It is well established that factors such as poor cardiorespiratory fitness, adiposity, impaired glucose tolerance, hypertension, and arteriosclerosis are independent threats to health and that physical inactivity increases the risk for premature death and elevates the incidence of the abovementioned unhealthy conditions. Epidemiologic cross-sectional investigations and longitudinal intervention studies have provided experimental evidence for the effectiveness of prolonged aerobic exercise training such as continuous running, brisk walking, or bicycling as interventions that may lower the relative risk for developing several metabolic diseases (Nybo et al., 2010). However, lack of time is a common reason why many people fail to accomplish the training programs (Godin et al., 1994). Recently, a novel type of high-intensity interval training (HIT) known as sprint interval training (SIT; repeated 30-s “all-out” efforts) has demonstrated increases in aerobic performance in a short time frame (Burgomaster et al., 2005; Gibala et al., 2006). It is interesting that SIT may induce similar improvements in cardiorespiratory fitness and skeletal muscle oxidative capacity as prolonged training, (Burgomaster et al., 2008; Nybo et al., 2010) and a recent study reported that SIT substantially improves insulin action (Babraj et al., 2009). Apparently, the repeated SIT bouts stress many of the physiological/biochemical systems used in aerobic efforts (Hazell et al., 2010) and poses a considerable metabolic challenge to skeletal muscle as large reductions in muscle glycogen and pH and increases in blood lactate as well as whole body carbohydrate and fat oxidation (Stepto et al., 2001). A wide range of adaptations have been shown after this type of training, including increased resting glycogen content (Barnett et al., 2004; Rodas et al., 2000), increased activity of various glycolytic and oxidative enzymes (Burgomaster et al., 2005; Jacobs et al., 1987), H+ buffering capacity (Gibala et al., 2006), and time to exhaustion (Burgomaster et al., 2005; Gibala et al., 2006). Increased (Rodas et al., 2000; Tabata et al., 1996) or unchanged (Burgomaster et al., 2005) values of VO₂max after SIT have also been reported. As a result, it has been speculated that SIT could be a time-efficient strategy for health promotion. Nonetheless, use of 30-s “all- out” efforts as a training program is often dismissed outright as unsafe, unpractical, or intolerable for general populations. Therefore, an evaluation of the physiological adaptations induced by different interval-training strategies in a wide range of populations will permit evidence-based recommendations that may provide an alternative to current exercise prescriptions for time-pressed individuals. Accordingly, the purpose of this study was to compare the established SIT protocol (30-s “all-out” efforts with 4 min recovery) versus a modified type of HIT (30-s efforts with 125% P_max with 2 min recovery) on both aerobic and anaerobic performance. The intensity of the modified training is the half of the intensity of SIT but with doubled repetitions. We hypothesized that the training induced changes are the same.

Twenty-four healthy young male graduate students volunteered to participate in the investigation (age = 25 ± 0.8 years; height = 1.72 ± 0.08 m; mass = 70 ± 11 kg; Percent body fat = 18 ± 6%). All were habitually active but not engaged in any sort of structured training program nor had they been for at least 3 months prior to the study. Prior to any participation, the experimental procedures and potential risks were explained fully to the participants and all provided written informed consent. Dietary and physical activity patterns were maintained throughout the study. Subjects were matched into three groups based on the time to exhaustion test and VO₂max. The study was approved by the Ethical Committee of the Faculty of Medical Sciences of Tarbiat Modares University and was in accordance with the Declaration of Helsinki.

Prior to any baseline testing, all participants attended a laboratory familiarization visit to introduce the testing/training procedures and to ensure that any learning effect was minimal for the baseline measures. Each participant first completed tests for body composition and graded exercise test (GXT) to determine their VO₂max and power at VO₂max (P_max). The second test was a T_max test used to determine the time to exhaustion at P_max. On the third day, the participants performed 30-second Wingate test to determine peak power output (PPO), mean power output (MPO) and total work (W_tot). All tests were separated by at least 24 h, post-testing occurred within 48 h of the final training session in the same order (Hazell et al., 2010).

VO₂max was determined using a progressive incremental test on a cycle ergometer until volitional fatigue. After 5 min warm-up and performing stretching exercises, the test commenced at an initial power output of 50 W and was increased by 30 W every minute until the participant was fatigued (Laursen et al., 2002a). Expired gas analysis was acquired with an automated metabolic system (ZAN600 CPET: ZAN Messgerate GmbH, Oberthulba, Germany), and VO₂max was calculated as the highest oxygen consumed over a 1 min period. VO₂max was confirmed when three or more of the following criteria were met: (1) a plateau in VO₂ despite an increase in work load; (2) a respiratory exchange ratio (RER) higher than 1.2 (Esfarjani and Laursen, 2007); (3) peak heart rate at least equal to 90% of the age-predicted maximum (Tanaka et al., 2001); and/or (4) visible exhaustion. P_max was defined as the final completed work rate (e.g., maintained for 10 s) (Laursen et al., 2002a).

The second test performed was a T_max test used to determine the time to exhaustion at P_max that was defined as the minimal power output that elicited a VO₂ reading that was within 2 ml·kg^-1·min^-1 of the previous reading, despite an increase in workload (Laursen et al., 2005). After a 10- minute warm-up at 50 W, participants cycled to fatigue at P_max at a self-selected cadence; the test was stopped when cadence fell below 60 rev·min^-1. The total amount of work completed during the T_max test (W_Tmax) was calculated as a product of P_max and T_max (W_Tmax = (P_max ËŸ T_max)/1000) and expressed in kJ.

Peak power output (PPO), mean power output (MPO) and total work (W_tot) were assessed over Wingate test on a mechanically braked cycle ergometer (model 894E, Monark, Sweden). Participants performed a Wingate test against a resistance equivalent to 0.075 kg/kg body mass. Participants were instructed to begin pedaling as fast as possible against the ergometer’s inertial resistance, and then the appropriate load was manually applied. Participants were verbally encouraged to continue pedaling as fast as possible throughout the 30-s test. PPO was defined as the highest work output in a 5-second period, and MPO as the average work output for the 30-second test period (Nottle and Nosaka, 2007). W_tot was used to describe muscle endurance and was calculated by multiplying MP by 30 seconds and expressed in kJ. Previously determined intraclass correlation coefficient (ICC) for Wingate variables was 0.94 (Bar-Or, 1987).

Participants were assigned to one of the three groups: (G₁) 30-s all-out efforts: 4 min recovery; (G₂) 30-s with 125% P_max: 2 min recovery and control group (no training) (Table 1). Participants trained three times per week on alternate days for a total of 4 wk. The G₁ cycling program began with 3 intervals in week 1, progressing to 5 in week 3 followed by a reduction to 4 intervals in week four. The G₂ cycling program began with 6 intervals in week 1, progressing to 10 in week 3 followed by a reduction to 8 intervals in week four.

Capillary blood samples were taken (by finger prick) from the forefinger at rest, 3, and 20 min after the Wingate trial. Blood lactate was analyzed on site using a Lactate Analyzer (Lactate Scout, Senslab GmbH Leipzig, Germany).

All results are reported as a mean ± SD. The Kolmogorov-Smirnov test was used to test the normality of the distribution. A 3 ËŸ 2 (Group ËŸ time) repeated measures analysis of variance (ANOVA) was performed. When a significant difference was revealed, Tukey’s post hoc test was used to specify where the difference occurred. The alpha level for statistical significance was set at p ≤ 0.05. Effect size was calculated using Cohen’s d (d).

Changes in physiological variables associated with the GXT are presented in Table 2. Following the 4-week training program, VO₂max (G₁: d = 1.10; G₂: d = 1.19), P_max (G₁: d = 1.27; G₂: d = 1.77), T_max (G₁: d = 3.13; G₂: d= 3.53) and W_Tmax (G₁: d = 2.49; G₂: d = 3.02) were significantly increased in the G₁ and G₂ groups compared with pre-testing. As well, the increases in P_max (G₁: p = 0.011, d = 1.31; G₂: p = 0.006, d = 1.58), T_max (G₁: p = 0.00, d = 3.01; G₂: p = 0.00, d = 3.34) and W_Tmax (G₁: p = 0.00, d = 3.38; G₂: p = 0.00, d = 4.09) were significantly greater in G₁ and G₂ compared with CON group. No variables were significantly changed in the CON group.

PPO increased significantly in G₁ (p = 0.006, d = 1.48; Table 3) and G₂ (p = 0.04, d = 1.86) after the training. As well, the increase in PPO was significantly greater in G₁ compared with CON group (p = 0.009, d = 1.66). In addition, MPO increased significantly in G₁ compared with pre-testing (p = 0.025, d = 1.32; Table 3) and the CON group (p = 0.017, d = 1.49). MPO in G₂ did not change significantly with the training (p = 0.064). There were significant increases in W_tot in G₁ (p = 0.025, d = 1.38; Table 3), which were statistically significant compared with CON group (p = 0.017, d = 1.52).

After the 4-week training period, maximal BLa^_ (3^th min) was significantly higher in G₁ compared with pre-testing (Post: 15.6 ± 1.6 vs. Pre: 13.5 ± 1.3 mmol·l^-1; p = 0.01, d = 1.45; Figure 1) and CON group (G₁: 15.6 ± 1.6 vs. CON: 13.1 ± 1.2 mmol·l^-1; p = 0.003, d = 1.76). Maximal BLa^_ in G₂ was only significantly different compared with CON group (G₂: 14.8 ± 1.6 vs. CON: 13.1 ± 1.2 mmol·l^-1; p = 0.032, d = 1.2). Blood lactate recovery (20th min) significantly decreased in G₁ (Post: 12.9 ± 1.8 vs. Pre: 15.8 ± 3.0 mmol·l^-1; p = 0.007, d = 1.21) and G₂ (Post: 13.0 ± 1.0 vs. Pre: 15.1 ± 1.4 mmol·l^-1; p = 0.04, d = 1.75) when compared with pre-testing and the CON group (p < 0.05).

Recent evidence suggests that sprint interval training is a time-efficient strategy to stimulate a number of skeletal muscle adaptations that are comparable to traditional endurance training (Gibala and McGee, 2008). It has been demonstrated that SIT up-regulates peroxisome proliferator-activated receptor-co-activator-1α (PGC-1α), a potent regulator of mitochondrial biogenesis (Gibala et al., 2009), which could be the underlying mechanism responsible for the observed aerobic adaptation. This information is exciting because it means that such adaptations can be obtained with a substantial reduction in exercise training time. However, the feasibility of this type of training is questionable for general populations. Therefore, the purpose of the current study was to compare the established SIT protocol versus a modified type of HIT on both aerobic and anaerobic performance.

The first finding of the present study was that both training programs significantly and similarly improved VO₂max in untrained subjects (G₁: 9.6% vs. G₂: 9.7%; Table 2). Several studies have shown an increase in VO₂max following established SIT program (Creer et al., 2004; Barnett et al., 2004). In contrast to these findings, Burgomaster et al., 2005 recently showed in untrained subjects that six sessions of sprint interval training (30-s all-out Wingate sprints) increased citrate synthase activity by 38% and doubled cycle time to exhaustion. Interestingly, no change occurred in VO₂max. Improvements in VO₂max may occur through increases in both oxygen delivery (i.e., increases in stroke volume) and/or oxygen utilization by active muscles (i.e., increases in capillarization/mitochondrial density). Given that maximal heart rate remains unchanged in response to training, improvements in oxygen delivery to exercising muscles during high-intensity exercise can be attributed to an increase in stroke volume. Stroke volume can increase through a higher left-ventricular contractile force and/or through an increase in cardiac filling pressure, which raises end-diastolic volume and resultant stroke volume (Laursen and Jenkins, 2002b). In addition, the increases in VO₂max and oxidative enzymes that has been reported by several authors (Barnett et al., 2004; Gibala et al., 2006) indicate the present sprint-training protocol evoked changes in the capacity to produce energy via oxidative metabolism. It is also known that the aerobic contribution to sprint exercise increases, depending on the recovery between bouts, as a function of successive sprints (Bogdanis et al., 1996). The relatively short recovery periods used in the present study would have imposed a considerable demand on aerobic metabolism in meeting ATP resynthesis in the latter sprint bouts. All of these factors may explain the observed increase in VO₂max.

T_max significantly increased in both groups following training (G₁: 48% vs. G₂: 54%; Table 2). T_max improvements are greater than those reported by Esfarjani and Laursen, 2007 who reported a 32% improvement in moderately trained runners using HIT prescribed at 130% vVO₂max with interval durations of 30-s. In addition, 30-s all-out SIT program (over 2 wk) has been shown to improve (100%) cycle time to exhaustion at 80% VO₂max in untrained subjects (Burgomaster et al., 2005). Franch et al., 1998 also reported a significant increase (65%) in time to exhaustion after 6 weeks of short-interval training. From a metabolic point view, the increased mitochondrial enzyme content, which is associated with an increase in the rate of lipid utilization and consequently a decrease in rate of glycogen depletion contributes to an improved exercise tolerance, the glycogen depletion being strongly linked with fatigue during prolonged exercise (Demarle et al., 2003). Interestingly, a comprehensive work by Harmer et al., 2000 indicated a reduced anaerobic ATP synthesis during intense exercise following seven weeks of sprint training, and also suggested an enhanced aerobic metabolism. Another possible reason for the improved T_max found in the training groups may be a decreased lactate accumulation throughout the test and/or a greater muscle buffering capacity, which has been demonstrated in repeated 30-s sprint training (Gibala et al., 2006). It is possible that the greater improvement in T_max in G₂ versus G₁ was aided through the higher training volume in G₂ (6-10 30-s bouts) compared with G₁ (3-5 30-s bouts).

PPO elicited during the Wingate test increased by 10.3% and 7.3% in G₁ and G₂, respectively, with no difference between groups (Table 3); whereas, MPO was increased only in G₁ by 17.1% (p < 0.05). This result is consistent with a greater reliance on glycolysis during training in G₁ and could explain at least partially why the less intense 30-s repeats seemed less difficult. Such results are in accordance with previous studies reporting an improvement in PPO with SIT. Burgomaster et al., 2005 reported increase in PPO after 2 weeks of SIT but MPO did not change in their investigation. Increased muscle phosphocreatine concentration (Rodas et al., 2000), anaerobic enzyme activities (MacDougall et al., 1998; Parra et al., 2000), and a significant increase in FTa fibers, along with a decrease in ST fibers (Jansson et al., 1990; Dawson et al., 1998), are possible explanations of our findings.

As expected with SIT, there was an increase in maximal blood lactate from pre to post training in G₁ (15.5%; Figure 1). An increase in maximal BLa? in post-testing coinciding with increased peak power, mean power, and total work in G₁. Sharp et al., 1986 reported an increase in blood lactate concentrations and total work performed during a 45-s maximal cycle sprint after eight weeks of intense sprint training in untrained subjects. These data were reported in conjunction with an increase in the glycolytic enzyme phosphofructokinase (PFK), suggesting that increased lactate and total work values were due to improved glycolytic output. Increases in glycolytic enzymes such as hexokinase and PFK due to SIT have been shown as well (MacDougall et al., 1998; Rodas et al., 2000), indicating that increases in blood lactate and total work values in G₁ may be due to improved glycolytic function. Interestingly, Sharp and colleague (1986) saw no change in muscle pH in spite of increased lactate concentrations suggesting an increase in buffering capacity, which may have also contributed to increases in total work in the current study in spite of increased blood lactate concentrations. However, the changes in G₂ did not reach to significant level (p = 0.05). In addition, blood lactate recovery changed significantly and similarly with either training regimen (Figure 1).

As a result, 30-s all-out SIT should be easily incorporated into the training program of any athlete desiring to increase both aerobic and anaerobic power quickly but not into the training program of general population. The Wingate-based training model requires a specialized ergometer and an extremely high level of subject motivation. Given the extreme nature of the exercise, it is doubtful that the general population could safely or practically adopt the model. Like the our study, future studies should examine modified interval-based approaches to identify the optimal combination of training intensity and volume necessary to induce adaptations in a practical time-efficient manner.

The results of the current study agree with earlier work demonstrating the effectiveness of 30-s all-out SIT to aerobic and anaerobic adaptations. However, of substantial interest is our observation that many of the same performance gains occurred in modified HIT protocol (30-s with 125% P_max).