Sage Journals: Discover world-class research

Abstract

BACKGROUND:

While interval training is considered an effective modality for improving performance, its effectiveness among athletes may be influenced by previous training experience.

OBJECTIVE:

To investigate whether differences in training background are reflected in the development of exercise capacity and level of muscle damage following a single bout of repeated maximal sprints after an 8-week intervention of high-intensity interval training (HIIT), sprint interval training (SIT), and endurance training (ET).

METHODS:

Three groups of male cyclists were studied: E1 ( $n=$ 10) included cyclists with a background in high-volume moderate-intensity training, E2 ( $n=$ 7) comprised cyclists with low-volume high-intensity training experience, and C ( $n=$ 7) served as a control group with an identical training background as E1. During 8-week intervention HIIT, SIT, and ET were performed by cyclists in group E1 and E2, group C performed only ET. At pre- and post-intervention, cyclists performed two exercise tests: 1) incremental testing protocol (ITP) to assess maximal oxygen uptake (VO ${}_{2}$ max) and maximal power (Pmax); and 2) sprint interval testing protocol (SITP) to determine oxygen uptake (VO ${}_{2})$ , work, and change in creatine kinase ( $\Delta$ CK) and myoglobin ( $\Delta$ Mb) levels.

RESULTS:

After intervention, VO ${}_{2}$ max increased in E1 and E2 group although Pmax increased only in E1. During post-intervention sprint interval testing protocol, VO ${}_{2}$ and work increased only in E1, whereas $\Delta$ CK and $\Delta$ Mb decreased in E1 but increased in E2.

CONCLUSIONS:

A history of high-volume moderate-intensity training can induce beneficial performance adaptations by reducing muscle damage and allowing greater work output. It is suggested that interval training be preceded by a longer period of high-volume training in athletes.

Keywords

Interval training work creatine kinase myoglobin

1. Introduction

Sprint interval training (SIT) and high-intensity interval training (HIIT) are known as two potent exercise strategies in the development of aerobic and anaerobic capacity [1, 2, 3]. The former involves several bouts of short maximal intensity exercise (Cca. 30 s) separated by recovery intervals of 15 s–4 min duration [4, 5, 6]. In the latter, the repeated exercise is either performed for several minutes at an intensity exceeding 90% maximal oxygen uptake (VO ${}_{2}$ max) [1] or with repeated efforts at an intensity above the ventilatory threshold [2]. The well-documented effects of these training modalities in high-performance athletes include significant increases in VO ${}_{2}$ max [6, 7], maximal power output during incremental exercise testing [6, 7], power output on metabolic thresholds [6], performance in individual time trials [7, 8], and performance in cycling races [9]. One study by the present authors [10] revealed greater improvements in VO ${}_{2}$ max ( $\approx$ 15%) and maximal power output ( $\approx$ 10.4%) during incremental test among well-trained mountain bike (MTB) cyclists than those reported in comparable studies that administered an exclusive HIIT or SIT intervention ( $\approx$ 3–8%) [1, 6, 7]. In Hebisz et al. [10], the authors administered the 8-week training intervention that involved a microcycle of SIT, HIIT, and steady-state endurance training. While most of the available studies assess the effects of one type of interval training [7, 8, 9]. It is possible that an exercise protocol consisting of both HIIT and SIT may induce enhanced training adaptations compared with one modality alone. HIIT that involves several minutes of exercise at an intensity above 90% VO ${}_{2}$ max is known to increase cardiac output and stroke volume [1, 10, 11, 12] whereas the concomitant application of SIT may have provoked changes in skeletal muscle oxidative capacity [13]. Many of these adaptations are associated with stimulated angiogenesis; increased mitochondrial biogenesis via the peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1 $\alpha$ ) and AMP-activated protein kinase (AMPK) activation; and increased maximal oxidative enzyme activity including citrate synthase, beta-hydroxyacyl-CoA-dehydrogenase, cytochrome oxidase, pyruvate dehydrogenase, and malate dehydrogenase [3].

In addition to limited information on the combination of different interval modalities, there is lack of documented evidence on the effects of athlete training background. The most majority of interval training studies have stratified their population samples according to VO ${}_{2}$ max levels by distinguishing groups such as elite athletes ( $>$ 70 ml $\cdot$ min ${}^{-1}\cdot$ kg ${}^{-1}$ ), highly trained athletes (60–69 ml $\cdot$ min ${}^{-1}\cdot$ kg ${}^{-1}$ ), well-trained athletes (50–59 ml $\cdot$ min ${}^{-1}\cdot$ kg ${}^{-1}$ ), and sedentary individuals ( $<$ 50 ml $\cdot$ min ${}^{-1}\cdot$ kg ${}^{-1}$ ) [2]. According to this classification of aerobic capacity, studies have found that SIT or HIIT elicit greater improvements in VO ${}_{2}$ max among sedentary individuals ( $\approx$ 10–15%) [14, 15, 16] than trained cyclists ( $\approx$ 5%) [17] or well-trained cyclists or triathletes ( $\approx$ 3–8%) [7]. While research has included a wide range of study populations, a literature review revealed no works that have stratified a sample according to such characteristics as exercise intensity, volume and training history.

Despite many beneficial changes induced by interval training, several negative effects have been identified with muscle damage as the most prominent [18]. It is worth noting that significant exercise-induced muscle fiber damage can result from not only interval training but steady-state exercise performed at moderate or high intensity [19]. Research also suggests that muscle fiber damage is a necessary precursor for the onset of important physiological adaptations [20]. In the literature, some biochemical markers of muscle damage are increased myoglobin concentration (Mb) and creatine kinase activity (CK) in blood plasma following exercise [21, 22]. Interestingly, current findings suggest that eccentric muscular contractions induce greater increases in Mb and CK than concentric contractions [23] and that Mb and CK can also be triggered by increased oxidative stress [21]. However, it is unclear what changes occur to Mb and CK during SIT-based exercise particularly among trained athletes with varied training backgrounds (different macrocycle volume and intensity). This is of interest as many coaches continue to apply the Matveyev model of training periodization [24], in which training progresses from a low-intensity high-volume phase to a high-intensity low-volume phase. This model theoretically would best prepare the athlete for the high loads entailed in interval training. However, there is a modicum of scientific evidence for this model particularly among advanced athletes [24]. An assessment of the acute changes in serum Mb and CK in response to SIT should show the degree of experienced muscle damage among athletes with different training backgrounds. Furthermore, interval training has been strongly promoted as a time-efficient exercise strategy that induces enhanced adaptations compared with longer-duration and more monotonous endurance training [3]. However, little attention has been paid to whether the participant or athlete can tolerate the high loads of SIT, again suggesting the need for research on the effects of this training modality on muscle damage.

Table 1
Anthropometric and physiological characteristics of groups E1, E2, and C

Group	Age [years]	Height [cm]	Mass [kg]	VO ${}_{2}$ max [ml $\cdot$ kg ${}^{-1}\cdot$ min ${}^{-1}$ ]	Pmax [W]
E1	21.7 $\pm$ 6.6	179.5 $\pm$ 6	70.2 $\pm$ 9.9	57.4 $\pm$ 3.4	369.5 $\pm$ 42.5
E2	21.2 $\pm$ 4.8	176.4 $\pm$ 5.2	67.4 $\pm$ 8.6	58.6 $\pm$ 5.9	349.3 $\pm$ 26.5
C	20.2 $\pm$ 4.3	176.5 $\pm$ 5.8	68.4 $\pm$ 9.1	55.4 $\pm$ 7.2	345.6 $\pm$ 44.2

VO ${}_{2}$ max – maximal oxygen uptake in an incremental testing protocol, Pmax – maximal aerobic power in an incremental testing protocol; data are presented as mean $\pm$ standard deviation.

Figure 1.

Scheme of the experiment (SIT – sprint interval training; HIIT – high-intensity interval training; CET – continuous endurance training; VET – varied-intensity endurance training; ITP – incremental testing protocol; SITP – sprint interval testing protocol).

In light of the above, the aim of the study was to determine the effects of a concomitant SIT, HIIT, and continuous endurance training (CET) intervention on maximal aerobic power and VO ${}_{2}$ max in relation to prior training background. Another goal was to determine if differences in training background would be reflected in the level of muscle damage in response a single dose of SIT. It was hypothesized that athletes with greater training experience in high-volume exercise would be subject to less muscular damage and present better post-intervention improvements in exercise performance.

2. Materials and methods

2.1 Participants

This study design was approved by the institutional ethics committee and all procedures were performed in accordance with the Declaration of Helsinki. Twenty-four male mountain bike (MTB) cyclists were recruited with a minimum of 2 years competitive experience in their respective racing format. Written informed consent was obtained after the procedures were fully explained. Previous training characteristics (heart rate and power output) over a 3-month period prior to study outset were collected from previously saved training records using the Garmin Connect system (Garmin Ltd.,USA). Participant exercise history was then determined and the cyclists were assigned to either one of two experimental groups (E1: $n=$ 10; E2: $n=$ 7) or a control group (C: $n=$ 7). Group E1 was composed of cyclists who executed a relatively high-volume training regime at moderate intensity. In this group, weekly training volume was 14–16 hours, of which 7% was performed at 65–70% of maximal heart rate (HRmax), 85% at 70–80% HRmax, 5% at 80–85% HRmax, and 3% above 85% HRmax. Group E2 included cyclists who executed relatively low-volume training at high intensity. Weekly training volume was 7–9 hours, of which 15% of exercise was performed at 65–70% HRmax, 21% at 70–80% HRmax, 62% at 80–90% HRmax, and 2% above 90% HRmax. Group C involved cyclists who shared an identical training profile as group E1 (high-volume training at moderate-intensity) but served as a control group and were not subject to any intervention or training modifications during the study duration. Group characteristics are presented in Table 1.

2.2 Procedures

The duration of the training intervention was 8 weeks (shown in Fig. 1). HIIT, SIT, and CET were concomitantly executed by E1 and E2. SIT was performed twice a week. Each SIT session involved 12 to 16 repetitions of 30-s maximal intensity cycling with four repetitions constituting one set. Each repetition was interspersed with 90 s of low-intensity cycling not exceeding 30 W. A recovery period was provided between each set in which the first 2 min were performed at an intensity corresponding to 30% maximal aerobic power (determined during an incremental test) followed by 20 min of cycling at 50% maximal aerobic power and then 3 min of cycling at 15% maximal aerobic power. HIIT was performed once a week and involved 5 to 7 cycling bouts of 5 min performed at an intensity 85–95% maximal aerobic power with recovery intervals between each repetition performed at 45–50% maximal aerobic power for 10–15 min. The CET modality was performed twice a week and involved 120–180 min of cycling at an intensity of 70–80% HRmax.

Participants in group C continued their existing training regime based on two endurance training modalities. The first was varied-intensity endurance training (VET) with two sessions held each week. Each session began with several minutes of cycling at an intensity of 65–70% HRmax, followed by cycling again for several minutes at an intensity of 80–85% HRmax, and then several dozen minutes of cycling at 70–80% HRmax. This order was then repeated several times with total session duration 120–180 min. The second involved steady-state CET executed three times a week. In this modality, the controls cycled for 120–180 min at an intensity equivalent to 70–80% HRmax.

In total, participants in all groups (E1, E2, and C) performed five training sessions per week during the intervention. Only one training session was held per day. The remaining two days of the week included: a day of absolute rest and a day of recovery session that involved low-intensity cycling at 60% HRmax, in all participants. Weekly training volume was 11–13 hours for groups E1 and E2 and 14–16 hours for group C (identical to pre-intervention training volume). Every fourth week total training volume was decreased by approximately 50% in each group (to 5.5–8 hours of exercise) to promote recovery without modification to the exercise protocol or intensity. Power output during training was continuously measured using a rear wheel hub-mounted G3 ANT+ and GS ANT+ telemetric system (PowerTap, Wisconson, US). Heart rate was continuously measured and displayed together with power output during training with the Garmin Edge 520 and Edge 810 cycling monitor (Garmin Ltd., Kansas, US).

2.3 Testing

Physical fitness parameters and physiological variables were measured pre- and post-intervention by administering two exercise tests based on an incremental testing protocol (ITP) and a sprint interval testing protocol (SITP). The two tests were interspersed by 24 hours of rest during which the participants refrained from any exercise or training stimulus. ITP and SITP were executed in controlled laboratory conditions (temperature and humidity controlled) at the Exercise Laboratory of the University School of Physical Education (PN-EN ISO 9001:2001 certified). Testing began at 09:00 approximately 150 min postprandial.

2.3.1 Incremental testing protocol

The ITP was performed on an Excalibur Sport cycle ergometer calibrated before each test (Lode B.V., The Netherlands). Starting workload was 50 W and increased every 3 min by 50 W until volitional fatigue. If a participant was unable to complete an entire 3 min stage 0.28 W per second missed was subtracted from the work rate at that stage. The highest power output determined in the incremental exercise test was taken to be the measure of maximal aerobic power (Pmax). Respiratory gas exchange was measured on a breath-by-breath basis with a Quark gas analyzer (Cosmed, Italy, Mediolan). The device was calibrated before each trial with a reference gas mixture of carbon dioxide (5%), oxygen (16%), and nitrogen (79%). Tidal air was collected by wearing a face mask and analyzed to determine oxygen uptake (VO ${}_{2}$ ). The composition of expired air and minute pulmonary ventilation was used to determine VO ${}_{2}$ max and averaged over 30-s intervals.

Table 2
Pre- and post-intervention work done, Pmax, and VO ${}_{2}$ in the ITP and SITP

Pre

Post

Pre

Post

Pre

Post

Sprint interval testing protocol

{}_{1}

[kJ]

72.3

\pm

8.4

76.2

\pm

{}^{**}

73.9

\pm

6.9

\pm

7.7

68.5

\pm

10.7

71.1

\pm

10.3

{}_{2}

[kJ]

72.4

\pm

8.1

76.4

\pm

9.4

{}^{**}

74.3

\pm

7.2

74.8

\pm

7.6

69.4

\pm

11.3

71.7

\pm

11.2

{}_{3}

[kJ]

71.5

\pm

8.1

{}^{\wedge}

75.7

\pm

9.1

{}^{**}

73.2

\pm

6.8

74.3

\pm

7.7

\pm

69.4

\pm

10.5

{}^{\wedge}

{}_{\text{tot}}

[kJ]

216.2

\pm

24.6

220.9

\pm

12.4

{}^{**}

221.3

\pm

20.8

224.1

\pm

22.9

206.9

\pm

32.9

213.1

\pm

32.2

{}_{2-1}

[l]

36.8

\pm

6.5

41.5

\pm

6.4

{}^{**}

43.4

\pm

3.8

43.1

\pm

37.4

\pm

6.3

37.9

\pm

6.7

{}_{2-2}

[l]

38.8

\pm

5.7

43.2

\pm

6.9

{}^{**\wedge}

43.5

\pm

4.4

41.5

\pm

2.5

38.1

\pm

36.9

\pm

{}_{2-3}

[l]

39.4

\pm

5.6

43.3

\pm

6.2

{}^{*\wedge}

43.3

\pm

4.7

41.9

\pm

2.5

\pm

6.2

37.3

\pm

6.8

Incremental testing protocol

Pmax [W]

369.5

\pm

42.5

393.9

\pm

{}^{**}

349.3

\pm

26.5

365

\pm

35.4

345.6

\pm

44.2

352

\pm

45.3

{}_{2}

max [ml

\cdot

min

{}^{-1}\cdot

{}^{-1}

]

57.4

\pm

3.4

63.5

\pm

6.1

{}^{**}

58.6

\pm

5.9

63.6

\pm

3.9

{}^{*}

55.4

\pm

7.2

58.9

\pm

9.8

Pre – pre-intervention; Post – post-intervention; W ${}_{1,2,3}$ – work done in the first, second, third sprint interval testing protocol set; W ${}_{\text{tot}}$ – total work done in all sprint interval testing protocol sets; VO ${}_{2-1,2,3}$ – sum of oxygen uptake in the first, second, third sprint interval testing protocol set; Pmax – maximal aerobic power in an incremental testing protocol; VO ${}_{2}$ max – maximal oxygen uptake in an incremental testing protocol; ${}^{*}$ – $p<$ 0.05 vs. pre-intervention measures; ${}^{**}$ – $p<$ 0.01 vs. pre-intervention measures; ${}^{\wedge}$ – $p<$ 0.05 vs. the first and second set; data are presented as mean $\pm$ standard deviation.

2.3.2 Sprint interval testing protocol

The SITP was performed on the same Excalibur Sport cycle ergometer as in the ITP and preceded by a warm-up in which the participant cycled for 5 min at 40% Pmax (as determined in the ITP) and then for 15 min at 60% Pmax. An active 5-min cool-down was then performed by cycling at an intensity equivalent to 30 W. The test proper then began and consisted of three sets of sprint interval exercise. Each set was composed of four 30-s maximal bouts with the participant motivated to produce an all-out effort and sustain a high power output for as long as possible. The repetitions were interspersed with 90 s of active recovery in which cycling intensity was reduced to 30 W. Upon completing each set a recovery component was performed that involved pedaling with no external load for the first 2.5 min. Intensity was then increased to 40% Pmax and continued until blood pH decreased to 7.3. Arterialized capillary blood from the fingertip was drawn in order to assay pH with the use of a RapidLab 348 blood gas analyzer (Siemens Healthcare, Germany). This resulted in individualized recovery times that ranged from 25 to 40 min. A subsequent low-intensity effort of 5 min at 30 W was then performed prior to beginning the next set.

Instantaneous and average power were recorded in each sprint repetition and the work done in each set (W ${}_{1}$ , W ${}_{2}$ , W ${}_{3}$ ) and the sum of all sets (W ${}_{\text{tot}}$ ) was extrapolated as the product of power and time. Respiratory function was also measured with the same procedure and equipment as in the ITP. Respiratory gas measures were collected at test start and recorded for 2.5 min after set termination. VO ${}_{2}$ was summed for each set and included the four sprint repetitions and recovery intervals and the 2.5 min post-exertion interval.

A 10 ml blood sample was drawn from the antecubital forearm vein to determine myoglobin concentration (Mb) and creatine kinase activity (CK) as markers of muscular damage. A baseline measure was obtained 20 min prior to test start and a post-exertion sample was drawn 60 min after the last set was completed. Blood was immediately centrifuged to extract blood plasma. The samples were stored in Eppendorf tubes at $-$ 80 ${}^{\circ}$ C and analyzed once all pre- and post-intervention samples were collected. CK was determined with a standard assay kit (Biosystems, Spain) and an Epoch microplate spectrophotometer integrated with Gen5 proprietary software (Biotek, USA). Mb was determined with a respective assay kit (EIAab, USA) with the same microplate reader as above. The delta change between baseline and post-exertion measures was calculated and reported as $\Delta$ CK and $\Delta$ Mb.

2.4 Data analysis

Means and standard deviations were calculated for all variables using the Statistica 13 software package (Statsoft, Poland). The distribution of the data set was screened for normality with the Shapiro-Wilk test. Data comparisons were made with the Friedman test with the Wilcoxon signed-rank test for post-hoc analysis. Pearson’s correlation coefficients (PCC) were calculated to analyze the relationship between changes in pre- and post-intervention Wtot with the changes in $\Delta$ Mb and $\Delta$ CK. Significance for inferential analysis was accepted at the 0.05 level of confidence.

Table 3
Pre- and post-intervention creatine kinase activity and myoglobin concentration in the sprint interval testing protocol

	E1				E2				C
	Pre		Post		Pre		Post		Pre		Post
CK ${}_{\text{B}}$ [U $\cdot$ l ${}^{-1}$ ]	148.9 $\pm$	61.8	150.5 $\pm$	67.2	220.7 $\pm$	125	231.5 $\pm$	156.5	156.9 $\pm$	39.8	162.4 $\pm$	79.2
CK ${}_{\text{E}}$ [U $\cdot$ l ${}^{-1}$ ]	205 $\pm$	83.1 ${}^{\wedge}$	174.8 $\pm$	75.5 ${}^{*\wedge}$	232.7 $\pm$	128.5	279.3 $\pm$	136 ${}^{*\wedge}$	179.6 $\pm$	57.2 ${}^{\wedge}$	190.3 $\pm$	85 ${}^{\wedge}$
Mb ${}_{\text{B}}$ [ng $\cdot$ ml ${}^{-1}$ ]	12.4 $\pm$	8.9	11.6 $\pm$	5.6	12 $\pm$	5.6	20.3 $\pm$	26.2	13.8 $\pm$	7.1	12.6 $\pm$	4.7
Mb ${}_{\text{E}}$ [ng $\cdot$ ml ${}^{-1}$ ]	41.1 $\pm$	20.4 ${}^{\wedge}$	27.8 $\pm$	14.6 ${}^{*\wedge}$	18.5 $\pm$	9.4	41.5 $\pm$	17.2 ${}^{*\wedge}$	31.8 $\pm$	15.1 ${}^{\wedge}$	32.4 $\pm$	19.7 ${}^{\wedge}$
$\Delta$ CK [U $\cdot$ l ${}^{-1}$ ]	56.2 $\pm$	33.3	24.4 $\pm$	17.1 ${}^{*}$	12 $\pm$	15.6	47.8 $\pm$	8.9 ${}^{*}$	22.6 $\pm$	34.3	27.9 $\pm$	26.3
$\Delta$ Mb [ng $\cdot$ ml ${}^{-1}$ ]	28.7 $\pm$	18.1	16.2 $\pm$	13.1 ${}^{*}$	6.5 $\pm$	10.1	21.2 $\pm$	6.9 ${}^{*}$	18 $\pm$	17.1	19.8 $\pm$	20

Pre – pre-intervention; Post – post-intervention; CK ${}_{\text{B}}$ – baseline creatine kinase activity in blood serum; CK ${}_{\text{E}}$ – post-exertion creatine kinase in blood serum; Mb ${}_{\text{B}}$ – baseline myoglobin concentration in blood serum; Mb ${}_{\text{E}}$ – post-exertion myoglobin concentration in blood serum; $\Delta$ CK – difference in baseline and post-exertion CK; $\Delta$ Mb – difference in baseline and post-exertion Mb; ${}^{*}$ – $p<$ 0.05 vs. pre-intervention measures; ${}^{\wedge}$ – $p<$ 0.05 vs. baseline value; data are presented as mean $\pm$ standard deviation.

3. Results

The assumption of normal distribution was not met for $\Delta$ CK and $\Delta$ Mb in E1, $\Delta$ Mb in E2, and W ${}_{1}$ , W ${}_{2}$ , W ${}_{3}$ , W ${}_{\text{tot}}$ , VO ${}_{2-2}$ , VO ${}_{2-3}$ and $\Delta$ CK in group C. For group-combined data (E1 and E2), $\Delta$ Mb, $\Delta$ CK, and Wtot were characterized by a normal distribution. Analysis of pre- and post-intervention ITP-derived Pmax and VO ${}_{2}$ max revealed significant increases in group E1. In E2, a significant increase was observed only for VO ${}_{2}$ max albeit a trend towards an increase in Pmax was identified ( $p=$ 0.09) (Table 2). Analysis of the SITP variables showed that VO ${}_{2}$ and work done increased significantly only in group E1, in all three individual sets. No significant differences were observed for total work done, work done per set, or VO ${}_{2}$ in group E2 and C (Table 2).

Analysis of the biochemical markers revealed significant post-exertion increases in CK and Mb (compared with baseline values) among all groups at both the pre- and post-intervention time points (excluding pre-intervention E2). Post-intervention group comparisons showed that the increase in CK and Mb was significantly less in E1 but significantly greater in E2 when compared with pre-intervention measures. This was reflected in the delta change between baseline and post-exertion values, in which post-intervention $\Delta$ CK and $\Delta$ Mb significantly decreased in E1 but significantly increased in E2. No significant differences were observed in control group between pre- and post-intervention CK and Mb levels. Baseline value CK and Mb was greater in E2 compared with E1 and C at pre- and post-intervention but not significant between-group differences were observed (Table 3).

Correlation analysis of the changes in $\Delta$ Mb and W ${}_{\text{tot}}$ for group-combined data (E1 and E2, together) at pre- and post-intervention revealed a significant negative correlation ( $r=-$ 0.62, R ${}^{2}=$ 0.39, $p=$ 0.008), in which a decrease in $\Delta$ Mb after SITP was associated with an increase in post-intervention W ${}_{\text{tot}}$ when compared pre-intervention W ${}_{\text{tot}}$ (Fig. 2). A similar relationship was observed for the change in $\Delta$ CK and the change in W ${}_{\text{tot}}$ ( $r=-$ 0.5, R ${}^{2}=$ 0.25, $p=$ 0.041) (Fig. 3).

Figure 2.

Scatter plot illustrating the linear correlation between pre- and post-intervention changes in $\Delta$ Mb and Wtot ( $r=-$ 0.62, $p<$ 0.05); correlation coefficients based on E1 and E2 combined data.

Figure 3.

Scatter plot illustrating the linear correlation trend between pre- and post-intervention changes in $\Delta$ CK and Wtot ( $r=-$ 0.5, $p<$ 0.05); correlation coefficients based on E1 and E2 combined data.

4. Discussion

Increased Mb and CK levels were observed after the administration of SITP. Several studies have confirmed that strenuous exercise and the resultant oxidative stress can cause severe muscle damage due to metabolic [21, 25] and mechanical factors associated with excessive muscle tension or stretch [26, 27]. However, the applied exercise tests were all based on pedaling mechanics, an activity dominated by concentric muscle work [28]. While researchers have suggested that even highly intensive concentric exercise does not induce significant changes in CK and Mb [23, 29] or other biochemical markers of acute muscle damage (i.e. calpain or calpastatin) [29, 30, 31], the cited works adopted an exercise testing protocol significantly different from the one used herein. For example, Newham and Jones [23] and Vissing et al. [29] both administered an uphill walking/climbing task. While Murphy et al. [31] did use a cycle ergometer, their exercise protocol involved cycling at 70% VO ${}_{2}$ max until fatigue and a Wingate-based protocol. In the present study, Mb and CK were measured when performing repeated 30-s maximal sprints which may have induced greater metabolic stress and causing increased muscle damage than the above protocols.

Post-intervention group comparisons revealed that the increase in CK and Mb was significantly less in E1 compared with other groups. This was also seen by the significant decrease in post-intervention $\Delta$ CK and $\Delta$ Mb compared with pre-intervention values. Such a diametric difference between pre- and post-intervention values was accompanied by increased muscle oxygen potential. Laughlin and Roseguini [32] indicated that sprint interval training develops capillary density and muscular blood flow in fast twitch muscle fibers. In addition, SIT-induced changes in neuromuscular characteristics are known to increases muscle oxidative potential during such efforts [26]. This is evidenced in the present study by the significant post-intervention increases of SITP-based VO ${}_{2}$ . The concomitant increase in oxygen potential and the observed changes of $\Delta$ CK and $\Delta$ Mb could have influenced the increase in the amount of work done in E1 but none of the other groups. This thesis is supported by the negative correlation between the change in $\Delta$ Mb and $\Delta$ CK with the change in work done that was observed at both pre- and post-intervention time points. These changes are significant in the context of previous findings in which a strong correlation was identified between VO ${}_{2}$ peak obtained during a SITP and race performance in well-trained MTB cyclists [33]. Moreover, another study demonstrated a correlation between average power in an interval training exercise test and MTB race times [34]. This relationship appears to be rationally justified as competitive MTB involves repeated dynamic efforts at an intensity above Pmax [35].

It is interesting to note the increase in CK and Mb in group E2 after the intervention was completed. Current evidence suggests that regular training should reduce susceptibility to muscle fatigue [26] and muscle tissue damage [36]. However, the differences between E1 and E2 suggest that the adaptive response to intensive training may be strongly influenced by previous high-volume endurance training background in well-trained cyclists. It may be surmised that if the training stimulus was insufficient, then the resistance to damage and also oxidative potential of muscle to short high-intensity exercise may not improve. Relatedly, the administration of intermittent sprint training to a group of untrained adults (twenty 10-s sprints performed three times per week for 5 weeks) led to enhanced Ca ${}^{++}$ release compared with controls [37]. This release can result in the activation of calpain-3 leading to the proteolysis of cell constituents and eventual apoptosis [30, 38] and also the activation of phospholipase A ${}_{2}$ which affects cell membrane integrity [38]. Hence, the detrimental effects of phospholipase A ${}_{2}$ and Ca ${}^{2+}$ overload due to high-intensity exercise [38] may explain the CK and Mb dynamics observed in group E2. It is important to note that while Ørtenblad et al. [37] did report improved sprint performance after 5 weeks of sprint training, they involved an untrained sedentary sample. In the present study, no change in work done was observed in group E2, suggesting that the applied intervention was not effective in the enhancement of exercise capacity during repeated sprint performance. When comparing E1 and E2 post-intervention outcomes, the results show that work done and VO ${}_{2}$ in the SITP is enhanced when previous training status involves high-volume training at moderate intensity and that the application of such a training regime appears to also reduce the post-exertion effects of CK and Mb during high-intensity exercise.

5. Conclusions

The concomitant execution of SIT, HIIT, and CET is beneficial in the development of VO ${}_{2}$ max regardless of previous training background. However, the findings suggest that an increase in VO ${}_{2}$ and work done in repeated sprint exercise is possible if a training intervention of SIT, HIIT, and CET be preceded by aerobic training of high-volume moderate-intensity. Such high-volume moderate-intensity training may induce beneficial training adaptations (evidenced via reduced SITP-based CK and Mb levels) that reduce structural damage within the muscle fiber thereby allowing a greater amount of work done during intense exercise. These findings may aid the coach in explicitly determining training load over a long-term (several-month or several-year) perspective. This is particularly useful in the planning of training at high-volume to prepare MTB cyclists for later training at high-intensity, with the goal of increasing power output during maximal efforts and therefore improving competitive performance.

5.1 Study limitations

The findings of the study require careful interpretation due to certain intrinsic limitations. The relatively small sample size and underlying distribution of the data required the use of non-parametric methods to compare individual sets and pre- and post-intervention. Non-parametric tests, particularly with small samples, lack the statistical power of their parametric equivalents and limit inference on the magnitude of the studied training effects. However, these limitations are difficult to overcome due to the difficulties in recruiting and retaining high-performance athletes that can execute the training intervention and highly demanding exercise tests.

Footnotes

Conflict of interest

The authors report no conflicts of interest associated with this manuscript.

References

Buchheit

Laursen

. High-intensity interval training, solutions to the programming puzzle: Part I: cardiopulmonary emphasis. Sports Med. 2013; 43(5): 313-338. doi: 10.1007/s40279-013-0029-x.

Laursen

Jenkins

. The scientific basis for high-intensity interval training. Optimizing training programmes and maximizing performance in highly trained endurance athletes. Sports Med. 2002; 32(1): 53-73. doi: 10.1249/01.MSS.0000036691.95035.7D.

Sloth

Overqaard

Dalgas

. Effects of sprint interval training on VO2max and aerobic exercise performance: A systematic review and meta-analysis. Scand J Med Sci Sports. 2013; 23(6): 341-352. doi: 10.1111/sms.12092.

Burgomaster

Heigenhauser

Gibala

. Effect of short-term sprint interval training on human skeletal muscle carbohydrate metabolism during exercise and time-trial performance. J Appl Physiol. 2006; 100(6): 2041-2047. doi: 10.1152/japplphysiol.01220.2005.

Gibala

Little

van Essen

Wilkin

Burgomaster

Safdar

, et al. Short-term sprint interval versus traditional endurance training: similar initial adaptations in human skeletal muscle and exercise performance. J Physiol. 2006; 575(3): 901-911. doi: 10.1113/jphysiol.2006.112094.

Rønnestad

Hansen

Vegge

Tønnessen

Slettaløkken

. Short intervals induce superior training adaptations compared with long intervals in cyclists – an effort-matched approach. Scand J Med Sci Sports. 2015; 25: 143-151. doi: 10.1111/sms.12165.

Laursen

Shing

Peake

Coombes

Jenkins

. Interval training program optimization in highly trained endurance cyclists. Med Sci Sports Exerc. 2002; 34(11): 1801-1807. doi: 10.1249/01.MSS.0000036691.95035.7D.

Stepto

Hawley

Dennis

Hopkins

. Effects of different interval-training programs on cycling time-trial performance. Med Sci Sports Exerc. 1999; 31(5): 736-741.

Inoue

Impellizzeri

Pires

Pompeu

Deslandes

Santos

. Effects of sprint versus high-intensity aerobic interval training on cross-country mountain biking performance: a randomized controlled trial. PLOS One. 2016; 11(1). doi: 10.1371/journal.pone.0145298.

10.

Hebisz

Zaton

Ochamann

Mielnik

. Concomitant application of sprint and high-intensity interval training on maximal oxygen uptake and work output in well-trained cyclists. Eur J Appl Physiol. 2016; 116(8): 1495-1502. doi: 10.1007/s00421-016-3405-z.

11.

Colakoglu

Ozkaya

Balci

Yapicioglu

. Schorter intervals at peak SV vs. VO2max may yield high SV with less physiological stress. Eur J Sport Sci. 2015; 15(7): 623-630. doi: 10.1080/17461391.2014.966762.

12.

Midgley

McNaughton

Wilkinson

. Is there an optimal training intensity for enhancing the maximal oxygen uptake of distance runners?: empirical research findings, current opinions, physiological rationale and practical recommendations. Sports Med. 2006; 36(2): 117-132.

13.

Gist

Fedeva

Dishman

Cureton

. Sprint interval training effects on aerobic capacity: a systematic review and meta-analysis. Sports Med. 2014; 44: 269-279. doi: 10.1007/s40279-013-0115-0.

14.

Bayati

Farzad

Gharakhanlou

Agha-Alinejad

. A practical model of low-volume high-intensity interval training induces performance and metabolic adaptations that resemble ‘all-out’ sprint interval training. J Sports Sci Med. 2011; 10(3): 571-576.

15.

Metcalfe

Babraj

Fawkner

Vollaard

. Towards the minimal amount of exercise for improving metabolic health: beneficial effects of reduced-exertion high-intensity interval training. Eur J Appl Physiol. 2012; 112(7): 2767-2775. doi: 10.1007/s00421-011-2254-z.

16.

Trilk

Singhal

Bigelman

Cureton

. Effect of sprint interval training on circulatory function during exercise in sedentary, ever weight/obese women. Eur J Appl Physiol. 2011; 111(8): 1591-1597. doi: 10.1007/s00421-010-1777-z.

17.

Creer

Ricard

Conlee

Hoyt

Parcell

. Neural, metabolic, and performance adaptations to four weeks of high intensity sprint-interval training in trained cyclists. Int J Sports Med. 2004; 25(2): 92-98. doi: 10.1055/s-2004-819945.

18.

Nalcakan

. The effects of sprint interval vs. continuous endurance training on physiological and metabolic adaptations in young healthy adults. Journal of Human Kinetics. 2014; 30(44): 97-109.

19.

Niemelä

Juvonen

Kangastupa

Niemelä

Juvonen

. Clinical and laboratory responses of cross-country skiing for a 24-H world record: case report. J Sports Sci Med. 2015; 14(4): 702-707.

20.

Banfi

Colombini

Lombardi

Lubkowska

. Metabolic markers in sports medicine. Advances in Clinical Chemistry. 2012; 56: 1-54.

21.

Brancaccio

Lippi

Maffulli

. Biochemical markers of muscular damage. Clin Chem Lab Med. 2010; 48(6): 757-767. doi: 10.1515/CCLM.2010.179.

22.

Noakes

. Effect of exercise on serum enzyme activities in humans. Sports Med. 1987; 4(4): 245-267.

23.

Newham

Jones

Edwards

. Plasma creatine kinase changes after eccentric and concentric contractions. Muscle Nerve. 1986; 9(1): 59-63.

24.

Lyakh

Mikolajec

Bujas

Litkowycz

. Review of Platonov’s “Sports training periodization. General theory and its practical application” – Kiev: olympic literature. J Hum Kinet. 2014; 44: 259-263. doi: 10.2478/hukin-2014-0131.

25.

Abbiss

Laursen

. Models to explain fatigue during prolong endurance cycling. Sports Med. 2005; 35(10): 865-898.

26.

Bogdanis

. Effects of physical activity and inactivity on muscle fatigue. Front Physiol. 2012; 3(142): 1-15. doi: 10.3389/fphys.2012.00142.

27.

Coffey

Hawley

. The molecular bases of training adaptation. Sports Med. 2007; 37(9): 737-763.

28.

Perrey

Betik

Candau

Rouillon

Hughson

. Comparison of oxygen uptake kinetics during concentric and eccentric cycle exercise. J Appl Physiol. 2001; 91(5): 2135-2142.

29.

Vissinq

Overqaard

Nederqaard

Fredsted

Schjerlinq

. Effects of concentric and repeated eccentric exercise on muscle damage and calpain-calpastat in gene expression in human skeletal muscle. Eur J Appl Physiol. 2008; 103(3): 323-332. doi: 10.1007/s00421-008-0709-7.

30.

Murphy

Goodman

McKenna

Bennie

Leikis

Lamb

. Calpain-3 is autolyzed and hence activated in human skeletal muscle 24h following a single bout of eccentric exercise. J Appl Physiol. 2007; 103: 926-931. doi: 10.1152/japplphysiol.01422.2006.

31.

Murphy

Snow

Lamb

. Mu-calpain and calpain-3 are not autolyzed with exhaustive exercise in humans. Am J Physiol Cell Physiol. 2006; 290(1): 116-122. doi: 10.1152/ajpcell.00291.2005.

32.

Laughlin

Roseguini

. Mechanisms for exercise training-induced increases in skeletal muscle blood flow capacity: differences with interval sprint training versus aerobic endurance training. J Physiol Pharmacol. 2008; 7: 71-88.

33.

Hebisz

Zatoń

Michalik

. Peak oxygen uptake in a sprint interval testing protocol vs. maximal oxygen uptake in an incremental testing protocol and their relationship with cross-country mountain-biking performance. Appl Physiol Nutr Metab. 2017; 42(4): 371-376. doi: 10.1139/apnm-2016-0362.

34.

Inoue

SaFilho

Mello

Santos

. Relationship between anaerobic cycling tests and mountain bike cross-country performance. J Strength Cond Res. 2012; 26(6): 1589-1593. doi: 10.1519/JSC.0b013e318234eb89.

35.

Impellizzeri

Marcora

. The physiology of mountain biking. Sports Med. 2007; 37(1): 59-71.

36.

Proske

Morgan

. Muscle damage from eccentric exercise: mechanism, mechanical signs, adaptation and clinical applications. J Physiol. 2001; 537(2): 333-345. doi: 10.1111/j.1469-7793.2001.00333.x.

37.

Ørtenblad

Lunde

Levin

Andersen

Pedersen

. Enhanced sarcoplasmatic reticulum Ca2+ release following intermittent sprint training. Am J Physiol Regulatory Integrative Comp Physiol. 2000; 279(1): 152-160.

38.

Gissel

. The role of Ca2+ in muscle cell damage. Ann N Y Acad Sci. 2005; 1066: 166-180.

Effects of concomitant high-intensity interval training and sprint interval training on exercise capacity and response to exercise- induced muscle damage in mountain bike cyclists with different training backgrounds

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

Table 1 Anthropometric and physiological characteristics of groups E1, E2, and C

2.1 Participants

2.2 Procedures

2.3 Testing

2.3.1 Incremental testing protocol

Table 2 Pre- and post-intervention work done, Pmax, and VO 2 in the ITP and SITP

2.4 Data analysis

Table 3 Pre- and post-intervention creatine kinase activity and myoglobin concentration in the sprint interval testing protocol

5. Conclusions

5.1 Study limitations

Footnotes

Conflict of interest

References

Table 1
Anthropometric and physiological characteristics of groups E1, E2, and C

Table 2
Pre- and post-intervention work done, Pmax, and VO ${}_{2}$ in the ITP and SITP

Table 3
Pre- and post-intervention creatine kinase activity and myoglobin concentration in the sprint interval testing protocol