monitored throughout the test with data collected breath by breath (Quark^®PFT, Cosmed, Italy). V̇O₂ data were reduced to 15-s average intervals to determine the submaximal V̇O₂(V̇O_2sub), and the highest value obtained during the incremental test, within these intervals, was considered the V̇O_2max. The first intensity in which V̇O_2maxoccurred was considered the V̇O_2maxvelocity (vV̇O_2max) [13].

The observation of the V̇O₂plateau at the end of the incremental test was considered to establish the occurrence of V̇O_2max¹³. If the phenomenon has not been observed, the maximal effort and V̇O_2max was deemed to be achieved if the incremental test met two of the following criteria: (1) peak lactate concentration (LA_peak) ≥ 8 mmol·L⁻¹, (2) maximal heart rate (HR_max) within ± 10 beats·min⁻¹ of age-predicted HR_max (206 – (0.7·age))and (3) peak rating of perceived exertion (RPE_peak) ≥ 19 in the 6–20 Borg scale [14, 15].

The gas exchange threshold (GET) was determined by the ventilatory equivalent method, considering an increase in O₂ equivalent (V̇E·V̇O₂^-1) and PETO₂ with no increase in CO₂equivalent (V̇E·V̇CO₂^-1) and PETCO₂, and by the excess CO₂ method, intensity that occurred a non-linear increase in carbon dioxide production (V̇CO₂₎[16].

Square wave test and PBM protocol

The determination of the individual exercise intensity for heavy domain trial performance was established from 50%Δ using the following equation [17]:

v50%Δ = vGET + 0.50 × (vV̇O_2max – vGET)

For each experimental condition (PLA and LED) two square wave transitions of six minutes and 50%Δ intensity were performed, with a passive rest interval between them (BURNLEY et al., 2006). HR, RPE and gas exchanges were monitored during the two transitions.

Before each test, the QuarkPFT gas analyzer (Cosmed^®, Italy) was calibrated with ambient air and constant concentration of O₂(16%) and CO₂ gas (5%), whereas the bi-directional turbine (flow meter) was also calibrated using a 3-L syringe, following all the manufacturer’s recommendations.

The V̇O₂ breath-to-breath data from each transition of the square wave tests were smoothed to three breathing points and manually filtered to remove V̇O₂ outliers’ points. These data were later linearly interpolated to obtain values with each second intervals (total of 360 seconds). Then, the data referring to the two transitions were aligned, and the averages for the V̇O₂ values were calculated with the aim of accentuating the fundamental characteristics of the physiological responses.

The first 20 seconds of data after the start of the exercise, representing the cardiodynamic phase, were excluded from the analysis. A non-linear least squares algorithm was used to fit the data, as described by the equation below [17]:

V̇O₂ (t) = V̇O_2base+ A₁x (1 – e ^–(t-TA)/^τ)

Being, V̇O₂ (t) the absolute V̇O₂ in a given time t; V̇O_2base the 30-second average of V̇O₂ in the baseline period; A₁ is the amplitude; TA is the delay time; and τ is the time constant.

A process of interactions was used to minimize the sum of squares error between the fitted function and the observed values, and the fitting window was restricted to the moment when a fundamental departure from nonexponentiality occurred, as judged by visual inspection of a portion of the adjustment residues [17]. The primary absolute amplitude (A₁’) was defined as the sum of V̇O_2baseand A₁. The final V̇O₂ of the transition (V̇O_2final) was defined as the average of 30 seconds of V̇O₂ measured at the end of each transition. A₂’ was calculated as the difference between the primary absolute amplitude and the V̇O_2final. The relative contribution of A₂’ to the net increase in V̇O₂ at the end of the exercise (%A₂’) was also calculated:

% A₂’ = A₂’/(A₁+ A₂’)x100

The net V̇O₂ value obtained in these tests was also determined, subtracting the V̇O_2base from the V̇O_2final, and the percentage of the final V̇O₂ compared to the V̇O_2max obtained during the maximum incremental test.

Before testing, participants were familiarized with the 6–20 Borg scale [15], which was used to measure the rating of perceived exertion (RPE) during the last 10 s of each stage and at exhaustion during the incremental test and every minute during the square wave test. Heart rate (HR) was recorded throughout the tests (Polar^® RS800sd, Kempele, Finland) and the data was reduced to 15 s intervals to determine maximal and submaximal HR values.

The LED protocol had total time of two minutes and 30 seconds (30 s per point, with application in both legs simultaneously), the same procedures were used in the PLA and LED conditions, respecting the presence or absence of light emission for each condition. The irradiation intervention started five minutes before the square wave test, in contact mode with the LED cluster held stationary with slight pressure at a 90º angle to the skin at each of the five treatment points [1-3,5].

The application was carried out in two points of the quadriceps muscle, two points of the femoral biceps muscle and one point of the gastrocnemius muscle, along the distribution axis of muscle fibers in both legs [18,19]. It was used the LED equipment THOR^® brand, with two clusters of 104 infrared (850 nm) LED diodes each, with power output of 30 mW, power density of 150 mW·cm^-2, total energy irradiated of 93.6J per cluster and energy density of 4.5 J·cm^-2.

Statistical procedures

Data are presented as mean ± SD and were analyzed using the Statistical Package for the Social Sciences 15.0 software (SPSS^® Inc., USA). The Shapiro-Wilk test was used to check the normality of the data distribution. The PLA and LED conditions were compared using the dependent Student t-test and the correlation matrices by the Pearson correlation test. As complementary analysis the effect size (ES) was calculated to determine the magnitude of change in each condition using the following equation:

ES = (M1-M2) ÷ ((SD1+SD2) ÷ 2)

Note: M1 and M2 the average of each condition, SD1 and SD2 the respective standard deviations. The ES was classified according to Cohen [20] as: ≤ 0.20 (trivial), between 0.21 and 0.50 (small), between 0.51 e 0.80 (moderate) and > 0.80 (large). For all analysis the statistical significance was set at P < 0.05.

In the incremental test, subjects presented V̇O_2max of 47.2 ± 5.7ml·kg^-1·min^-1, vV̇O_2max of 13.0 ± 1.3 km·h^-1and HR_maxof 195.3 ± 3.4 b·min^-1. Figure 1 shows the RPE values every 60 seconds, HR and V̇O₂ every 15 seconds of the square wave load tests in the LED and PLA conditions. The variables are presented based on the average of the values of the two transitions for each condition. The reported PSE values presented differences for the two conditions in the six evaluation moments, with lower values for the LED condition compared to the PLA condition; the LED condition also presented lower numerical HR values during the six minutes of the square wave load test, however, statistical differences between conditions were not found between 45 and 75 seconds, 210 and 240 seconds; in turn, V̇O₂ presented higher values for the LED condition compared to the PLA, with statistical differences between the conditions between 105 and 255 seconds of the square wave test.

Figure 1. Mean ± standard deviation values of oxygen uptake (V̇O₂), rating of perceived exertion (RPE) and heart rate (HR) of the first and second transition of the six-minute square wave load test for the LED therapy (LED) and Placebo conditions (PLA) (n = 26). * P < 0.05 between conditions.

Table 1 presents the data referring to the oxygen uptake kinetics analysis obtained during a six-minute square wave load test in a heavy effort domain, for the PLA and LED conditions. The statistical analysis showed a difference between conditions only for absolute (A₂’) and relative (A₂’%) values of the slow component, in addition, the complementary analysis demonstrated a small effect size (0.39) between conditions for the time of start of A₂’(TA₂). In neither of the two conditions V̇O_2max was reached during constant efforts, with mean V̇O_2final values being recorded between 93.3 and 92.9% of V̇O_2max for the PLA and LED conditions, respectively.

Table 1. Comparison and effect size (ES) of the oxygen consumption kinetics analysis variables obtained during the square wave test for the placebo (PLA) and LED therapy (LED) conditions.

Square wave test	PLA (n = 26)	LED (n = 26)	P	ES
VO_2base(ml· min^-1)	822.0 ± 240.6	833.0 ± 235.2	0.780	0.05
A₁(ml·min^-1)	2342.3 ± 436.2	2389.0 ± 329.1	0.365	0.12
τ (s)	32.5 ± 5.8	32.2 ± 5.3	0.806	0.04
TA₁(s)	2.7 ± 1.5	3.0 ± 1.5	0.476	0.17
A₁’(ml·min^-1)	3152.8 ± 433.4	3214.1 ± 373.7	0.124	0.15
TA₂(s)	190.4 ± 22.3	199.7 ± 24.7	0.057	0.39
A₂’(ml·min^-1)	311.8 ± 120.8	262.4 ± 99.3	0.038	0.45
A₂’%	11.8 ± 4.1	9.9 ± 3.5	0.036	0.49
VO₂_net(ml·min^-1)	2642.5 ± 467.1	2643.5 ± 417.3	0.983	0.01
VO_2final(ml·min^-1)	3462.1 ± 470.2	3480.3 ± 377.7	0.687	0.04
V̇O₂_máx%	93.3 ± 6.0	92.9 ± 5.7	0.777	0.07

Note. A₁ and A₁’_’: primary absolute amplitude with y = 0 e y = V̇O_2base, τ: time constant, TA₁ and TA₂: delay times, A₂’ and A₂’%: amplitude of the slow component expressed in absolute and relative values, V̇O_2final: Average of the final 15 seconds of the 6-minute square wave load test, V̇O_2net: V̇O_2final minus V̇O_2base, V̇O_2max%: Percentage of V̇O_2finalin relation to V̇O_2maxobtained in maximum incremental test.

P < 0.05

The correlation matrices of the variables resulting from the analysis of the oxygen consumption kinetics for the experimental conditions demonstrate that A'₁ presented a high correlation with V̇O_2final(r = 0.97 and 0.97, respectively for PLA and LED) and V̇O_2net(r = 0.82 and 0.75, respectively for PLA and LED). However, only in the PLA condition A₂’ significantly correlate with V̇O_2final (r = 0.42) and V̇O_2net (r = 0.42), demonstrating less dependence on A’₂ for the LED condition. The correlations between the experimental conditions were high for the variables V̇O_2final (r = 0.88), V̇O_2net (r = 0.84) and A₁’ (r = 0.89), but the delay times (r = 0.30 and 0.50, respectively for TA₁ and TA₂) and the amplitudes of the absolute (r = 0.47) and relative (r = 0.37) slow component did not show significant correlations. This demonstrates a significant deviation between the conditions depending on the application of LED for these variables.

The objective of the present study was to verify the effect of LED on V̇O₂ behavior during square wave running tests. The main results showed an increase in V̇O₂, reduction in RPE and HR during heavy intensity constant exercise performed after the application of LED, when compared to the placebo condition. Furthermore, the analysis of V̇O₂ kinetics also showed the reduction in the contribution of the V̇O₂ slow component in response to the intervention with LED.

Studies have been described many types of interventions and different physiological responses that might influence V̇O₂ response during heavy-intensity exercise performance (7-10). The first interventions were based on the hypothesis that the supply (perfusion) of O₂ would alter the V̇O₂ kinetics, with evidence that physical exercise performed under hyperoxia conditions showed a lower O₂ deficit, accelerated A₁’ kinetics and lower A₂’ and, on the other hand, physical exercises performed with induced reductions in O₂ transport capacity slow the primary phase of V̇O₂ kinetics [21, 22].

In this context, the physiological modulation of PBM would explain the responses observed in the LED group compared to PLA in the current findings, referring to the smaller contribution of A₂’ to the net increase in V̇O₂ and reduction in the explanatory power of A₂’ for the final V̇O₂ increases of the PLA (18%) compared to the LED group (4%). One of the PBM responses that could be associated with greater oxygen availability, even lasting just a few minutes after light application, is the augment in vasodilation due to the increased microcirculation and hyperemia in the site of application, which might further affect aerobic metabolism as a consequence of the increased circulatory response [3, 4].

Few other studies showed the increase in the availability and uptake of oxygen during aerobic exercises after the intervention with LED. Therefore, a gain in blood transport and oxygen supply to muscle cells can be accounting to the increased V̇O₂ response during exercise, and consequently the response of V̇O₂ kinetics in the rest–to-work exercise transition [1, 5, 10, 18, 19].

There are, however, other physiological responses influencing V̇O₂ kinetics, such as previous exercise, which might affect muscular performance by increase A'1 response and a reduce the contribution of A₂’. Despite V̇O₂ returns to baseline values in the first few minutes after a priming exercise intervention, the residual effect on V̇O₂kinetic parameters remains altered, gradually reducing in the first hour after exercise. Therefore, not only the higher availability of O₂, but also other factors, especially peripheral ones, are described as factors accounting to the respiratory response, such as: changes in enzymatic activity, body temperature, blood lactate concentration, oxygen dissociation -hemoglobin, and especially the recruitment pattern of muscle fibers [10, 16, 17].

The assumptions underlying these physiological inferences were the delayed activation of type II muscle fibers, which is directly associated with the delayed onset of A₂’. As well as with the amplitude of this component, and indirectly related to the contribution of A₁’ to the total V̇O₂kinetic time; and that, on the other hand, the percentage of type I fibers active in the vastus lateralis muscle during exercise was negatively correlated with the magnitude of A₂’ [6, 8, 9, 10].

The present study demonstrated that the physiological effects of LED intervention can be similar to those reported for previous exercise session in muscle pre-activation, modifying respiratory behavior at the beginning of exercise. These effects are based especially on the higher energy availability due to the acute and chronic increase in ATP synthesis via lactic and alactic metabolic pathways. It has already been demonstrated that the enzymatic activity of all complexes of the mitochondrial electron transport chain, and enzymes related to aerobic metabolism such as SDH and NADH, and of CK in the reconversion of phosphocreatine are all increased after the application of PBM, ensuring a higher rate of ATP synthesis through oxidative metabolism for a longer period [23].

Francescato et al. [24] verified the role of the kinetics of phosphocreatine degradation in the V̇O₂kinetics, and found a mirror behavior (inverse correlation) of these variables at the beginning of exercise, with an explanation of more than 60% between the time constant of A₁’ and the degradation of phosphocreatine. This result was attributed to the fact that at the beginning of physical exercise the metabolic adjustment at the muscular level is essentially dependent on local factors, and thus has a greater relationship with the type of muscle fiber primarily required, than with central factors such as cardiac output.

This extra capacity for energy production via aerobic routes and maintenance of high phosphocreatine stores allows greater activation of type II muscle fibers to be avoided, making complementary activation or greater metabolic dependence on ATP resynthesis via anaerobic pathways late. In the analysis of respiratory response carried out in the present study, this may mean less dependence of A₂’ on the net increase in V̇O₂ and consequently an accelerated V̇O₂ kinetics in the LED effort condition.

This effect becomes more plausible when observing the greater sensitivity of oxidative muscle tissues to the biomodulatory activity of phototherapy , especially in the enzymatic activity of complex IV of the electron transport chain (cytochrome c oxidase), which presents an increase of 18% for type II muscle fibers, and up to 54% for type I muscle fibers. Furthermore, it appears that, very similar to the effect of training itself physical, phototherapy favors a higher rate of fat acid oxidation in active muscle [23].

Information on the effect of PBM on V̇O₂ kinetics is limited, as in addition to the present study, only Ferraresi et al. [5] investigated a single Brazilian elite runner (V̇O_2max = 67.6 ml·kg^-1·min^-1) and their results showed accelerated A₁’ (PLA = 32 s; PBM = 24 s) and higher A₂’ (PLA = 220 ml; PBM = 415 ml) in the PBM condition compared to placebo.

These results partially corroborate those of the present study, however, Ferraresi et al. [5] used intensities in the severe domain of exercise to analyze respiratory responses, and in this high intensity exercise level the possibility of predominant activation of oxidative muscle fibers is reduced when compared to the heavy intensity domain that was used in the present study, hence increasing the anaerobic demand of exercise and minimizing the chance of evident effects of PBM on V̇O₂ kinetics. Furthermore, the analysis of a single subject does not allow conclusions that can be generalized for other runners or extrapolated for other exercises.

Cardiovascular changes were also evident, with reductions of six beats per minute on average, in addition to significantly lower values during 2/3 of the performance test in the LED condition compared to the same instant in the PLA condition. Possibly, this reduction in cardiovascular work can be attributed to the vasodilatory effect of nitric oxide produced in response to the application of heat, in addition to responses related to better autonomic adaptations of HR [1, 3, 4, 5].

Alves et al.(18) found improvements in cardiovascular efficiency compared to the placebo condition, through the linear relationship between HR and V̇O₂ (Laser = 56 ± 24 and PLA = 66 ± 30 b·L^-1·min^-1), also relating this response to circulatory effects sites, with greater vascularization promoted by vasodilation and the emergence of new capillaries. This reduction of 10 b·L^-1·min^-1 suggests gains in cardiovascular efficiency as an indication of better supply and/or extraction of O₂ after the application of LED, a response that is dependent on an increase in systolic cardiac volume or in the extraction of O₂ by the peripheral muscles. Despite the study by Alves et al. [18] did not use any methodology to quantify these variables, it was suggested that PBM essentially improved the peripheral muscle capacity for O₂extraction since an acute improvement in stroke volume is unlikely to have occurred.

The reduction in HR and increase in V̇O₂ specifically described by the present study in the LED group compared to PLA, strengthen the responses of greater peripheral V̇O₂ efficiency of the active muscles in submaximal efforts, directly related to the reduction in cardiac work.

After LED intervention were also found larger reduction in RPE response, when compared to the same moments of measurement in the PLA condition. Few studies have verified the effect of PBM on RPE [1, 2]. The Borg 6-20 scale [15] was first designed to be used during aerobic incremental load tests (cycle ergometer, with load increments of four to six minutes), since the scale with numerical anchors and their descriptors provides responses that increase linearly depending on aerobic demand: intensity and time of effort, HR and V̇O₂; with the amplitude of numerical responses between 6 and 20 strongly corresponding to the maximum HR amplitude of a healthy young adult, between 60 and 200 bpm. The HR response pattern after applying the LED measured in the present study, linearly modified by the intensity and duration of the rectangular and incremental load tests, was similar to the RPE, suggesting that the Borg scale 6-20 is sensitive to changes in aerobics demands and consequently to the effects of phototherapy.

Based on these fundamental responses of PBM on cardiorespiratory and psychophysiological parameters, it is possible to state that exercise tolerance is increased during running exercise performed in a heavy domain, generating positive acute responses and maintained even through two effort transitions.

The results of the present study indicate that LED can induce ergogenic effect on the aerobic performance during heavy domain efforts, and it can be detected by RPE, HR and V̇O₂responses_..

Clinical trial number: not applicable.

Conflicts of interests: The authors have no competing interests (financial ou non-financial) to declare that are relevant to the content of this article.

Ethical approval: The Human Research Ethics Committee of State University of Maringá (CEP-UEM) approved this study (#147362/2012, CAAE 08636412.5.000.0104). All research was conducted ethically according to the Helsinki Declaration. Each participant was informed of the risks and benefits of participation and signed written informed consent documentation before participating., they were free do abandon the study at any time, without any onus or bonus.

Funding Declaration: No funding was received for conducting this study.

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Muscle pre-activation using photobiomodulation attenuates slow component amplitude during running in heavy domain

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