Determination of optimal loading during the power clean, in collegiate athletes

ABSTRACT: Comfort, P, Fletcher, C, and McMahon, JJ. Determination of optimal loading during the power clean, in collegiate athletes. J Strength Cond Res 26(11): 2970-2974, 2012-Although previous research has been performed in similar areas of study, the optimal load for the development of peak power during training remains controversial, and this has yet to be established in collegiate level athletes. The purpose of this study was to determine the optimal load to achieve peak power output during the power clean in collegiate athletes. Nineteen male collegiate athletes (age 21.5 ± 1.4 years; height 173.86 ± 7.98 cm; body mass 78.85 ± 8.67 kg) performed 3 repetitions of power cleans, while standing on a force platform, using loads of 30, 40, 50, 60, 70, and 80% of their predetermined 1-repetition maximum (1RM) power clean, in a randomized, counterbalanced order. Peak power output occurred at 70% 1RM (2,951.7 ± 931.71 W), which was significantly greater than the 30% (2,149.5 ± 406.98 W, p = 0.007), 40% (2,201.0 ± 438.82 W, p = 0.04), and 50% (2,231.1 ± 501.09 W, p = 0.05) conditions, although not significantly different when compared with the 60 and 80% 1RM loads. In addition, force increased with an increase in load, with peak force occurring at 80% 1RM (1,939.1 ± 320.97 N), which was significantly greater (p < 0.001) than the 30, 40, 50, and 60% 1RM loads but not significantly greater (p > 0.05) than the 70% 1RM load (1,921.2 ± 345.16 N). In contrast, there was no significant difference (p > 0.05) in rate of force development across loads. When training to maximize force and power, it may be advantageous to use loads equivalent to 60-80% of the 1RM, in collegiate level athletes.     

Kinetic comparisons during variations of the power clean

Comfort, P, Allen, M, and Graham-Smith, P. Kinetic comparisons during variations of the power clean. J Strength Cond Res 25(12): 3269-3273, 2011-The aim of this investigation was to determine the differences in peak power, peak vertical ground reaction forces, and rate of force development (RFD) during variations of the power clean. Elite rugby league players (n = 16; age 22 ± 1.58 years; height 182.25 ± 2.81 cm; body mass 98.65 ± 7.52 kg) performed 1 set of 3 repetitions of the power clean, hang power clean, midthigh power clean, or midthigh clean pull, using 60% of 1 repetition maximum power clean, in a randomized order, while standing on a force platform. One-way analysis of variance with Bonferroni post hoc analysis revealed a significantly (p < 0.001) greater peak power output during the midthigh power clean (3,565.7 ± 410.6 W) and the midthigh clean pull (3,686.8 ± 386.5 W) compared with both the power clean (2,591.2 ± 645.5 W) and the hang power clean (3,183.6 ± 309.1 W), along with a significantly (p < 0.001) greater peak Fz during the midthigh power clean (2,813.8 ± 200.5 N) and the midthigh clean pull (2,901.3 ± 226.1 N) compared with both the power clean (2,264.1 ± 199.6 N) and the hang power clean (2,479.3 ± 267.6 N). The midthigh power clean (15,049.8 ± 4,415.7 N·s) and the midthigh clean pull (15,623.6 ± 3,114.4 N·s) also demonstrated significantly (p < 0.001) greater instantaneous RFD when compared with both the power clean (8,657.9 ± 2,746.6 N·s) and the hang power clean (10,314.4 ± 4,238.2 N·s). From the findings of this study, when training to maximize power, Fz, and RFD, the midthigh power clean and midthigh clean pull appear to be the most advantageous variations of the power clean to perform.     

Strength and power characteristics in English elite rugby league players

The aim of this article is to present data on the strength and power characteristics of forwards and backs in a squad of elite English rugby league players and compare these findings to previously published literature from Australia. Participants were elite English rugby league players (n = 18; height 184.16 ± 5.76 cm; body mass 96.87 ± 10.92 kg, age 21.67 ± 4.10 years) who were all regular first team players for an English Superleague club. Testing included 5-, 10-, 20-m sprint times, agility, vertical jump, 40-kg squat jump, isometric squat, concentric and eccentric isokinetic knee flexion and extension. Independent t-tests were performed to compare results between forwards and backs, with paired samples t-tests used to compare bilateral differences from isokinetic assessments and agility tests. Forwards demonstrated significantly (p < 0.05) greater body mass (102.15 ± 7.5 kg), height (186.30 ± 5.47 cm), power during the 40-kg jump squat (2,106 ± 421 W), isometric force (3,122 ± 611 N) and peak torque during left concentric isokinetic knee extension (296.1 ± 54.2 N·m) compared to the backs (86.30 ± 8.97 kg; 179.87 ± 3.72 cm; 1,709 ± 286 W; 2,927 ± 607 N; 241.7 ± 35.2 N·m, respectively). However, no significant differences (p > 0.05) were noted between forwards and backs during right concentric isokinetic knee extension (274.8 ± 37.7 and 246.8 ± 25.8 N·m), concentric isokinetic knee flexion for both left (158.8 ± 28.6 and 141.0 ± 22. 7 N·m) and right legs (155.3 ± 22.9 and 128.0 ± 23.9 N·m), eccentric isokinetic knee flexion and extension, hamstring quadriceps ratios, or vertical jump (37.25 ± 4.35 and 40.33 ± 6.38 cm). In comparison, relative measures demonstrated that backs performed significantly better compared to the forwards during the 40-kg jump squat (20.71 ± 5.15 and 19.91 ± 3.91 W·kg?1) and the isometric squat (34.32 ± 7.9 and 30.65 ± 5.34 N·kg?1). Bilateral comparisons revealed no significant differences (p > 0.05) between left and right leg performances in the agility test (3.26 ± 0.18 and 3.24 ± 0.18 seconds), or between left (0.7 ± 0.10) and right (0.71 ± 0.17) leg eccentric hamstring concentric quadriceps ratios. The results demonstrate that absolute strength and power measures are generally higher in forwards compared to in backs; however, when body mass is taken into account and relative measures compared, the backs outperform the forwards.     

Effects of different elastic cord assistance levels on vertical jump

Tran, TT, Brown, LE, Coburn, JW, Lynn, SK, Dabbs, NC, Schick, MK, Schick, EE, Khamoui, AV, Uribe, BP, and Noffal, GJ. Effects of different elastic cord assistance levels on vertical jump. J Strength Cond Res 25(12): 3472-3478, 2011-Currently, little research has been conducted using body weight reduction (BWR) as a means to enhance vertical jump. The purpose of this study was to determine the effects of different elastic cord assistance levels on vertical jump height (JH), takeoff velocity (TOV), relative ground reaction force (rGRF), relative impact force (RIF), and descent velocity (DV). Thirty recreationally trained college men and women (M = 15, W = 15) completed 3 testing sessions consisting of 5 conditions: 0, 10, 20, 30, and 40% BWR. In all BWR conditions, the subjects wore a full body harness while being attached to 2 elastic cords suspended from the ceiling and a linear velocity transducer. They then performed 3 maximal countermovement jumps with arm swing on a force plate. The results indicated no interaction of condition by sex for any variable; however, there was a significant (p < 0.05) main effect for condition for each variable. The JH significantly increased across all conditions (0%: 43.73 ± 1.62 cm, 40%: 64.77 ± 2.36 cm). The TOV at 30% (2.73 ± 0.34 m·s) was significantly greater than that at 0% (2.59 ± 0.39 m·s) and 10% (2.63 ± 0.34 m·s), whereas that at 40% (2.79 ± 0.43 m·s) was significantly greater than that at >0, 10, and 20%. The rGRF at 30% (18.62 ± 4.35 N·kg) was significantly greater than that at >0, 10, and 20%, whereas that at 40% (21.38 ± 5.21 N·kg) was significantly greater than in all conditions. The RIF at 20, 30, and 40% (40%: 61.60 ± 18.53 N·kg) was significantly greater than that at 0% (44.46 ± 9.12 N·kg). The DV at 20% (2.61 ± 0.31 m·s) was significantly greater than at 10%, whereas those at 30 and 40% (2.8 ± 0.41 m·s) were significantly greater than at 0, 10, and 20%. These results demonstrate that using different elastic cord levels to reduce body weight appears effective for increasing ascent and descent force and velocity variables. Future research should investigate greater BWR% and chronic training.     

Sustainability of critical power determined by a 3-minute all-out test in elite cyclists

Critical power (CP) is a theoretical workload representative of an athlete's maximal sustainable pace. Recent research has validated a 3-minute all-out test on a cycle ergometer for determining CP; however, few studies have investigated the sustainability of CP using this test. The purpose of this study was to determine the sustainability of CP established during the 3-minute test and the determinants of sustainability. A group of elite cyclists (N = 21) performed a VO2max test, 3-minute all-out test, and a time to exhaustion (TTE) trial at CP on 3 different days separated by at least 24 hours. Expired gases were collected during all trials and analyzed for VO2 and VCO2. Heart rate was measured by telemetry. Multiple regression was used to determine predictors of sustainability with significance predetermined at p < 0.05. VO2max was measured at 58.9 ± 5.6 ml·kg(-1)·min(-1), ventilation breakpoint at 44.9 ± 5.7 ml·kg(-1)·min(-1) (75% VO2max), and maximum heart rate at 179 ± 10 b·min(-1). Peak power (PP) in the 3-minute all-out test was measured at 738 ± 170 W, and CP was determined at 305 ± 32 W or 79% of VO2max. The VO2 at CP was 55.4 ± 6.9 ml·kg(-1)·min(-1), representing 94% of measured VO2max. The mean TTE at CP was 14.79 ± 8.38 minutes. The difference score of PP - CP significantly predicted TTE (r = 0.65, p < 0.05). No other measured variables contributed to this prediction. Based on sustainability, these data suggest that the 3-minute all-out test may overestimate CP in elite cyclists, which could lead to overtraining if CP determined with this test is used to identify training intensities.     

The effect of loading on kinematic and kinetic variables during the midthigh clean pull

The ability to develop high levels of muscular power is considered a fundamental component for many different sporting activities; however, the load that elicits peak power still remains controversial. The primary aim of this study was to determine at which load peak power output occurs during the midthigh clean pull. Sixteen participants (age 21.5 ± 2.4 years; height 173.86 ± 7.98 cm; body mass 70.85 ± 11.67 kg) performed midthigh clean pulls at intensities of 40, 60, 80, 100, 120, and 140% of 1 repetition maximum (1RM) power clean in a randomized and balanced order using a force plate and linear position transducer to assess velocity, displacement, peak power, peak force (Fz), impulse, and rate of force development (RFD). Significantly greater Fz occurred at a load of 140% (2,778.65 ± 151.58 N, p < 0.001), impulse within 100, 200, and 300 milliseconds at a load of 140% 1RM (196.85 ± 76.56, 415.75 ± 157.56, and 647.86 ± 252.43 N·s, p < 0.023, respectively), RFD at a load of 120% (26,224.23 ± 2,461.61 N·s, p = 0.004), whereas peak velocity (1.693 ± 0.042 m·s, p < 0.001) and peak power (3,712.82 ± 254.38 W, p < 0.001) occurred at 40% 1RM. Greatest total impulse (1,129.86 ± 534.86 N·s) was achieved at 140% 1RM, which was significantly greater (p < 0.03) than at all loads except the 120% 1RM condition. Results indicate that increased loading results in significant (p < 0.001) decreases in peak power and peak velocity during the midthigh clean pull. Moreover, if maximizing force production is the goal, then training at a higher load may be advantageous, with peak Fz occurring at 140% 1RM.     

Sweat rate prediction equations for outdoor exercise with transient solar radiation

We investigated the validity of employing a fuzzy piecewise prediction equation (PW) [Gonzalez et al. J Appl Physiol 107: 379-388, 2009] defined by sweat rate (m(sw), g·m(-2)·h(-1)) = 147 + 1.527·(E(req)) - 0.87·(E(max)), which integrates evaporation required (E(req)) and the maximum evaporative capacity of the environment (E(max)). Heat exchange and physiological responses were determined throughout the trials. Environmental conditions were ambient temperature (T(a)) = 16-26°C, relative humidity (RH) = 51-55%, and wind speed (V) = 0.5-1.5 m/s. Volunteers wore military fatigues [clothing evaporative potential (i(m)/clo) = 0.33] and carried loads (15-31 kg) while marching 14-37 km over variable terrains either at night (N = 77, trials 1-5) or night with increasing daylight (N = 33, trials 6 and 7). PW was modified (Pw,sol) for transient solar radiation (R(sol), W) determined from measured solar loads and verified in trials 6 and 7. PW provided a valid m(sw) prediction during night trials (1-5) matching previous laboratory values and verified by bootstrap correlation (r(bs) of 0.81, SE ± 0.014, SEE = ± 69.2 g·m(-2)·h(-1)). For trials 6 and 7, E(req) and E(max) components included R(sol) applying a modified equation Pw,sol, in which m(sw) = 147 + 1.527·(E(req,sol)) - 0.87·(E(max)). Linear prediction of m(sw) = 0.72·Pw,sol + 135 (N = 33) was validated (R(2) = 0.92; SEE = ±33.8 g·m(-2)·h(-1)) with PW β-coefficients unaltered during field marches between 16°C and 26°C T(a) for m(sw) ≤ 700 g·m(-2)·h(-1). PW was additionally derived for cool laboratory/night conditions (T(a) < 20°C) in which E(req) is low but E(max) is high, as: PW,cool (g·m(-2)·h(-1)) = 350 + 1.527·E(req) - 0.87·E(max). These sweat prediction equations allow valid tools for civilian, sports, and military medicine communities to predict water needs during a variety of heat stress/exercise conditions.     

Evidence that a higher ATP cost of muscular contraction contributes to the lower mechanical efficiency associated with COPD: preliminary findings

Impaired metabolism in peripheral skeletal muscles potentially contributes to exercise intolerance in chronic obstructive pulmonary disease (COPD). We used (31)P-magnetic resonance spectroscopy ((31)P-MRS) to examine the energy cost and skeletal muscle energetics in six patients with COPD during dynamic plantar flexion exercise compared with six well-matched healthy control subjects. Patients with COPD displayed a higher energy cost of muscle contraction compared with the controls (control: 6.1 ± 3.1% of rest·min(-1)·W(-1), COPD: 13.6 ± 8.3% of rest·min(-1)·W(-1), P = 0.01). Although, the initial phosphocreatine resynthesis rate was also significantly attenuated in patients with COPD compared with controls (control: 74 ± 17% of rest/min, COPD: 52 ± 13% of rest/min, P = 0.04), when scaled to power output, oxidative ATP synthesis was similar between groups (6.5 ± 2.3% of rest·min(-1)·W(-1) in control and 7.8 ± 3.9% of rest·min(-1)·W(-1) in COPD, P = 0.52). Therefore, our results reveal, for the first time that in a small subset of patients with COPD a higher ATP cost of muscle contraction may substantially contribute to the lower mechanical efficiency previously reported in this population. In addition, it appears that some patients with COPD have preserved mitochondrial function and normal energy supply in lower limb skeletal muscle.     

Influence of different relative intensities on power output during the hang power clean: identification of the optimal load

The influence of different relative intensities on power output was investigated in the present study in order to identify the optimal load that maximizes power output during the hang power clean. Fifteen men (age: 22.1 +/- 2.0 years, height: 180.1 +/- 6.3 cm, and body mass: 89.4 +/- 14.7 kg) performed the hang power cleans on a forceplate at 30-90% of one repetition maximum (1RM). Peak power was maximized at 70% 1RM, which was, however, not significantly different from peak power at 50, 60, 80, and 90% 1RM. Average power also was maximized at 70% 1RM, which was not significantly different from average power at 40, 50, 60, 80, and 90% 1RM. It was concluded that (a) the relative intensity had a significant influence on power output, and (b) power output can be maximized at a submaximal load during the hang power clean.     

Smith machine counterbalance system affects measures of maximal bench press throw performance

Equipment with counterbalance weight systems is commonly used for the assessment of performance in explosive resistance exercise movements, but it is not known if such systems affect performance measures. The purpose of this study was to determine the effect of using a counterbalance weight system on measures of smith machine bench press throw performance. Ten men and 14 women (mean ± SD: age, 25 ± 4 years; height, 173 ± 10 cm; weight, 77.7 ± 18.3 kg) completed maximal smith machine bench press throws under 4 different conditions (2 × 2; counterbalance × load): with or without a counterbalance weight system and using 'light' or 'moderate' net barbell loads. Performance variables (peak force, peak velocity, and peak power) were measured using a linear accelerometer attached to the barbell. The counterbalance weight system resulted in significant (p < 0.001) reductions in measures of peak force (mean difference ± standard error: light: -112 ± 20 N; moderate: -140 ± 23 N), peak velocity (light: -0.49 ± 0.10 m·s; moderate: -0.33 ± 0.07 m·s), and peak power (light: -220 ± 43 W; moderate: -143 ± 28 W) compared with no counterbalance system for both load conditions. Load condition did not affect absolute or percentage reductions from the counterbalance weight system for any variable. In conclusion, the use of a counterbalance weight system reduces accelerometer-based performance measures for the bench press throw exercise at light and moderate loads. This reduction in measures is likely because of an increase in the external resistance during the movement, which results in a discrepancy between the manually input and the actual value for external load. A counterbalance weight system should not be used when measuring performance in explosive resistance exercises with an accelerometer.     

Comparisons of peak ground reaction force and rate of force development during variations of the power clean

The aim of this investigation was to determine the differences in vertical ground reaction forces and rate of force development (RFD) during variations of the power clean. Elite rugby league players (n = 11; age 21 ± 1.63 years; height 181.56 ± 2.61 cm; body mass 93.65 ± 6.84 kg) performed 1 set of 3 repetitions of the power clean, hang-power clean, midthigh power clean, or midthigh clean pull, using 60% of 1-repetition maximum power clean, in a randomized order, while standing on a force platform. Differences in peak vertical ground reaction forces (F(z)) and instantaneous RFD between lifts were analyzed via 1-way analysis of variance and Bonferroni post hoc analysis. Statistical analysis revealed a significantly (p < 0.001) greater peak F(z) during the midthigh power clean (2,801.7 ± 195.4 N) and the midthigh clean pull (2,880.2 ± 236.2 N) compared to both the power clean (2,306.24 ± 240.47 N) and the hang-power clean (2,442.9 ± 293.2 N). The midthigh power clean (14,655.8 ± 4,535.1 N·s?1) and the midthigh clean pull (15,320.6 ± 3,533.3 N·s?1) also demonstrated significantly (p < 0.001) greater instantaneous RFD when compared to both the power clean (8,839.7 ± 2,940.4 N·s?1) and the hang-power clean (9,768.9 ± 4,012.4 N·s?1). From the findings of this study, when training to maximize peak F(z) and RFD the midthigh power clean and midthigh clean pull appear to be the most advantageous variations of the power clean to perform.     

Large differences in peak oxygen uptake do not independently alter changes in core temperature and sweating during exercise

The independent influence of peak oxygen uptake (Vo(? peak)) on changes in thermoregulatory responses during exercise in a neutral climate has not been previously isolated because of complex interactions between Vo(? peak), metabolic heat production (H(prod)), body mass, and body surface area (BSA). It was hypothesized that Vo(? peak) does not independently alter changes in core temperature and sweating during exercise. Fourteen males, 7 high (HI) Vo(? peak): 60.1 ± 4.5 ml·kg?1·min?1; 7 low (LO) Vo(? peak): 40.3 ± 2.9 ml·kg?1·min?1 matched for body mass (HI: 78.2 ± 6.1 kg; LO: 78.7 ± 7.1 kg) and BSA (HI: 1.97 ± 0.08 m2; LO: 1.94 ± 0.08 m2), cycled for 60-min at 1) a fixed heat production (FHP trial) and 2) a relative exercise intensity of 60% Vo(? peak) (REL trial) at 24.8 ± 0.6°C, 26 ± 10% RH. In the FHP trial, H(prod) was similar between the HI (542 ± 38 W, 7.0 ± 0.6 W/kg or 275 ± 25 W/m2) and LO (535 ± 39 W, 6.9 ± 0.9 W/kg or 277 ± 29 W/m2) groups, while changes in rectal (T(re): HI: 0.87 ± 0.15°C, LO: 0.87 ± 0.18°C, P = 1.00) and aural canal (T(au): HI: 0.70 ± 0.12°C, LO: 0.74 ± 0.21°C, P = 0.65) temperature, whole-body sweat loss (WBSL) (HI: 434 ± 80 ml, LO: 440 ± 41 ml; P = 0.86), and steady-state local sweating (LSR(back)) (P = 0.40) were all similar despite relative exercise intensity being different (HI: 39.7 ± 4.2%, LO: 57.6 ± 8.0% Vo(2 peak); P = 0.001). At 60% Vo(2 peak), H(prod) was greater in the HI (834 ± 77 W, 10.7 ± 1.3 W/kg or 423 ± 44 W/m2) compared with LO (600 ± 90 W, 7.7 ± 1.4 W/kg or 310 ± 50 W/m2) group (all P < 0.001), as were changes in T(re) (HI: 1.43 ± 0.28°C, LO: 0.89 ± 0.19°C; P = 0.001) and T(au) (HI: 1.11 ± 0.21°C, LO: 0.66 ± 0.14°C; P < 0.001), and WBSL between 0 and 15, 15 and 30, 30 and 45, and 45 and 60 min (all P < 0.01), and LSR(back) (P = 0.02). The absolute esophageal temperature (T(es)) onset for sudomotor activity was ～0.3°C lower (P < 0.05) in the HI group, but the change in T(es) from preexercise values before sweating onset was similar between groups. Sudomotor thermosensitivity during exercise were similar in both FHP (P = 0.22) and REL (P = 0.77) trials. In conclusion, changes in core temperature and sweating during exercise in a neutral climate are determined by H(prod), mass, and BSA, not Vo(? peak).     

Identifying factors related to Achilles tendon stress, strain, and stiffness before and after 6 months of growth in youth 10-14 years of age

The purposes of this study were (1) determine if youth peak Achilles tendon (AT) strain, peak AT stress, and AT stiffness, measured during an isometric plantar flexion, differed after six months (mos) of growth, and (2) determine if sex, physical activity level (Physical Activity Questionnaire (PAQ-C)), and/or growth rate (GR) were related to these properties. AT stress, strain, and stiffness were quantified in 20 boys (13.47±0.81 years) and 22 girls (11.18±0.82 years) at 2 times (0 and 6 mos). GR (change in height in 6 mos) was not significantly different between boys and girls (3.5±1.4 and 3.4±1.1cm/6 mos respectively). Peak AT strain and stiffness (mean 3.8±0.4% and 128.9±153.6N/mm, respectively) did not differ between testing sessions or sex. Peak AT stress (22.1±2.4 and 24.0±2.1MPa at 0 and 6 mos, respectively) did not differ between sex and increased significantly at 6 mos due to a significant decrease in AT cross-sectional area (40.6±1.3 and 38.1±1.6mm(2) at 0 and 6 mos, respectively) with no significant difference in peak AT force (882.3±93.9 and 900.3± 65.5N at 0 and 6 mos, respectively). Peak AT stress was significantly greater in subjects with greater PAQ-C scores (9.1% increase with 1 unit increase in PAQ-C score) and smaller in subjects with faster GRs (13.8% decrease with 1cm/6 mos increase in GR). These results indicate that of the AT mechanical properties quantified, none differed between sex, and only peak AT stress significantly differed after 6 months and was related to GR and physical activity.     

Cardiac function following prolonged exercise: influence of age

This study sought to determine the influence of age on the left ventricular (LV) response to prolonged exercise (PE; 150 min). LV systolic and diastolic performance was assessed using echocardiography (ECHO) before (pre) and 60 min following (post) exercise performed at 80% maximal aerobic power in young (28 ± 4.5 years; n = 18; mean ± SD) and middle-aged (52 ± 3.9 years; n = 18) participants. LV performance was assessed using two-dimensional ECHO, including speckle-tracking imaging, to determine LV strain (LV S) and LV S rate (LV SR), in addition to Doppler measures of diastolic function. We observed a postexercise elevation in LV S (young: -19.5 ± 2.1% vs. -21.6 ± 2.1%; middle-aged: -19.9 ± 2.3% vs. -20.8 ± 2.1%; P < 0.05) and LV SR (young: -1.19 ± 0.1 vs. -1.37 ± 0.2; middle-aged: -1.20 ± 0.2 vs. -1.38 ± 0.2; P < 0.05) during recovery in both groups. Diastolic function was reduced during recovery, including the LV SR ratio of early-to-late atrial diastolic filling (SR(e/a)), in young (2.35 ± 0.7 vs. 1.89 ± 0.5; P < 0.01) and middle-aged (1.51 ± 0.5 vs. 1.05 ± 0.2; P < 0.01) participants, as were conventional indices including the E/A ratio. Dobutamine stress ECHO revealed a postexercise depression in LV S in response to increasing dobutamine dose, which was similar in both young (pre-exercise dobutamine 0 vs. 20 μg·kg(-1)·min(-1): -19.5 ± 2.1 vs. -27.2 ± 2.2%; postexercise dobutamine 0 vs. 20 μg·kg(-1)·min(-1): -21.6 ± 2.1 vs. -23.7 ± 2.2%; P < 0.05) and middle-aged participants (pre: -19.9 ± 2.3 vs. -25.3 ± 2.7%; post: -20.8 ± 2.1 vs. -23.5 ± 2.7; P < 0.05). This was despite higher noradrenaline concentrations immediately postexercise in the middle-aged participants compared with young (4.26 ± 2.7 nmol/L vs. 3.00 ± 1.4 nmol/L; P = 0.12). These data indicate that LV dysfunction is observed following PE and that advancing age does not increase the magnitude of this response.     

Lactate response to different volume patterns of power clean

The ability to metabolize or tolerate lactate and produce power simultaneously can be an important determinant of performance. Current training practices for improving lactate use include high-intensity aerobic activities or a combination of aerobic and resistance training. Excessive aerobic training may have undesired physiological adaptations (e.g., muscle loss, change in fiber types). The role of explosive power training in lactate production and use needs further clarification. We hypothesized that high-volume explosive power movements such as Olympic lifts can increase lactate production and overload lactate clearance. Hence, the purpose of this study was to assess lactate accumulation after the completion of 3 different volume patterns of power cleans. Ten male recreational athletes (age 24.22 ± 1.39 years) volunteered. Volume patterns consisted of 3 sets × 3 repetition maximum (3RM) (low volume [LV]), 3 sets × 6 reps at 80-85% of 3RM (midvolume [MV]), and 3 sets × 9 reps at 70-75% of 3RM (high volume [HV]). Rest period was identical at 2 minutes. Blood samples were collected immediately before and after each volume pattern. The HV resulted in the greatest lactate accumulation (7.43 ± 2.94 mmol·L) vs. (5.27 ± 2.48 and 4.03 ± 1.78 mmol·L in MV and LV, respectively). Mean relative increase in lactate was the highest in HV (356.34%). The findings indicate that lactate production in power cleans is largely associated with volume, determined by number of repetitions, load, and rest interval. High-volume explosive training may impose greater metabolic demands than low-volume explosive training and may improve ability to produce power in the presence of lactate. The role of explosive power training in overloading the lactate clearance mechanism should be examined further, especially for athletes of intermittent sport.     

Aging and factors related to running economy

The purpose of this study was to investigate the relationship that age has on factors affecting running economy (RE) in competitive distance runners. Fifty-one male and female subelite distance runners (Young [Y]: 18-39 years [n = 18]; Master [M]: 40-59 years [n = 22]; and Older [O]: 60-older [n = 11]) were measured for RE, step rate, lactate threshold (LT), VO2max, muscle strength and endurance, flexibility, power, and body composition. An RE test was conducted at 4 different velocities (161, 188, 215, and 241 m·min(-1)), with subjects running for 5 minutes at each velocity. The steady-state VO2max during the last minute of each stage was recorded and plotted vs. speed, and a regression equation was formulated. A 1 × 3 analysis of variance revealed no differences in the slopes of the RE regression lines among age groups (y = 0.1827x - 0.2974; R2 = 0.9511 [Y]; y = 0.1988x - 1.0416; R2 = 0.9697 [M]; y = 0.1727x + 3.0252; R2 = 0.9618 [O]). The VO2max was significantly lower in the O group compared to in the Y and M groups (Y = 64.1 ± 3.2; M = 56.8 ± 2.7; O = 44.4 ± 1.7 mlO2·kg(-1)·min(-1)). The maximal heart rate and velocity @ LT were significantly different among all age groups (Y = 197 ± 4; M = 183 ± 2; O = 170 ± 6 b·min(-1) and Y = 289.7 ± 27.0; M = 251.5 ± 32.9; O = 212.3 ± 24.6 m·min(-1), respectively). The VO2max @ LT was significantly lower in the O group compared to in the Y and M groups (Y = 50.3 ± 2.0; M = 48.8 ± 2.9; O = 34.9 ± 3.2 mlO2·kg(-1)·min(-1)). The O group was significantly lower than in the Y and M groups in flexibility, power, and upper body strength. Multiple regression analyses showed that strength and power were significantly related to running velocity. The results from this cross-sectional analysis suggest that age-related declines in running performance are associated with declines in maximal and submaximal cardiorespiratory variables and declines in strength and power, not because of declines in running economy.     

Effects of self-selected music on strength, explosiveness, and mood

There has been much investigation into the use of music as an ergogenic aid to facilitate physical performance. However, previous studies have primarily focused on predetermined music and aerobic exercise. The purpose of this study was to investigate the effects of self-selected music (SSM) vs. those of no music (NM) on the mood and performance of the athletes performing bench press and squat jump. Twenty resistance trained collegiate men completed 2 experimental conditions, one while listening to SSM and the other with NM. The subjects reported their profile of mood states (POMS) and rating of perceived exertion (RPE) before and after performing 3 sets to failure of the bench press at 75% 1 repetition maximum (1RM) and 3 reps of the squat jump at 30% 1RM. Statistical analyses revealed no differences in squat jump height or relative ground reaction force, but the takeoff velocity (SSM-2.06 ± 0.17 m·s(-1); NM-1.99 ± 0.18 m·s(-1)), rate of velocity development (SSM-5.92 ± 1.46 m·s(-2); NM-5.63 ± 1.70 m·s(-2)), and rate of force development (SSM-3175.61 ± 1792.37 N·s(-1); NM-2519.12 ± 1470.32 N·s(-1)) were greater with SSM, whereas RPE (SSM-5.71 ± 1.37; NM-6.36 ± 1.61) was greater with NM. Bench press reps to failure and RPE were not different between conditions. The POMS scores of vigor (SSM-20.15 ± 5.58; NM-17.45 ± 5.84), tension (SSM-8.40 ± 3.99; NM-6.07 ± 3.26), and fatigue (SSM-8.65 ± 4.49; NM-7.40 ± 4.38) were greater with SSM. This study demonstrated increased performance during an explosive exercise and an altered mood state when listening to SSM. Therefore, listening to SSM might be beneficial for acute power performance.     

Occurrence of fatigue during sets of static squat jumps performed at a variety of loads

Research has identified that the optimal power load for static squat jumps (with no countermovement) is lower than the loads usually recommended for power training. Lower loads may permit the performance of additional repetitions before the onset of fatigue compared with heavier loads; therefore, the aim of this study was to determine the point of fatigue during squat jumps at various loads (0, 20, 40, 60% 1-repetition maximum [1RM]). Seventeen professional rugby league players performed sets of 6 squat jumps (with no countermovement), using 4 loading conditions (0, 20, 40, and 60% of 1RM back squat). Repeated measures analysis of variance revealed no significant differences (p > 0.05) in force, velocity, power, and displacement between repetitions, for the 0, 20, and 40% loading conditions. The 60% condition showed no significant difference (p > 0.05) in peak force between repetitions; however, velocity (1.12 + 0.10 and 1.18 + 0.11 m·s(-1)), power (3,385 + 343 and 3,617 + 396 W) and displacement (11.13 + 2.31 and 11.85 + 2.16 cm) were significantly (p < 0.02) lower during repetition 6 compared with repetition 2. These findings indicate that when performing squat jumps (with no countermovement) with a load <40% 1RM back squat, up to >6 repetitions can be completed without inducing fatigue and a minimum of 4-6 repetitions should be performed to achieve peak power output. When performing squat jumps (with no countermovement) with a load equal to the 60% 1RM only, 5 repetitions should be performed to minimize fatigue and ensure maintenance of velocity and power.     

Diurnal variation in Wingate-test performance and associated electromyographic parameters

The present study was designed to evaluate time-of-day effects on electromyographic (EMG) activity changes during a short-term intense cycling exercise. In a randomized order, 22 male subjects were asked to perform a 30-s Wingate test against a constant braking load of 0.087?kg·kg(-1) body mass during two experimental sessions, which were set up either at 07:00 or 17:00?h. During the test, peak power (P(peak)), mean power (P(mean)), fatigue index (FI; % of decrease in power output throughout the 30 s), and evolution of power output (5-s span) throughout the exercise were analyzed. Surface EMG activity was recorded in both the vastus lateralis and vastus medialis muscles throughout the test and analyzed over a 5-s span. The root mean square (RMS) and mean power frequency (MPF) of EMG were calculated. Neuromuscular efficiency (NME) was estimated from the ratio of power to RMS. Resting core temperature, P(peak), P(mean), and FI were significantly higher (p?相似文献