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Bekris, E, Pidoulas, G, Pidoulas, P, Gissis, I, Katis, A, and Komsis, S. Examination of physical fitness parameters between professional and amateur Greek soccer players during the transition period. J Strength Cond Res 35(3): 776-781, 2021-The aim of the study was to compare physical fitness parameters between professional and amateur soccer players of different levels. The sample consisted of 381 soccer players divided in 4 experimental groups: first division professional players (n = 115), second division professional players (n = 70), third division semiprofessional players (n = 93), and amateur soccer players (n = 103). Players were tested for several physiological parameters at the end of the transition period. Analysis of variance showed significantly lower body fat and increased maximum oxygen consumption (Vo2max) and velocity of maximum oxygen consumption (vVo2max) values for first division professional players compared with the other experimental groups (p < 0.05). Similarly, first division professional players showed higher performance during squat jump and countermovement jump test compared with the other experimental groups (p < 0.05). Significant differences on flexibility test were observed between amateur players and the other group (p < 0.05). The results of the study indicated that Greek soccer players at the highest level overcome in almost all the underexamination physiological parameters probably because of less absence from training and better implementation of training programs during the transition period.

To examine the association between the metabolic power paradigm during training and match-play and objective aerobic fitness measures within elite Gaelic football players. Twenty-five elite Gaelic football players completed objective physiological testing for VO2max, vVO2max, Peak treadmill Velocity (PTV), Running economy (RE) and selected blood lactate concentrations of 2 mmol L−1 (S2) and 4 mmol L−1 (S4). Aerobic testing was performed at the start of the season and at the halfway point of the season. Training and match-play running performances were recorded across the period with global positioning system technology (GPS; 4-Hz; VX Sport, Lower Hutt, New Zealand). Instantaneous raw velocity data were obtained from the GPS and exported to a customised spreadsheet which provided estimations of total distance (m), high-speed running distance (m; 17 km h−1), very-high-speed running distance (m; 22 km h−1), total accelerations (n), acceleration distance (m), peak and mean velocity (km h−1). Furthermore, changes in velocity were analysed which allowed for the assessment of the metabolic power paradigm during these training and match-play events. Players average metabolic power (Pmet; W Kg−1) observed to have a large association with VO2max (r = 0.76–0.88) and velocity at VO2max (r = 0.72–0.91) in training and match situations. Interestingly, peak treadmill velocity showed a moderate association with training and match-play high metabolic power distance (r = 0.56–0.76). Large associations were observed between high power distance during match and training categories and velocity at VO2max (r = 0.76–0.89). Furthermore, high power distance was observed to have a large association with peak treadmill velocity (r = 0.72–0.91) in training and match situations with lactate variables showing a small to moderate association with metabolic power variables. The current investigation is the first to provide evidence towards the ecological validity of the metabolic power paradigm to assess aerobic fitness within elite Gaelic football. Practitioners should consider the association between aerobic fitness and specific metabolic load paradigm variables within their monitoring system as a potential means to understand the impact of training plans within elite Gaelic football players.

The current investigation examined the effect of a periodized small-sided games (SSG) intervention across a 4-week pre-season period on physical and physiological performance measures within hurling players. Twenty-five (n = 25) hurling players were observed across the training intervention with GPS and HR technologies. Players participated in 12 sessions of exclusive 4 min SSG bouts (4 v 4) across differing pitch dimensions from 100 to 200-m2 with the number of bouts of SSG increasing across the intervention period (from 4 up to 8 bouts). Pre and post intervention tests included physiological (VO2max (mL kg−1 min−1), vVO2max (mL kg−1 min−1), PTV (km h−1), oxygen consumption (mL kg−1 min−1), vLT (mmol L−1), vOBLA (mmol L−1) and HRmax) and physical [5-, 10-, 20-m speed (s), Yo-YoIR1 (m) and RSAb (s)] testing methodologies. Across the period significant improvements in physical and physiological qualities were observed with these being trivial to large in nature. Significant large improvements in VO2max (ES 1.79; 95% CI 1.02–2.01) and vLT (ES 1.56; 95% CI 1.12–1.78) were reported with moderate improvements in vVO2max (ES 0.93; 95% CI 0.77–1.11) and vOBLA (ES 0.89; 95% CI 0.34–0.99) respectively. Moderate improvements in Yo-YoIR1 (ES 0.65; 95% CI 0.33–0.78) and RSAb (ES 0.41; 95% CI 0.21–0.66) were also observed across the period with trivial improvements observed for speed across 5-, 10- and 20-m. Furthermore, SSG also led to an improvement in oxygen consumption across varying speeds as indicated through significantly reduced VO2 and HR at running speeds of 8-, 10-, 12-, 14- and 16-km h−1 (ES 0.99–1.78). The present study provides coaches with a periodization strategy for pre-season hurling specific SSG. Overall, the data demonstrate that implementing a structured periodized SSG training intervention can improve the physical and physiological fitness characteristics of hurling players across a pre-season.

Current study aimed to establish percentile normative data and to find age differences in fitness performance tests of 14–19-year-old footballers played in a Greek elite youth football academy. A total of 216 male players from four different chronological age groups of the same club, from under 15 to under 19 (U-15, U16, U17 & U-19) for 5 consecutive years (2014–2018) who played in six different positions — as midfielders, defenders, wingbacks, wingers, forwards, and goalkeepers — participated in the study, with 426 measurements. Measured variables of weight, height, body mass index (BMI), squat jump (SJ), countermovement jump test (CMJ), countermovement jump test with arm swing (CMJAS) isokinetic strength peak torque (PT) ratio of hamstring (H) and quadriceps (Q) at speed of 60°·s−1, sit & reach test (i.e., flexibility), aerobic maximal exercise test on a treadmill to exhaustion (VO2max), and velocity at VO2max were recorded and compared among age groups during the period 2014–2018. Age and performance physical fitness parameters values (i.e., P3 to P97) were generated using Box–Cox power transformations. The elite footballers had mean age of 15.6 ± 1.4 years, body weight 66.7 ± 7.8 kg, height 1.757 ± 0.064 cm and BMI 21.6 ± 1.7 kg·m−2. Performance across all testing variables was increased according to age, with each age scoring higher/better than their younger counterparts from the U-15 squad up. Velocity at lactate threshold (VLth-Km/h) was 13.6, 13.4, 13.1, and 13.2 Km/h, for the four age groups respectively, and 203.5, 201.9, 187.8, and 177.4 Nm in extension of left quadriceps in 60°·s−1 peak torque, Q (Nm). Moreover, the U-19 presented superior performance in VO2max (Vvo2max) to the other age categories (18.2, 17.9, 17.4, and 17.3 km/h, respectively). Footballers’ flexibility and jump ability were more developed in U-19 age group compared with other group ages. Findings indicated that U-19 players performed better than younger players in all assessments. This may have been possible due to the differences in training experience, and individual levels of strength/power/endurance ability. Moreover, establishing normative performance values will allow practitioners to more accurately identify deficiencies in performance that are relative to their athletes.

Training intensity distribution is important to training program design. The zones 1 to 2 boundary can be defined by the Talk Test and the rating of perceived exertion. The zones 2 to 3 boundary can be defined by respiratory gas exchange, maximal lactate steady state, or, more simply, by critical speed (CS). The upper boundary of zone 3 is potential defined by the velocity at maximum oxygen uptake (vVO2max), although no clear strategy has emerged to categorize this intensity. This is not normally definable outside the laboratory. Purpose: This study predicts vVO2max from CS, determined from 1 (1.61 km) and 2 (3.22 km) citizen races in well-trained runners. Methods: A heterogeneous group of well-trained runners (N = 22) performed 1- and 2-mile races and were studied during submaximal and maximal treadmill running to measure oxygen uptake, allowing computation of vVO2max. This vVO2max was compared with CS. Results: vVO2max (4.82 [0.53] m·s−1) was strongly correlated with CS (4.37 [0.49] m·s−1; r = .84, standard error of estimate [SEE] = 0.132 m·s−1), 1-mile speed (5.09 [0.51] m·s−1; r = .84, SEE = 0.130 m·s−1), and 2-mile speed (4.68 [0.49] m·s−1; r = .86, SEE = 0.120 m·s−1). Conclusions: CS, calculated from 2 citizen races (or even training time trials), can be used to make reasonable estimates of vVO2max, which can be used in the design of running training programs.

Purpose We compared a new locomotor-specific model to track the expenditure and reconstitution of work done above critical power (W´) and balance of W´ (W´BAL) by modelling flat over-ground power during exhaustive intermittent running. Method Nine male participants completed a ramp test, 3-min all-out test and the 30–15 intermittent fitness test (30–15 IFT), and performed a severe-intensity constant work-rate trial (SCWR) at the maximum oxygen uptake velocity (vV̇O2max). Four intermittent trials followed: 60-s at vV̇O2max + 50% Δ1 (Δ1 = vV̇O2max − critical velocity [VCrit]) interspersed by 30-s in light (SL; 40% vV̇O2max), moderate (SM; 90% gas-exchange threshold velocity [VGET]), heavy (SH; VGET + 50% Δ2 [Δ2 = VCrit − VGET]), or severe (SS; vV̇O2max − 50% Δ1) domains. Data from Global Positioning Systems were derived to model over-ground power. The difference between critical and recovery power (DCP), time constant for reconstitution of W´ ($$\tau_{{W^{\prime}}}$$τW′), time to limit of tolerance (TLIM), and W´BAL from the integral (W´BALint), differential (W´BALdiff), and locomotor-specific (OG-W´BAL) methods were compared. Results The relationship between $$\tau_{{W^{\prime}}}$$τW′ and DCP was exponential (r2 = 0.52). The $$\tau_{{W^{{\prime}}}}$$τW′ for SL, SM, and SH trials were 119 ± 32-s, 190 ± 45-s, and 336 ± 77-s, respectively. Actual TLIM in the 30–15 IFT (968 ± 117-s) compared closely to TLIM predicted by OG-W´BAL (929 ± 94-s, P > 0.100) and W´BALdiff (938 ± 84-s, P > 0.100) but not to W´BALint (848 ± 91-s, P = 0.001). Conclusion The OG-W´BAL accurately tracked W´ kinetics during intermittent running to exhaustion on flat surfaces.

A number of factors determine neuromuscular economy (NE) and running economy (RE) in endurance-trained runners. The purpose of this investigation was to examine the relationship between aerobic fitness and NE in endurance-trained runners. Twenty-seven endurance-trained runners (25.1 ± 10.2 y) completed a maximal voluntary isometric contraction of the leg extensors to measure maximal electromyography (EMGmax) amplitude of the vastus lateralis (VL) and rectus femoris (RF), a steady-state treadmill run at 9.66, 11.27, and 12.87 km∙hr−1 and a maximal graded exercise test. Participants were outfitted with surface electrodes over the VL and RF muscles to record EMG amplitude throughout each test. During the steady-state test, the EMG (as a percentage of EMGmax) and oxygen consumption (VO2) over the final minute of each stage were established and considered NE and RE, respectively. Pearson product moment correlations were used to determine the relationships between VO2max and velocity at VO2max (vVO2max) and NE and RE. The results revealed significant negative correlations between VO2max and vVO2max and relative NE and RE at all three speeds. In addition, there were significant correlations between relative RE and NE at all three speeds. These results indicate that faster runners have improved NE and RE when expressed as a relative measure.

Background Running velocity associated with VO2max (vVO2max) is a parameter widely used for exercise prescription and is related to endurance performance. However, the vVO2max determination usually requires a maximal effort test and equipped laboratory for expired gas analysis, what make difficulty its assessment. Objective We aimed to test the validity of a simple method of vVO2max prediction through the heart rate cost of running (HRC) in a submaximal 6-min running test, both in treadmill and in a 400-meter track. Methods Male recreational runners (n = 16; 30.3 ± 8.0 years; VO2max of 46.2 ± 3.2 ml·kg−1·min−1) randomly underwent an incremental test in treadmill with gas analysis, and a 3000-m time trial in a track, to determine vVO2max. Before every maximal test, participants also performed a submaximal 6-min running (~85% HRmax), both in the treadmill and in a track, to assess HRC (bpm−1m·min−1) by dividing the submaximal running velocity by its respective HR. The vVO2max (km·h−1) was predicted by dividing the HRmax (bpm)/HRC (bpm−1m·min−1). Results No differences were verified (p > .05) among vVO2max determined both in the treadmill (13.8 ± 0.9 km·h−1) and track (13.6 ± 0.9 km·h−1) to those predicted by the HRC method both in treadmill (13.5 ± 0.8 km·h−1) and track (13.6 ± 1.0 km·h−1). The vVO2max measured directly with expired gas analysis was highly correlated with vVO2max estimated through HRC in treadmill and track (p Conclusion A submaximal 6-min exercise test protocol to assess HRC of running was considered valid to estimate vVO2max of recreational runners both in treadmill and outdoor track.

L-Arginine, the precursor of NO might be involved in improving the cardiovascular disorders via regulation of functional properties of erythrocytes.This study investigated the effects of L-Arginine supplementation on responses of red blood cell (RBC) properties to high intensity interval exercise (HIIE).Ten overweight healthy men participated voluntarily in the study and performed two HIIE trials with and without L-Arginine in two separate weeks. The HIIE protocol included 12 intervals of 3-min encompassed 1-min running at 100% of vVO2max and 2-min active recovery at 40% of vVO2max. Three blood samples were taken before and after supplementation, and immediately after exercise; and were used to measure red blood cell properties.The HIIE protocol increased hematocrit, hemoglobin and lactate significantly (P 0.05), but had no significant effect on RBC aggregation, RBC deformability, and fibrinogen concentration. When data were compared for two trials no significant differences between the responses of RBC properties to two HIIE protocols were detected (P 0.05), whereas the increases in lactate concentration following HIIE was significantly lower in L-Arginine than placebo trial (P 0.05).It is concluded that L-Arginine consumption prior to HIIE does not lead to any improvement in RBC properties during HIIE in overweight healthy men.

Aims: The study aimed to evaluate the effects of a backward running (BR) training program prescribed by the peak backward running velocity (Vpeak_BR) on physiological variables and a 3 km forward running (FR) performance. Methods: Eight untrained running male adults in running took place in the study. All the participants underwent five weeks of BR training prescribed based on Vpeak_BR. They performed a maximal incremental test on the treadmill to determine the maximal oxygen uptake (V̇O2max) and the velocity associated with V̇O2max (vV̇O2max). The participants were also tested on the track field to determine the Vpeak_BR and undertook a 3 km FR performance. All initial assessments were also performed after the training period. Results: The results showed statistically significant improvements in 3 km FR performance (14.2 ± 1.2 min vs. 13.5 ± 1.0 min) and Vpeak_BR (8.0 ± 0.8 km·h−1 vs. 8.5 ± 0.5 km·h−1) after the training period. Conclusion: BR training effectively improved 3 km FR performance and Vpeak_BR, demonstrating that Vpeak_BR determined according to the protocol proposed in this study can be used for the prescription of BR training. Further, BR training represents an effective training method that can be inserted into an FR running training program.

Objectives Recent studies investigated the determinants of trail running performance (i.e., combining uphill (UR) and downhill running sections (DR)), while the possible specific physiological factors specifically determining UR vs DR performances (i.e., isolating UR and DR) remain presently unknown. This study aims to determine the cardiorespiratory responses to outdoor DR vs UR time-trial and explore the determinants of DR and UR performance in highly trained runners. Design Randomized controlled trial. Methods Ten male highly-trained endurance athletes completed 5-km DR and UR time-trials (average grade: ±8%) and were tested for maximal oxygen uptake, lower limb extensor maximal strength, local muscle endurance, leg musculotendinous stiffness, vertical jump ability, explosivity/agility and sprint velocity. Predictors of DR and UR performance were investigated using correlation and commonality regression analyses. Results Running velocity was higher in DR vs UR time-trial (20.4 ± 1.0 vs 12.0 ± 0.5 km·h−1, p 0.05) despite lower average VO2 (85 ± 8% vs 89 ± 7% VO2max; p Conclusions Five-km UR and DR running performances are both well explained by three independent predictors. If two predictors are shared between UR and DR performances (vVO2max and maximal strength), their relative contribution is different and, importantly, the third predictor appears very specific to the exercise modality (BMI for UR vs leg musculotendinous stiffness for DR).

This study aimed to compare the aerobic power (treadmill running) and muscle power (bench press and bench pull) of Junior/U23 paddlers from Slovakia who won medals in international championships with that of those who did not take the podium. Forty-three Slovak Junior/U23 paddlers (sprint = 24, medalists = 8, non-medalists = 16; slalom = 19, medalists = 11, non-medalists = 8) were tested in 2018 and 2019 after the world championships. The maximal oxygen uptake (VO2max) and the velocity at maximal oxygen uptake (vVO2max) were determined by the incremental running protocol (0% slope and 1 km⋅h–1increments every minute until volitional exhaustion). Mean maximal power from the entire concentric phase was recorded during bench press and bench pull exercises by the validated TENDO weightlifting analyzer. No interaction was obtained between medal and canoe discipline for VO2max(p= 0.069,F= 3.495), vVO2max(p= 0.552,F= 0.361) and absolute (bench press:p= 0.486,F= 0.495; bench pull:p= 0.429,F= 0.640) or relative (bench press:p= 0.767,F= 0.089; bench pull:p= 0.696,F= 0.155) mean maximal power. Conversely, a significant effect for the medal on the bench press (absolutep= 0.017,F= 6.170; relativep= 0.043,F= 4.384) and the bench pull (absolutep= 0.041,F= 4.470) mean maximal power were observed. Our study indicates the absolute mean power on the bench press as a prerequisite for success in international Junior/U23 championships of slalom and sprint canoeing. However, the mean power on bench pull seems to have a deeper influence on sprint paddlers when compared to slalom athletes. Regarding the aerobic power, the data from the treadmill testing did not reveal outcomes between medalists and non-medalists. This result can be associated with the lack of specificity of the incremental treadmill testing for canoeing, and future studies are encouraged to propose specific protocols to compare the aerobic power of medalists and non-medalists in international slalom and sprint championships.

Physiological variables such as maximal oxygen uptake (VO2max), velocity at maximal oxygen uptake (vVO2max), running economy (RE) and changes in lactate levels are considered the main factors determining performance in long-distance races. The aim of this review was to present the mathematical models available in the literature to estimate performance in the 5000 m, 10,000 m, half-marathon and marathon events. Eighty-eight articles were identified, selections were made based on the inclusion criteria and the full text of the articles were obtained. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables were also included by athletic specialty. A total of 58 studies were included, from 1983 to the present, distributed in the following categories: 12 in the 5000 m, 13 in the 10,000 m, 12 in the half-marathon and 21 in the marathon. A total of 136 independent variables associated with performance in long-distance races were considered, 43.4% of which pertained to variables derived from the evaluation of aerobic metabolism, 26.5% to variables associated with training load and 20.6% to anthropometric variables, body composition and somatotype components. The most closely associated variables in the prediction models for the half and full marathon specialties were the variables obtained from the laboratory tests (VO2max, vVO2max), training variables (training pace, training load) and anthropometric variables (fat mass, skinfolds). A large gap exists in predicting time in long-distance races, based on field tests. Physiological effort assessments are almost exclusive to shorter specialties (5000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate coefficients of determination. The variables of note in the marathon category are fundamentally those associated with training and those derived from physiological evaluation and anthropometric parameters.

Purpose The aim of this study was to assess the effects of adding shoe mass on running economy (RE), gait characteristics, neuromuscular variables and performance in a group of trained runners. Methods Eleven trained runners (6 men and 5 women) completed four evaluation sessions separated by at least 7 days. The first session consisted of a maximal incremental test where the second ventilatory threshold (VT2) and the speed associated to the VO2max(vVO(2max)) were calculated. In the next sessions, RE at 75, 85, and 95% of the VT(2)and the time to exhaustion (TTE) at vVO(2max)were assessed in three different shoe mass conditions (control, +50 g and +100 g) in a randomized, counterbalanced crossover design. Biomechanical and neuromuscular variables, blood lactate and energy expenditure were measured during the TTE test. Results RE worsened with the increment of shoe mass (Control vs. 100 g) at 85% (7.40%, 4.409 +/- 0.29 and 4.735 +/- 0.27 kJ.kg(-1).km(-1),p= 0.021) and 95% (10.21%, 4.298 +/- 0.24 and 4.737 +/- 0.45 kJ.kg(-1).km(-1),p= 0.005) of VT2. HR significantly increased with the addition of mass (50 g) at 75% of VT2(p= 0.01) and at 75, 85, and 95% of VT2(p= 0.035, 0.03, and 0.03, respectively) with the addition of 100 g. TTE was significantly longer (similar to 22%, similar to 42 s,p= 0.002,ES= 0.149) in the Control condition vs. 100 g condition, but not between Control vs. 50 g (similar to 24 s,p= 0.094,ES= 0.068). Conclusion Overall, our findings suggest that adding 100 g per shoe impairs running economy and performance in trained runners without changes in gait characteristics or neuromuscular variables. These findings further support the use of light footwear to optimize running performance.

Purpose The aim of this study was to verify whether physiological components [vertical jumps (Squat Jump - SJ and Countermovement Jump - CMJ), eccentric utilization ratio (EUR) of vertical jumps, running economy (RE), metabolic cost (C MET ), first and second ventilatory threshold (VT1 and VT2) maximal oxygen uptake (VO2MAX)] can predict maximal endurance running performance. Methods Twenty male runners performed maximal vertical jumps, submaximal running at constant speeds, and maximal incremental running test. Before, we measured anthropometric parameters (body mass and height) and registered the training history and volume. SJ and CMJ tests were evaluated prior to running tests. Initially, the oxygen uptake (VO2) was collected at rest in the orthostatic position for 6 min. Soon after, a 10-min warm-up was performed on the treadmill at 10 km⋅h-1, followed by two 5-min treadmill rectangular tests at 12 and 16 km⋅h-1 monitored by a gas analyzer. After that, the runners performed a maximal incremental test, where the VT1, VT2, and VO2MAX were evaluated, as well as the maximum running speed (vVO2MAX). Thus, RE and C MET were calculated with data obtained during rectangular running tests. Multivariate stepwise regression analyses were conducted to measure the relationship between independent variables (height and power of SJ and CMJ, EUR; RE and C MET 12 and 16 km⋅h-1; VT1, VT2, and VO2MAX), as predictors of maximal running performance (vVO2MAX), with significance level at α = 0.05. Results We found that VO2MAX and RE at 16 km⋅h-1 predict 81% of performance (vVO2MAX) of endurance runners (p < 0.001). Conclusion The main predictors of the maximal incremental running test performance were VO2MAX and RE.

This study investigated the effects of chronic 3-day beetroot juice (BRJ) supplementation on maximum oxygen uptake (VO2max), velocity associated with VO2max(vVO2max), and peak velocity (Vpeak) in recreational runners. Thirteen male recreational runners (age 28.2 ± 3.0 years, height 176.8 ± 0.1 cm, body mass 74.4 ± 9.5 kg) performed four tests on a treadmill in a randomized, double-blind, crossover design: two maximum incremental tests to determine VO2max and vVO2max, and two tests to determine Vpeak. Trials were performed following 3 days of supplementation of NO3−-rich BRJ in natura (8.4 mmol NO3− day− 1) or BRJ NO3−-depleted placebo (0.01 mmol NO3− day− 1), with the last dose being ingested 2 h before each test. During the tests, maximum heart rate (HRmax), maximal rating of perceived exertion (RPEmax), pre- and post-test glucose concentrations (Glucpre, Glucpost), and peak blood lactate concentration were determined. VO2max was higher following BRJ vs PLA (46.6 ± 6.4 vs 45.1 ± 5.8 mL kg− 1 min− 1; P = 0.022), as well as vVO2max (14.5 ± 0.8 vs 13.9 ± 1.0 km h− 1P = 0.024) and Vpeak (15.5 ± 1.1 vs 15.2 ± 1.2 km h− 1P = 0.038), with no differences in the other variables. Consumption of NO3−-rich BRJ in natura (8.4 mmol NO3− day− 1) once per day for 3 days improved VO2max, vVO2max and Vpeak in recreational runners without changing the other analyzed variables.

O presente estudo averiguou se as diferenças nas circunstâncias (esteira vs. pista) de avaliação da velocidade crítica (VC) interferem no valor e na relação com a desempenho em 3000 metros (v3000m) e, assim, indicar a especificidade de cada valor como parâmetro de treinamento para esta distância. Sete corredores (15,3±1,4 anos) submeteram-se a um teste progressivo máximo (incrementos de 1,0 km×h-1×min-1, até a exaustão) para avaliação do V̇O2max e velocidade aeróbia máxima (vV̇O2max). A seguir, a VC foi estimada a partir do desempenho de corrida em três diferentes intensidades do exercício, em cada ambiente de avaliação, registrando-se o tempo-limite (tLim) nas distâncias de 900, 2100 e 3300 metros na pista, e à 90, 95 e 115% vV̇O2max em esteira. Ajustes lineares, pelo método “stepwise”, forneceram os parâmetros VC em esteira (VCESTEIRA) e pista (VCPISTA), que foram comparados pelo teste de Mann-Whitney. O coeficiente de dispersão ajustado à amostra (R2 aj) averiguou a variância de v3000m com VCPISTA, VCESTEIRAe vV̇O2max. Em todas as análises adotou-se P≤0,05. No teste progressivo, o V̇O2max atingiu 54,2±5,2 mLO2∙kg-1∙min-1 e a vV̇O2max foi 16,8±1,9 km×h-1. Não se observaram diferenças entre VCESTEIRA e VCPISTA (14,0±1,8 vs. 12,3±3,2 km∙h-1, P=0,46). Houveram correlações entre v3000m com VCESTEIRA (R2 aj ~0,94), VCPISTA (R2 aj ~0,99) e vV̇O2max (R2 aj ~0,90), todas com P=0,001. Conclui-se que o contexto de avaliação não interfere na consistência do valor de VC. Porém, quanto à relação com v3000 metros, a VCPISTA apresenta melhor especificidade, tornando-a mais autêntica que VCESTEIRA para a prescrição do treino e monitoramento do desempenho.

Objectives Ongoing debates about benefits and risks of barefoot- and minimally-shod running have, to date, revealed no conclusive findings for long-term effects on physical performance. The purpose of this study was to examine the effects of an 8-week transition to minimalist footwear (MFW) on running economy (RE). Design Randomised controlled trial. Methods Thirty-two male, habitually-shod runners were assigned randomly to an 8-week training intervention either in minimalist (=intervention group) or conventional running shoes (=control group). The intervention consisted of a gradual increase in use of the new footwear by 5% of the individual weekly distance. Before and after the intervention, a VO2max test was followed by a submaximal RE test at 70% and 80% of vVO2max in both shoe conditions 7 days later. RE was measured at the submaximal tests and expressed as caloric unit cost (kcal kg−1 km−1) and oxygen consumption (ml kg−1 km−1). Results RE improved in the intervention group over time compared to the control group with small to moderate effect sizes (ES) in both shoe conditions: Effects on RE (kcal kg−1 km−1) in conventional running shoes: ES vVO270%: 0.68 (95% CI: −0.14 to 1.51), ES vVO280%: 0.78 (95% CI: 0–1.56). In minimalist footwear: ES vVO270%: 0.3 (95% CI: −0.54 to 1.14), ES vVO280%: 0.42 (95% CI: −0.41 to 1.25). These effects were not statistically significant (p > 0.05). The repeated-measures ANOVA also showed no group by time interactions for all submaximal RE testing conditions (p > 0.05). Conclusions Although not reaching statistical significance, training in MFW compared to CRS resulted in small to moderate improvements in RE.

Introduction: Knowing which physiological variables predict running performance could help coaches to optimize training prescription to improve running performance. Objective: The present study investigated which physiological respiratory responses could predict 3000-m running performance. Methods: Seventeen amateur runners (29.82±7.1years; 173.12±9.0cm; 64.59±9.3kg) performed a maximal graded running test on a treadmill. The ventilatory threshold (VT), respiratory compensation point (RCP), and maximal oxygen consumption (VO2max) were assessed, as well as the respective velocities (vVT, vRCP, vVO2max). After 72 to 96 hours the runners performed the 3000-m running field test. The relationships between variables were performed using Pearson product momentum correlations. Thereafter, simple and multiple regression models were applied. The significance level adopted was 5% (p

Critical power (CP) demarcates the boundary between heavy and very heavy exercise intensity domains, and therefore, the power output (PO) that can be sustained at the maximal metabolic steady-state during constant-PO exercise (i.e., maximal lactate steady-state (MLSS)). However, the estimated CP does not always reflect a sustainable intensity of exercise, where blood lactate concentration ([La]) and oxygen uptake ( V ˙ O2) reach a plateau. Objectives To test cyclists’ ability to predict their highest PO associated with metabolic steady-state based on their own perception of effort. Design Repeated measures. Methods Thirteen healthy young cyclists (26 ± 3years; 69.0 ± 9.2 kg; 174 ± 10 cm) were tested. Five time-to-exhaustion trials were used to derive CP based on a 2-parameter hyperbolic model (CPHYP). Participants performed two 30-min rides at a self-selected PO that they considered their highest sustainable exercise intensity (CPSELF). Additionally, MLSS was determined as the highest PO at which variation in [La] ≤1.0 mmol L−1 between the 10th and 30th min was observed during a 30-min ride. Results Mean PO at CPSELF (233 ± 42 W) was similar (p > 0.05) to MLSS (233 ± 41 W), whereas CPHYP (253 ± 44 W) consistently overestimated (p 0.05), whereas the LOA between CPHYP and CPSELF were −40 to 0 W (bias = −20 W, p 0.05) metabolic response (i.e., V ˙ O2, [La], and HR). Conclusions Compared to CPHYP, CPSELF may offer a more precise approach to predict the constant-PO associated with maximal physiological steady-state.

This study investigated the effect of 5 days of controlled short-term heat acclimation (STHA) on the determinants of endurance performance and 5-km performance in runners, relative to the impairment afforded by moderate heat stress. A control group (CON), matched for total work and power output (2.7 W·kg−1), differentiated thermal and exercise contributions of STHA on exercise performance. Seventeen participants (10 STHA, 7 CON) completed graded exercise tests (GXTs) in cool (13 °C, 50% relative humidity (RH), pre-training) and hot conditions (32 °C, 60% RH, pre- and post-training), as well as 5-km time trials (TTs) in the heat, pre- and post-training. STHA reduced resting (p = 0.01) and exercising (p = 0.04) core temperature alongside a smaller change in thermal sensation (p = 0.04). Both groups improved the lactate threshold (LT, p = 0.021), lactate turnpoint (LTP, p = 0.005) and velocity at maximal oxygen consumption (vV̇O2max; p = 0.031) similarly. Statistical differences between training methods were observed in TT performance (STHA, −6.2(5.5)%; CON, −0.6(1.7)%, p = 0.029) and total running time during the GXT (STHA, +20.8(12.7)%; CON, +9.8(1.2)%, p = 0.006). There were large mean differences in change in maximal oxygen consumption between STHA +4.0(2.2) mL·kg−1·min−1 (7.3(4.0)%) and CON +1.9(3.7) mL·kg−1·min−1 (3.8(7.2)%). Running economy (RE) deteriorated following both training programmes (p = 0.008). Similarly, RE was impaired in the cool GXT, relative to the hot GXT (p = 0.004). STHA improved endurance running performance in comparison with work-matched normothermic training, despite equality of adaptation for typical determinants of performance (LT, LTP, vV̇O2max). Accordingly, these data highlight the ergogenic effect of STHA, potentially via greater improvements in maximal oxygen consumption and specific thermoregulatory and associated thermal perception adaptations absent in normothermic training.

[Abstract]: This study compared the ability to predict performance in half-marathon races through physiological variables obtained in a laboratory test and performance variables obtained in the Cooper field test. Twenty-three participants (age: 41.6 7.6 years, weight: 70.4 8.1 kg, and height: 172.5 6.3 cm) underwent body composition assessment and performed a maximum incremental graded exercise laboratory test to evaluate maximum aerobic power and associated cardiorespiratory and metabolic variables. Cooper’s original protocol was performed on an athletic track and the variables recorded were covered distance, rating of perceived exertion, and maximum heart rate. The week following the Cooper test, all participants completed a half-marathon race at the maximum possible speed. The associations between the laboratory and field tests and the final time of the test were used to select the predictive variables included in a stepwise multiple regression analysis, which used the race time in the half marathon as the dependent variable and the laboratory variables or field tests as independent variables. Subsequently, a concordance analysis was carried out between the estimated and actual times through the Bland-Altman procedure. Significant correlations were found between the time in the half marathon and the distance in the Cooper test (r = -0.93; p < 0.001), body weight (r = 0.40; p < 0.04), velocity at ventilatory threshold 1, (r = -0.72; p < 0.0001), speed reached at maximum oxygen consumption (vVO2max), (r = -0.84; p < 0.0001), oxygen consumption at ventilatory threshold 2 (VO2VT2) (r = -0.79; p < 0.0001), and VO2max (r = -0.64; p < 0.05). The distance covered in the Cooper test was the best predictor of time in the half-marathon, and might predicted by the equation: Race time (min) = 201.26 – 0.03433 (Cooper test in m) (R2 = 0.873, SEE: 3.78 min). In the laboratory model, vVO2max, and body weight presented an R2 = 0.77, SEE 5.28 min. predicted by equation: Race time (min) = 156.7177 – 4.7194 (vVO2max) – 0.3435 (Weight). Concordance analysis showed no differences between the times predicted in the models the and actual times. The data indicated a high predictive power of half marathon race time both from the distance in the Cooper test and vVO2max in the laboratory. However, the variable associated with the Cooper test had better predictive ability than the treadmill test variables. Finally, it is important to note that these data may only be extrapolated to recreational male runners.

This study aimed to investigate the effects of beta2‐agonist terbutaline sulfate (TER) at a supra‐therapeutic dose (8 mg) on aerobic exercise performance. Twelve (6 females and 6 males) amateur athletes familiarized with all experimental procedures had their anthropometric data obtained on day 1. On days 2 and 3 either 8 mg of TER or a placebo (PLA) was administered orally (double‐blind manner) to participants who had rested for 3 h prior to aerobic exercise performance 20 m multistage fitness test (MSFT)]. This test was used to predict maximal oxygen uptake (VO2max) and velocity at which VO2max occurs (vVO2max). The Borg rating of perceived exertion (RPE), cardiovascular variables [heart rate (HR) and blood pressure (BP)] and blood glucose concentration [BGC] were obtained 15 min pre‐ and immediately post‐MSFT. Significant mean group differences were reported between PLA and TER groups (p < 0.05), respectively, in the RPE (15.6 ± 1.2 vs. 17.3 ± 1.5 a.u.), maximum heart rate (HRmax: 191.2 ± 7.1 vs. 197.2 ± 8.6 bpm) and BGC (118.4 ± 18.3 vs. 141.2 ± 15.8 mg/dL) post‐MSFT. The main effect of gender (male vs. female) in TER and PLA groups (p< 0.05) was observed, with higher estimated VO2max, vVO2max, HRmax and a lower mean HR pre‐test in male than female athletes. For these reasons, the inclusion of TER in the Prohibited List should be re‐discussed because of the lack of ergogenic effects.

The aim of the present study was to examine the role of the classical physiological model of endurance running performance - maximal oxygen uptake (VO(2)max), %VO(2)max at ventilatory thresholds (VT), work economy, lactate levels, and body composition on the prediction of short trail running performance. Eleven male trail runners (age 36.1 +/- 6.5 years, sport experience 6.6 +/- 3.8 years, and mean +/- standard deviation) were examined for fat mass and skeletal muscle mass, and performed a graded exercise test to measure VO(2)max, vVO(2)max, and VT. Also, they participated in a short 27 km trail run with a positive elevation of +1750 m. Age, years of training and skeletal muscle mass did not correlate with race time (P > 0.05), and fat mass and body mass index (BMI) showed significant correlations with race time (P < 0.05). Heart rate, velocity and VT1 and VT2 were not associated with race time (P > 0.05). Only vVO(2)max (P = 0.005) and VO(2)max (P = 0.007) is correlated to race time. Multiple regression models for VO(2)max accounted for 57% of the total variance. The vVO(2)max model variable accounted for 60% and the fat mass model for 59.5%. Finally, the combined VO(2)max and fat mass model explained 83.9% of the total variance (P < 0.05 in all models). The equation for this model is "race time (min) = 203.9956-1.9001 x VO(2)max + 10.2816 x Fat mass%" (R-2 = 0.839, SEE = 11.1 min, and P = 0.0007). The classical variable VO(2)max together with fat mass percent are two strong predictors for short trail running performance.

Michaelides, MA, Parpa, KM, and Zacharia, AI. Effects of an 8-week pre-seasonal training on the aerobic fitness of professional soccer players. J Strength Cond Res XX(X): 000-000, 2019-Pre-season in soccer training develops the physical requisites for competition and usually consists of a high volume of aerobic and anaerobic conditioning training including friendly games. The purpose of the study was to determine the effects of pre-season training on the aerobic fitness of professional soccer players. Nineteen professional male soccer players (age = 27.37 ± 3.67 years, height = 179.61 ± 5.17 cm, and body fat percentage = 11.3 ± 3.19%) participated in this study performed an incremental cardiopulmonary exercise testing on a treadmill before and after the 8 weeks of pre-season preparation. The results were analyzed using paired t tests, revealing significant differences on several indices. The subjects improved significantly on maximal aerobic capacity (V[Combining Dot Above]O2max) and lasted significantly longer on the treadmill (p < 0.05). The V[Combining Dot Above]O2 at ventilatory threshold (VT) and respiratory compensation point (RCP) increased significantly (p < 0.05). The running velocity at ventilatory thresholds (vVT and vRCP) and at V[Combining Dot Above]O2 max (vVO2max) also increased significantly (p < 0.05). In conclusion, the results of this study, as expected, demonstrated that the proposed 8 weeks of pre-season training program was sufficient to cause significant improvements on the aerobic performance indices of professional soccer players. The study confirms the beneficial changes in the process of adaptations that occur with this type of training and can assist coaches and trainers in planning a successful pre-season training program.

This study compared the effects of 4 weeks of training prescribed by peak velocity (Vpeak) or velocity associated with maximum oxygen uptake (vVO2max) in moderately trained endurance runners. Study participants were 14 runners (18–35 years) randomized into 2 groups, named group VO2 (GVO2) and group Vpeak (GVP). The GVO2 had training prescribed by vVO2max and its time limit (tlim), whereas the GVP had training prescribed by Vpeak and its tlim. Four tests were performed on a treadmill: 2 maximum incremental for Vpeak and vVO2max and 2 for their tlim. Performance (10 km) was evaluated on a 400 m track. Evaluations were repeated after 4 weeks of endurance training. The results showed a significant effect of training on Vpeak [GVP (16.7±1.2–17.6±1.5 km.h−1), GVO2 (17.1±1.9–17.7±1.6 km·h−1)]; vVO2max [GVP (16.4±1.4–17.0±1.3 km·h−1), GVO2 (17.2±1.7–17.5±1.9 km·h−1)]; and 10 km performance [GVP (41.3±2.4–39.9±2.7 min), GVO2 (40.1±3.4–39.2±2.9 min)]. The Vpeak highly correlated with performance in both pre- and post-training in GVP (–0.97;–0.86) and GVO2 (–0.95;–0.94), as well as with vVO2max in GVP (–0.82;–0.88) and GVO2 (–0.99; –0.98). It is concluded that training prescribed by Vpeak promoted similar improvements compared to training prescribed by vVO2max. The use of Vpeak is recommended due to its practical application and the low cost of determination.

The post‐exercise hepcidin response during prolonged ( > 2 weeks) hypoxic exposure is not well understood. We compared plasma hepcidin levels 3 h after exercise [6 × 1000 m at 90% of maximal aerobic running velocity (vVO2max)] performed in normoxia and normobaric hypoxia (3000 m simulate altitude) 1 week before, and during 14 days of normobaric hypoxia [196.2 ± 25.6 h (median: 200.8 h; range: 154.3–234.8 h) at 3000 m simulated altitude] in 10 well‐trained distance runners (six males, four females). Venous blood was also analyzed for hepcidin after 2 days of normobaric hypoxia. Hemoglobin mass (Hbmass) was measured via CO rebreathing 1 week before and after 14 days of hypoxia. Hepcidin was suppressed after 2 (Cohen's d = −2.3, 95% confidence interval: [−2.9, −1.6]) and 14 days of normobaric hypoxia (d = −1.6 [−2.6, −0.6]). Hepcidin increased from baseline, 3 h post‐exercise in normoxia (d = 0.8 [0.2, 1.3]) and hypoxia (d = 0.6 [0.3, 1.0]), both before and after exposure (normoxia: d = 0.7 [0.3, 1.2]; hypoxia: d = 1.3 [0.4, 2.3]). In conclusion, 2 weeks of normobaric hypoxia suppressed resting hepcidin levels, but did not alter the post‐exercise response in either normoxia or hypoxia, compared with the pre‐exposure response.

This study analysed the effects of two different periodization strategies on physiological parameters at various exercise intensities in competitive swimmers. Seventeen athletes of both sexes were divided to two groups, the traditional periodization (TPG, n = 7) and the reverse periodization group (RPG, n = 10). Each group followed a 10-week training period based on the two different periodization strategies. Before and after training, swimming velocity (SV), energy expenditure (EE), energy cost (EC) and percentage of aerobic (%Aer) and anaerobic (%An) energy contribution to the swimming intensities corresponding to the aerobic threshold (AerT), the anaerobic threshold (AnT) and the velocity at maximal oxygen uptake (vVO2max) were measured. Both groups increased the %An at the AerT and AnT intensity (P ≤ .05). In contrast, at the AnT intensity, EE and EC were only increased in TPG. Complementary, %Aer, %An, EE and EC at vVO2max did not alter in both groups (P > .05); no changes were observed in SV in TPG and RPG at all three intensities. These results indicate that both periodization schemes confer almost analogous adaptations in specific physiological parameters in competitive swimmers. However, given the large difference in the total training volume between the two groups, it is suggested that the implementation of the reverse periodization model is an effective and time-efficient strategy to improve performance mainly for swimming events where the AnT is an important performance indicator. Sin financiación 2.576 JCR (2017) Q2, 22/81 Sport Sciences 1.122 SJR (2017) Q1, 480/2878 Medicine (miscellaneous), 44/285 Orthopedics and Sports Medicine, 24/201 Physical Therapy, Sports Therapy and Rehabilitation; Q2, 34/127 Sports Science No data IDR 2017 UEM

Objective To explore the association between the polymorphism of angiotensin II receptor type 1 gene(AGTR1) and elite endurance athlete performance and the mechanism of how the polymorphism works. Methods (1) Polymorphism of AGTR1 rs5182 between 122 elite Chinese endurance athletes and 222 controls were analyzed by MALDI-TOF-MS. (2) Aerobic capacity of 79 elite Chinese endurance athletes such as VC/FEV1/MVV/ VO2AT/ HRAT/ VAT/ VO2max/ HRmax/ VVO2max were measured and association between rs5182 polymorphism and the performance was analyzed. (3) PcDNA3.1-AGTR1 -T and pcDNA3.1-AGTR1-C plasmid were build and the plasmids was transfected into mammalian 293T cells. mRNA levels were detected after 48 hours. Statistical analysis was performed using SPSS software version 15.0. Values of P < 0.05 were considered statistically significant. Continuous data were expressed as mean ± SD, while categorical data were expressed as frequencies. Genotype distribution and allele frequencies between athletes and control subjects were compared using χ2 tests. Aerobic performance data was analyzed with One-Way ANOVA if it conformed to normal distribution and homogeneity of variance otherwise Non-parametric test of independent sample was used. Results (1) Genotype frequencies of AGTR1 rs5182 are significant differences between the athletes and control subjects (p = 0.040), the Word-Class athletes and control subjects (p = 0.018), 5km athletes and control subjects (p =0.015), 10km athletes and control subjects (p = 0.026), male athletes and male controls(p=0.045). (2) Association is found between Genotype distribution and MV(L/min) though others not (Genotype: MV; CC: 122.514±6.767; CT:117.187±17.961; TT:119.688±20.226, p=0.047). (3) Transiently transfectedpcDNA3.1-AGTR1-T and pcDNA3.1-AGTR1-C plasmids into 293T cells successfully. The differences of mRNA levels between the groups were not significant (p = 0.991). Conclusions AGTR1 gene rs5182 could be a candidate genetic mark of selection elite endurance athletes in Han Population from Northern China, but this polymorphism does not affect AT1R protein function through changing its mRNA level.

Purpose: Anaerobic speed reserve (ASR), defined as the speed range from velocity associated with maximal oxygen uptake (vVO2max) to maximal sprint speed, has recently been shown to be an important tool for middle-distance coaches to meet event surge demands and inform on the complexity of athlete profiles. To enable field application of ASR, the relationship between gun-to-tape 1500-m average speed (1500v) and the vVO2max for the determination of lower landmark of the ASR was assessed in elite middle-distance runners. Methods: A total of 8 national and 4 international middle-distance runners completed a laboratory-measured vVO2max assessment within 6 wk of a nonchampionship 1500-m gun-to-tape race. ASR was calculated using both laboratory-derived vVO2max (ASR-LAB) and 1500v (ASR-1500v), with maximal sprint speed measured using radar technology. Results: 1500v was on average +2.06 ± 1.03 km/h faster than vVO2max (moderate effect, very likely). ASR-LAB and ASR-1500v mean differences were −2.1 ± 1.5 km/h (large effect, very likely). 1500v showed an extremely large relationship with vVO2max, r = .90 ± .12 (most likely). Using this relationship, a linear-regression vVO2max-estimation equation was derived as vVO2max (km/h) = (1500v [km/h] − 14.921)/0.4266. Conclusions: A moderate difference was evident between 1500v and vVO2max in elite middle-distance runners. The present regression equation should be applied for an accurate field prediction of vVO2max from 1500-m gun-to-tape races. These findings have strong practical implications for coaches lacking access to a sports physiology laboratory who seek to monitor and profile middle-distance runners.

Malone, S, Hughes, B, Collins, K, and Akubat, I. Methods of monitoring training load and their association with changes across fitness measures in hurling players. J Strength Cond Res 34(1): 225-234, 2020-The aim of the current investigation was to assess the dose-response relationship for various methods of monitoring training load (TL) and changes in aerobic and anaerobic fitness in hurling players. Training and match load measures were collected from 30 hurling players (speed at different blood lactate [vLT, vOBLA], maximal oxygen uptake [VO2max], speed at VO2max [vVO2max], peak treadmill velocity [PTV] running economy [RE] Yo-Yo intermittent recovery test (Yo-YoIR1, Yo-YoIR2), speed at 5, 10 , 20 m, and repeated sprint ability [6 × 35 m]) before and after during a 12-week in-season period. Mean weekly training and match loads as determined by s-RPE, bTRIMP, luTRIMP, eTRIMP, iTRIMP, and gTRIMP were correlated with each other, percentage change in VO2max, vVO2max, RE, PTV, the speed at blood lactate concentrations of 2 mmol·L (vLT) and 4 mmol·L (vOBLA), and YoYoIR1, Yo-YoIR2 performance. iTRIMP showed a trivial association with s-RPE and a small to moderate association with other heart rate-based methods. Small to large changes (effect size: 0.38-1.12) were observed in aerobic and anaerobic fitness measures were observed across the 12-week period. Trivial to very large associations (r = 0.11-0.78) were observed between TL variables and changes in fitness depending on the variable analyzed. iTRIMP was shown to have large to very large associations with changes in vOBLA {r = 0.78 (95% confidence interval [CI]: 0.71-0.88)}, VO2max (r = 0.77 [95% CI: 0.68-0.82]), RE (r = 0.77 [95% CI: 0.67-0.82]), Yo-YoIR1 (r = 0.69 [95% CI: 0.51-0.72]), and RSAb (r = 0.66 [95% CI: 0.60-0.72]) with moderate associations reported between iTRIMP and other variables. All other measures of TL showed trivial to moderate associations (r = 0.11-0.66). The current investigation shows that fully individualized training load (iTRIMP) measures may potentially offer a better understanding of dose-response relationships when compared with subjective and nonindividualized measures of TL to changes in aerobic and anaerobic fitness in team sports athletes; as such, it may be suggested that practitioners should use individualized measures of TL assessment within their day-to-day practices.

Made available in DSpace on 2018-11-26T16:04:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-07-09 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Purpose: The aim of the present study was to compare the contributions of the anaerobic pathway as determined by two different methods and energy expenditure during a typical high-intensity intermittent exercise (HIIE) protocol. Methods: A descriptive research design was utilized in which thirteen physically active men performed six experimental sessions consisting of an incremental test (session 1), submaximal tests at 40, 50, 60, 70, 75, 80, 85, 90% of velocity associated with maximum oxygen uptake (v(V) over dotO(2max)) with two intensities per session (sessions 2-5), and the HIIE protocol (session 6; 10 efforts of 1 min at (V) over dotO(2max) interspersed by 1 min of passive recovery). The estimation of anaerobic energy system contribution was calculated by: (a) the excess post-exercise oxygen consumption plus delta lactate method and (b) the accumulated oxygen deficit method using the difference between predicted oxygen demand from the submaximal tests of varying intensities and accumulated oxygen uptake during HIIE. Estimation of aerobic energy system contribution was calculated through the measurement of oxygen consumption during activity. Total EE during the entire HIIE protocol (efforts + recovery) and for the efforts only were calculated from each method. Results: For efforts + recovery and efforts only, anaerobic contribution was similar for both methods, and consequently total EE was also equivalent (p = 0.230 for both comparisons). During efforts + recovery, aerobic:anaerobic energy system contribution was (68 +/- 4%: 32 +/- 4%), while efforts only was (54 +/- 5%: 46 +/- 5%) with both situations demonstrating greater aerobic than anaerobic contribution (p < 0.001 for both). Conclusion: Anaerobic contribution seems to be relevant during HIIE and must to be taken into account during total EE estimation; however, the type of method employed did not change the anaerobic contribution or total EE estimates. Univ Sao Paulo, Sch Phys Educ & Sport, Sao Paulo, Brazil Univ Cent Florida, Sch Kinesiol & Phys Therapy, Orlando, FL 32816 USA Sao Paulo State Univ, Dept Phys Educ, Exercise & Immunometab Res Grp, Sao Paulo, Brazil Sao Paulo State Univ, Sao Paulo, Brazil Australian Inst Sport, Canberra, ACT, Australia Sao Paulo State Univ, Dept Phys Educ, Exercise & Immunometab Res Grp, Sao Paulo, Brazil Sao Paulo State Univ, Sao Paulo, Brazil FAPESP: 2017/07304-6 FAPESP: 2017/08167-2 FAPESP: 2015/11302-3

To provide information for high-intensity interval training (HIIT) load, we compared the temporal variables of VO2 response at, and after, a time sustained at the exercise intensity corresponding to VO2max (Tlim) in different exercise modes. Forty-five trained male swimmers (11), rowers (13), runners (10) and cyclists (11) completed an incremental protocol to determine the velocity (vVO2max) or power (wVO2max) at VO2max and a square wave exercise from rest to 100% of vVO2max/wVO2max. The temporal variables of VO2 response were examined using a breath-by-breath gas analyzer. VO2 responses were not different between exercise modes, except for the percentage of VO2max at 50% of Tlim, which was ~6% higher in rowing compared to cycling (97.70±2.90 vs 92.40±5.69%, p=0.013). During the recovery period, both swimmers and rowers evidenced higher percentages of VO2max compared to cyclists at 30 s (65.1±10.4 and 65.7±5.6 vs 52.7±5.6%) and 60 s (41.7±10.8 and 38.4±5.4 vs 30.4±1.8%) time periods, all for p

BACKGROUND: The purpose of the present research was to analyze the modifications on aerobic swimming performance indicators after performing traditional and reverse training periodizations (TTP and RTP, respectively). METHODS: Seventeen trained swimmers were divided into two groups: one group (N.=7) performed 10 weeks of TTP (based on high volumes and an increased intensity during the program) and the second one (N.=10) was involved in a similar period of RTP (based on low volumes and high intensity during the entire program). Velocity (v), heart rate (HR) and rate of perceived exertion (RPE) at the intensity of 4 mmol/L of blood lactate concentration, v, HR, RPE, stroke rate, stroke length and stroke index at the minimal intensity that elicits maximal oxygen uptake (vVO2max) and maximal oxygen uptake (VO2max) were analyzed pre- and post-training intervention. RESULTS: Stroke index significantly increased (2.9±0.3 vs. 3.1±0.2; P

The objective of this study was to determine the effects of high-intensity warm-ups (WUs) on performance, physiological, neuromuscular and biomechanical parameters. Three randomized cross-over 105%vVO2max time limit trials (TLimT) were performed by 11 well-trained runners following three different WU protocols. These included two experimental high-intensity variants and one control WU variant: (i) 9x20-sec level strides (105%vVO2max; 1% gradient) with 60 s of recovery (level); (ii) 6x6-sec uphill strides (105%vVO2max; 5% gradient), with the same recovery (uphill) and (iii) 7 min at 60%vVO2max as control condition (control). The uphill and level WUs resulted in a greater performance during TLimT (160.0±6.62 s and 152.64±10.88 s, respectively) compared to control WUs (144.82±6.60 s). All WU conditions reduced the energy cost (EC) of running, respiratory exchange ratio, and step frequency (SF) after the experimental and control phases of WU, while blood lactate (BLC) increased in uphill and level WUs and decreased in control WUs. Changes in kinematic variables were found without differences between WU conditions during TLimT. BLC rose at conclusion of TLimT without differences between WU conditions. Both high-intensity WUs show a longer TLimT. EC is deteriorated after the high-intensity WU exercise due to a change of substrate utilization, increase of BLC and SF. A long transient phase (18 min) is necessary to avoid impairing the performance.

[Purpose] It is believed that eccentric high-intensity exercise can decrease performance in subsequent exercise. However, with repetition, the deleterious effects can be minimized. Thus, this study evaluated the influence of repeated bouts of eccentric exercise on subsequent high-intensity aerobic performance. [Subjects and Methods] Seven healthy and sedentary male volunteers were recruited. a) Visit 1: determination of maximum oxygen uptake (VO2max) and speed associated with maximum oxygen uptake (vVO2max) in incremental treadmill testing; b) Visit 2: run to exhaustion at vVO2max (Tlim control); c) Visit 3: 10 sets of 10 depth jumps, followed by a run to exhaustion at vVO2max (Tlim 1); d) Visit 4: after 6 weeks without any physical training, the volunteers carried out the same procedures as on the third visit (Tlim 2). Data were analyzed using one-way analysis of variance (ANOVA) with the post-hoc Tukey test. [Results] Significant differences were found between Tlim control and Tlim 1 (283.4 ± 47.7 s vs. 125.2 ± 64.1 s, respectively), these were not different from Tlim 2. [Conclusion] Eccentric exercise showed deleterious effects on subsequent high-intensity aerobic performance. These effects were minimized after the exercise protocol was repeated 6 weeks after the first event.

Summary Objective The present study aimed to compare maximal aerobic speed (MAS) determined by vVO 2max and peak velocity ( V peak ) as well as their time limits ( t lim ) in middle-aged recreationally-trained runners. The relationships between MAS and t lim with 10- and 15-km running performances were analyzed. Equipment and methods Twenty-one middle-aged recreationally-trained runners with VO 2max of 54.0 ± 7.6 mL·kg −1 ·min −1 took part in the present study. Participants were randomly submitted to two incremental continuous treadmill tests conducted in laboratory environment to determine vVO 2max and V peak . After that, it was performed two tests which aimed to determine t lim at vVO 2max and V peak . Participants also run 10 km and 15 km in a 400 m track. Results Results demonstrated that vVO 2max (15.5 ± 1.7 km·h −1 ) was significantly higher ( P = 0.033) than V peak (15.2 ± 1.4 km·h −1 ). It was also observed statistical differences ( P = 0.023) between t lim at vVO 2max (5.4 ± 2.1 min) and t lim at V peak (6.3 ± 1.4 min). Correlations between V peak and performances were higher than correlations between vVO 2max and the same performances (10-km- r = 0.77 vs 0.65 [ P r = 0.75 vs 0.64 [ P t lim at V peak presented correlation with 10- and 15-km, not observed between t lim at vVO 2max and performances ( V peak - r = −0.44 and −0.45 [ P 2max - r = −0.21 and −0.20 [ P > 0.05]). V peak and its t lim showed to be better predictors of endurance performance of middle-aged recreationally-trained runners.

New Findings What is the central question of this study? Do the mechanical differences between swimming, rowing, running and cycling have a potential effect on the oxygen uptake (VO2) off-kinetics after an exercise sustained until exhaustion at 100% of maximal oxygen uptake (VO2max) intensity? What is the main finding and its importance? The mechanical differences between exercise modes had a potential effect and contributed to distinct amplitude of the fast component (higher in running compared with cycling) and time constant (higher in swimming compared with rowing and cycling) in the VO2 off-kinetic patterns at 100% of VO2max intensity. This suggests that swimmers, unlike rowers and cyclists, would benefit more from a longer duration of training intervals after each set of exercise performed at VO2max intensity. The kinetics of oxygen uptake (VO2) during recovery (off-transient kinetics) for different exercise modes is largely unexplored, hampering the prescription of training and recovery to enhance performance. The purpose of this study was to compare the VO2 off-transient kinetics response between swimmers, rowers, runners and cyclists during their specific mode of exercise at 100% of maximal oxygen uptake (VO2max) intensity and to examine the on–off symmetry. Groups of swimmers, rowers, runners and cyclists (n = 8 per group) performed (i) an incremental exercise protocol to assess the velocity or power associated with VO2max (vVO2max or wVO2max, respectively) and (ii) a square-wave exercise transition from rest to vVO2max/vVO2maxwVO2maxwVO2max until volitional exhaustion. Pulmonary exchange parameters were measured using a telemetric portable gas analyser (K4b2; Cosmed, Rome, Italy), and the on- and off-transient kinetics were analysed through a double-exponential approach. For all exercise modes, both transient periods were symmetrical in shape once they had both been adequately fitted by a double-exponential model. However, differences were found in the off-kinetic parameters between exercise modes; the amplitude of the fast component of the VO2 off-response was higher in running compared with cycling (48 ± 5 and 36 ± 7 ml kg−1 min−1, respectively; P

The purpose of this study was to examine the effects of acute, intermittent exercise performed in hypoxic environments on the release of cardiac troponin (cTn). Ten well-trained, male marathon runners (22.1 ± 2.6 years, 64.0 ± 4.9 kg and 177.3 ± 3.9 cm) completed three intermittent exercise protocols under normoxic (trial N) and hypoxic (trial AH and RH) conditions. In trial N, the fraction of inspiration oxygen (FIO2 ) was 21.0% and exercise intensity was 90% and 50% normoxic velocity of VO2max (vVO2max). In trial AH, FIO2 was 14.4% (simulated altitude of 3000 m) and exercise intensity was 90% and 50% normoxic vVO2max. In trial RH, FIO2 was 14.4% and exercise intensity was 90% and 50% hypoxic vVO2max. High-sensitivity cardiac troponin T (hs-cTnT) and cardiac troponin I (cTnI) were measured pre- and 0, 2, 4, and 24 h post-exercise. Hs-cTnT was elevated in all three trials, peaking at 2 to 4 h and returning to the baseline 24 h post-exercise. CTnI increased in trial AH, peaking at 2 to 4 h and returning below the detection limit 24 h post-exercise. It is concluded that the stimulus of hypoxia did not in and of itself induce more cTn to be released, but exercise intensity could affect this response in hypoxic environments.

Purpose: To compare the efficiency of an aerobic physical training program prescribed according to either velocity associated with maximum oxygen uptake (vVO2max) or peak running speed obtained during an incremental treadmill test (Vpeak_K) in mice. Methods: Twenty male Swiss mice, 60 days old, were randomly divided into two groups with 10 animals each: 1. group trained by vVO2max (GVO2), 2. group trained by Vpeak_K (GVP). After the adaptation training period, an incremental test was performed at the beginning of each week to adjust training load and to determine the amount of VO2 and VCO2 fluxes consumed, energy expenditure (EE) and run distance during the incremental test. Mice were submitted to 4 weeks of aerobic exercise training of moderate intensity (velocity referring to 70% of vVO2max and Vpeak_K) in a programmable treadmill. The sessions lasted from 30 to 40 min in the first week, to reach 60 min in the fourth week, in order to provide the mice with a moderate intensity exercise, totaling 20 training sessions. Results: Mice demonstrated increases in VO2max (ml·kg-1·min-1) (GVO2 = 49.1% and GVP = 56.2%), Vpeak_K (cm·s-1) (GVO2 = 50.9% and GVP = 22.3%), EE (ml·kg-0,75·min-1) (GVO2 = 39.9% and GVP = 51.5%), and run distance (cm) (GVO2 = 43.5% and GVP = 33.4%), after 4 weeks of aerobic training (time effect, P < 0.05); there were no differences between the groups. Conclusions: Vpeak_K, as well as vVO2max, can be adopted as an alternative test to determine the performance and correct prescription of systemized aerobic protocol training to mice.

Purpose: There is a lack of scientific investigation into the predictors of 3 km race performance in collegiate distance runners. The purpose of this investigation was to determine what physiological variables best predict 3 km race time in a group of collegiate distance runners. Methods: Twenty-one endurance trained runners (11 men, 10 women) volunteered for this investigation. Running economy (RE) and maximal oxygen uptake (VO2max) testing were conducted within 9 ± 6 days of the race in a single session. All participants ran in a 3 km race at an NCAA sanctioned track meet. Pearson’s product moment correlations were performed between 3 km race time and velocity at VO2max (vVO2max), relative VO2max, RE at 9.7, 11.3, 12.9, and 14.5 km•hr-1 and percent of VO2max. A stepwise multiple regression was performed with 3 km race time as the dependent variable and independent variables of vVO2max, VO2max, RE9.7, RE11.3, RE12.9, RE14.5. Results: The results revealed that vVO2max was the best predictor of 3 km race performance in a heterogeneous group of collegiate distance runners (R2=0.90). For the men, vVO2max remained the best predictor of 3 km race performance (R2=0.49). For the women, the best predictors of 3 km performance were vVO2max and VO2max (R2=0.97). Conclusions: Distance coaches should consider emphasizing vVO2max as a primary factor in training to improve 3 km race performance and conversely, the pace achieved in a 3-km race is a good predictor of vVO2max.

The multi-stage 20-m shuttle run fitness test (20mMSFT) is a popular field test which is widely used to measure aerobic fitness by predicting maximum oxygen uptake (VO2 max) and performance. However, the velocity at which VO 2 max occurs (vVO 2 max) is a better indicator of performance than VO 2 max, and can be used to explain inter-individual differences in performance that VO 2 max cannot. It has been reported as a better predictor for running performance and it can be used to monitor athletes’ training for predicting optimal training intensity. This study investigated the validity and suitability of predicting VO2max and vVO2max of adult subjects on the basis of the performance of the 20mMST. Forty eight (25 male and 23 female) physical education students performed, in random order, a laboratory based continuous horizontal treadmill test to determine VO2max, vVO 2 max and a 20mMST, with an interval of 3 days between each test. The results revealed significant correlations between the number of shuttles in the 20mMSFT and directly determined VO 2 max (r = 0.87, p