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Athletes use hypoxic living and training to increase hemoglobin mass (Hb mass ), but Hb mass declines rapidly upon return to sea level. We investigated whether intermittent hypoxic exposure (IHE) + continuous hypoxic training (CHT) after return to sea level maintained elevated Hb mass , and if changes in Hb mass were transferred to changes in maximal oxygen uptake (V̇o 2max ) and exercise performance. Hb mass was measured in 58 endurance athletes before (PRE), after (POST1), and 30 days after (POST2) a 27 ± 4-day training camp in hypoxia ( n = 44, HYP) or at sea level ( n = 14, SL). After returning to sea level, 22 athletes included IHE (2 h rest) + CHT (1 h training) in their training every third day for 1 mo (HYP IHE + CHT ), whereas the other 22 HYP athletes were not exposed to IHE or CHT (HYP SL ). Hb mass increased from PRE to POST1 in both HYP IHE + CHT (4.4 ± 0.7%, means ± SE) and HYP SL (4.1 ± 0.6%) (both P < 0.001). Compared with PRE, Hb mass at POST2 remained 4.2 ± 0.8% higher in HYP IHE + CHT ( P < 0.001) and 1.9 ± 0.5% higher in HYP SL ( P = 0.023), indicating a significant difference between the groups ( P = 0.002). In SL, no significant changes were observed in Hb mass with mean alterations between -0.5% and 0.4%. V̇o 2max and time to exhaustion during an incremental treadmill test ( n = 35) were elevated from PRE to POST2 only in HYP IHE + CHT (5.8 ± 1.2% and 5.4 ± 1.4%, respectively, both P < 0.001). IHE + CHT possesses the potential to mitigate the typical decline in Hb mass commonly observed during the initial weeks after return to sea level. NEW & NOTEWORTHY Sets of 2-h intermittent hypoxic exposure + 1-h continuous hypoxic training, every third day, possess the potential to mitigate the typical decline in Hb mass that is commonly observed during the initial weeks after return to sea level from an altitude camp. Inclusion of IHE + CHT in the training regimen was also accompanied by improvements in V̇o 2max and exercise performance in most but not all Tier 3-Tier 5 level endurance athletes during the training season.

Purpose: Very low intensity endurance training (LIT) does not seem to improve maximal oxygen uptake. The purpose of the present study was to investigate if very high volume of LIT could compensate the lack of intensity and is LIT affecting differently low and high intensity performances., Methods: Recreationally active untrained participants (n = 35; 21 females) cycled either LIT (mean training time 6.7 ± 0.7 h / week at 63% of maximal heart rate, n = 16) or high intensity training (HIT) (1.6 ± 0.2 h /week, n = 19) for 10 weeks. Two categories of variables were measured: Low (first lactate threshold, fat oxidation at low intensity exercise, post-exercise recovery) and high (aerobic capacity, second lactate threshold, sprinting power, maximal stroke volume) intensity performance., Results: Only LIT enhanced pooled low intensity performance (LIT: p = 0.01, ES = 0.49, HIT: p = 0.20, ES = 0.20) and HIT pooled high intensity performance (LIT: p = 0.34, ES = 0.05, HIT: p = 0.007, ES = 0.48)., Conclusions: Overall, very low endurance training intensity cannot fully be compensated by high training volume in adaptations to high intensity performance, but it nevertheless improved low intensity performance. Therefore, the intensity threshold for improving low intensity performance is lower than that for improving high intensity performance. Consequently, evaluating the effectiveness of LIT on endurance performance cannot be solely determined by high intensity performance tests., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Matomäki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: Without appropriate standardization of exercise doses, comparing high- (HI) and low-intensity (LI) training outcomes might become a matter of speculation. In athletic preparation, proper quantification ensures an optimized stress-to-recovery ratio. This review aims to compare HI and LI doses by estimating theoretically the conversion ratio, 1:x, between HI and LI: How many minutes, x, of LI are equivalent to 1 minute of HI using various quantification methods? A scrutinized analysis on how the dose increases in relation to duration and intensity was also made., Analysis: An estimation was conducted across 4 categories encompassing 10 different approaches: (1) "arbitrary" methods, (2) physiological and perceptual measurements during exercise, (3) postexercise measurements, and comparison to (4a) acute and (4b) chronic intensity-related maximum dose. The first 2 categories provide the most conservative estimation for the HI:LI ratio (1:1.5-1:10), and the third, slightly higher (1:4-1:11). The category (4a) provides the highest estimation (1:52+) and (4b) suggests 1:10 to 1:20. The exercise dose in the majority of the approaches increase linearly in relation to duration and exponentially in relation to intensity., Conclusions: As dose estimations provide divergent evaluations of the HI:LI ratio, the choice of metric will have a large impact on the research designs, results, and interpretations. Therefore, researchers should familiarize themselves with the foundations and weaknesses of their metrics and justify their choice. Last, the linear relationship between duration and exercise dose is in many cases assumed rather than thoroughly tested, and its use should be subjected to closer scrutiny.

Monitoring performance-related characteristics of athletes can reveal changes that facilitate training adaptations. Here, we examine the relationships between submaximal running, maximal jump performance (CMJ), concentrations of blood lactate, sleep duration (SD) and latency (SL), and perceived stress (PSS) in junior cross-country skiers during pre-season training. These parameters were monitored in 15 male and 14 females (17 ± 1 years) for the 12-weeks prior to the competition season, and the data was analysed using linear and mixed-effect models. An increase in SD exerted a decrease in both PSS (B = -2.79, p  ≤ 0.01) and blood lactate concentrations during submaximal running (B = -0.623, p  ≤ 0.05). In addition, there was a negative relationship between SL and CMJ (B = -0.09, p  = 0.08). Compared to males, females exhibited higher PSS scores and little or no change in performance-related tests. A significant interaction between time and sex was present in CMJ with males displaying an effect of time on CMJ performance. For all athletes, lower PSS appeared to be associated with longer overnight sleep. Since the females experienced higher levels of stress, monitoring of their PSS might be beneficial. These findings have implications for the preparation of young athletes' competition season.

Purpose: To investigate whether 4 weeks of normobaric "live high-train low and high" (LHTLH) causes different hematological, cardiorespiratory, and sea-level performance changes compared to living and training in normoxia during a preparation season., Methods: Nineteen (13 women, 6 men) cross-country skiers competing at the national or international level completed a 28-day period (∼18 h day -1 ) of LHTLH in normobaric hypoxia of ∼2400 m (LHTLH group) including two 1 h low-intensity training sessions per week in normobaric hypoxia of 2500 m while continuing their normal training program in normoxia. Hemoglobin mass (Hb mass ) was assessed using a carbon monoxide rebreathing method. Time to exhaustion (TTE) and maximal oxygen uptake (VO 2max ) were measured using an incremental treadmill test. Measurements were completed at baseline and within 3 days after LHTLH. The control group skiers (CON) (seven women, eight men) performed the same tests while living and training in normoxia with ∼4 weeks between the tests., Results: Hb mass in LHTLH increased 4.2 ± 1.7% from 772 ± 213 g (11.7 ± 1.4 g kg -1 ) to 805 ± 226 g (12.5 ± 1.6 g kg -1 ) (p < 0.001) while it was unchanged in CON (p = 0.21). TTE improved during the study regardless of the group (3.3 ± 3.4% in LHTLH; 4.3 ± 4.8% in CON, p < 0.001). VO 2max did not increase in LHTLH (61.2 ± 8.7 mL kg -1  min -1 vs. 62.1 ± 7.6 mL kg -1  min -1 , p = 0.36) while a significant increase was detected in CON (61.3 ± 8.0-64.0 ± 8.1 mL kg -1  min -1 , p < 0.001)., Conclusions: Four-week normobaric LHTLH was beneficial for increasing Hb mass but did not support the short-term development of maximal endurance performance and VO 2max when compared to the athletes who lived and trained in normoxia., (© 2023 The Authors. Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd.)

This study examined the predictive quality of intervals performed at maximal sustainable effort to predict 3-km and 10-km running times. In addition, changes in interval performance and associated changes in running performance were investigated. Either 6-week (10-km group, n=29) or 2-week (3-km group, n=16) interval training periods were performed by recreational runners. A linear model was created for both groups based on the running speed of the first 6×3-min interval session and the test run of the preceding week (T1). The accuracy of the model was tested with the running speed of the last interval session and the test run after the training period (T2). Pearson correlation was used to analyze relationships between changes in running speeds during the tests and interval sessions. At T2, the mean absolute percentage error of estimate for 3-km and 10-km test times were 2.3% and 3.4%, respectively. The change in running speed of intervals and test runs from T1 to T2 correlated (r=0.75, p<0.001) in both datasets. Thus, the maximal sustainable effort intervals were able to predict 3-km and 10-km running performance and training adaptations with good accuracy, and current results demonstrate the potential usefulness of intervals as part of the monitoring process., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Introduction: This is one of the first intervention studies to examine how low- (LIT) and high-intensity endurance training (HIT) affect durability, defined as 'time of onset and magnitude of deterioration in physiological-profiling characteristics over time during prolonged exercise'. Methods: Sedentary and recreationally active men (n = 16) and women (n = 19) completed either LIT (average weekly training time 6.8 ± 0.7 h) or HIT (1.6 ± 0.2 h) cycling for 10 weeks. Durability was analyzed before and after the training period from three factors during 3-h cycling at 48% of pretraining maximal oxygen uptake (VO 2max ): 1) by the magnitude and 2) onset of drifts (i.e. gradual change in energy expenditure, heart rate, rate of perceived exertion, ventilation, left ventricular ejection time, and stroke volume), 3) by the 'physiological strain', defined to be the absolute responses of heart rate and its variability, lactate, and rate of perceived exertion. Results: When all three factors were averaged the durability was improved similarly (time x group p = 0.42) in both groups (LIT: p = 0.03, g = 0.49; HIT: p = 0.01, g = 0.62). In the LIT group, magnitude of average of drifts and their onset did not reach statistically significance level of p < 0.05 (magnitude: 7.7 ± 6.8% vs. 6.3 ± 6.0%, p = 0.09, g = 0.27; onset: 106 ± 57 min vs. 131 ± 59 min, p = 0.08, g = 0.58), while averaged physiological strain improved ( p = 0.01, g = 0.60). In HIT, both magnitude and onset decreased (magnitude: 8.8 ± 7.9% vs. 5.4 ± 6.7%, p = 0.03, g = 0.49; onset: 108 ± 54 min vs. 137 ± 57 min, p = 0.03, g = 0.61), and physiological strain improved ( p = 0.005, g = 0.78). VO 2max increased only after HIT (time x group p < 0.001, g = 1.51). Conclusion: Durability improved similarly by both LIT and HIT based on reduced physiological drifts, their postponed onsets, and changes in physiological strain. Despite durability enhanced among untrained people, a 10-week intervention did not alter drifts and their onsets in a large amount, even though it attenuated physiological strain., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Matomäki, Heinonen, Nummela, Laukkanen, Auvinen, Pirkola and Kyröläinen.)

Purpose: Long-term development of endurance performance requires a proper balance between strain and recovery. Because responses and adaptations to training are highly individual, this study examined whether individually adjusted endurance training based on recovery and training status would lead to greater adaptations compared with a predefined program., Methods: Recreational runners were divided into predefined (PD; n = 14) or individualized (IND; n = 16) training groups. In IND, the training load was decreased, maintained, or increased twice a week based on nocturnal heart rate variability, perceived recovery, and heart rate-running speed index. Both groups performed 3-wk preparatory, 6-wk volume, and 6-wk interval periods. Incremental treadmill tests and 10-km running tests were performed before the preparatory period ( T0 ) and after the preparatory ( T1 ), volume ( T2 ), and interval ( T3 ) periods. The magnitude of training adaptations was defined based on the coefficient of variation between T0 and T1 tests (high >2×, low <0.5×)., Results: Both groups improved ( P < 0.01) their maximal treadmill speed and 10-km time from T1 to T3 . The change in the 10-km time was greater in IND compared with PD (-6.2% ± 2.8% vs -2.9% ± 2.4%, P = 0.002). In addition, IND had more high responders (50% vs 29%) and fewer low responders (0% vs 21%) compared with PD in the change of maximal treadmill speed and 10-km performance (81% vs 23% and 13% vs 23%), respectively., Conclusions: PD and IND induced positive training adaptations, but the individualized training seemed more beneficial in endurance performance. Moreover, IND increased the likelihood of high response and decreased the occurrence of low response to endurance training., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine.)

Purpose: To assess the reliability of nocturnal heart rate (HR) and HR variability (HRV) and to analyze the sensitivity of these markers to maximal endurance exercise., Methods: Recreational runners recorded nocturnal HR and HRV on nights after 2 identical low-intensity training sessions (n = 15) and on nights before and after a 3000-m running test (n = 23). Average HR, the natural logarithm of the root mean square of successive differences (LnRMSSD), and the natural logarithm of the high-frequency power (LnHF) were analyzed from a full night (FULL), a 4-hour (4H) segment starting 30 minutes after going to sleep, and morning value (MOR) based on the endpoint of the linear fit through all 5-minute averages during the night. Differences between the nights were analyzed with a general linear model, and intraclass correlation coefficient (ICC) was used for internight reliability assessments., Results: All indices were similar between the nights followed by low-intensity training sessions. A very high ICC (P < .001) was observed in all analysis segments with a range of .97 to .98 for HR, .92 to .97 for LnRMSSD, and .91 to .96 for LnHF. HR increased (P < .001), whereas LnRMSSD (P < .01) and LnHF (P < .05) decreased after the 3000-m test compared with previous night only in 4H and FULL. Increments in HR (P < .01) and decrements in LnRMSSD (P < .05) were greater in 4H compared with FULL and MOR., Conclusions: Nocturnal HR and HRV indices are highly reliable. Demanding maximal exercise increases HR and decreases HRV most systematically in 4H and FULL segments.

Purpose: This study examined the physiological, perceptual, and performance responses to a 2-wk block of increased training load and compared whether responses differ between high-intensity interval (HIIT) and low-intensity training (LIT)., Methods: Thirty recreationally trained males and females performed a 2-wk block of 10 HIIT sessions (INT, n = 15) or 70% increased volume of LIT (VOL, n = 15). Running time in the 3000 m and basal serum and urine hormone concentrations were measured before (T1) and after the block (T2), and after a recovery week (T3). In addition, weekly averages of nocturnal heart rate variability (HRV) and perceived recovery were compared with the baseline., Results: Both groups improved their running time in the 3000 m from T1 to T2 (INT = -1.8% ± 1.6%, P = 0.003; VOL = -1.4% ± 1.7%, P = 0.017) and from T1 to T3 (INT = -2.5% ± 1.6%, P < 0.001; VOL = -2.2% ± 1.9%, P = 0.001). Resting norepinephrine concentration increased in INT from T1 to T2 (P = 0.01) and remained elevated at T3 (P = 0.018). The change in HRV from the baseline was different between the groups during the first week (INT = -1.0% ± 2.0% vs VOL = 1.8% ± 3.2%, P = 0.008). Muscle soreness increased only in INT (P < 0.001), and the change was different compared with VOL across the block and recovery weeks (P < 0.05)., Conclusions: HIIT and LIT blocks increased endurance performance in a short period. Although both protocols seemed to be tolerable for recreational athletes, a HIIT block may induce some negative responses such as increased muscle soreness and decreased parasympathetic activity., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine.)

Purpose: The purpose of this study was to compare heart rate (HR) and heart rate variability in young endurance athletes during nocturnal sleep and in the morning; and to assess whether changes in these values are associated with changes in submaximal running (SRT) and counter-movement jump (CMJ) performance., Methods: During a three-week period of similar training, eleven athletes (16 ± 1 years) determined daily HR and heart rate variability (RMSSD) during sleep utilizing a ballistocardiographic device (Emfit QS), as well as in the morning with a HR monitor (Polar V800). Aerobic fitness and power production were assessed employing SRT and CMJ test., Results: Comparison of the average values for week 1 and week 3 revealed no significant differences with respect to nocturnal RMSSD (6.8%, P = 0.344), morning RMSSD (13.4%, P = 0.151), morning HR (-3.9 bpm, P = 0.063), SRT HR (-0.7 bpm, P = 0.447), SRT blood lactate (4.9%, P = 0.781), CMJ (-4.2%, P = 0.122) or training volume (16%, P = 0.499). There was a strong correlation between morning and nocturnal HRs during week 1 (r = 0.800, P = 0.003) and week 3 (r = 0.815, P = 0.002), as well as between morning and nocturnal RMSSD values (for week 1, r = 0.895, P<0.001 and week 3, r = 0.878, P = 0.001)., Conclusion: This study concluded that HR and RMSSD obtained during nocturnal sleep and in the morning did not differ significantly. In addition, weekly changes in training and performance were small indicating that fitness was similar throughout the 3-week period of observation. Consequently, daily measurement of HR indices during nocturnal sleep provide a potential tool for long-term monitoring of young endurance athletes., Competing Interests: The authors have declared that no competing interests exist.

The aims of the current study were to examine the relationships between heart rate variability (HRV), salivary cortisol, sleep duration and training in young athletes. Eight athletes (16 ± 1 years) were monitored for 7 weeks during training and competition seasons. Subjects were training for endurance-based winter sports (cross-country skiing and biathlon). Training was divided into two zones (K1, easy training and K2, hard training). Heart rate and blood lactate during submaximal running tests (SRT), as well as cortisol, sleep duration and nocturnal HRV (RMSSD), were determined every other week. HRV and cortisol levels were correlated throughout the 7-week period (r = -0.552, P = 0.01), with the strongest correlation during week 7 (r = -0.879, P = 0.01). The relative changes in K1 and HRV showed a positive correlation from weeks 1-3 (r = 0.863, P = 0.006) and a negative correlation during weeks 3-5 (r = -0.760, P = 0.029). The relative change in sleep during weeks 1-3 were negatively correlated with cortisol (r = -0.762, P = 0.028) and K2 (r = -0.762, P = 0.028). In conclusion, HRV appears to reflect the recovery of young athletes during high loads of physical and/or physiological stress. Cortisol levels also reflected this recovery, but significant change required a longer period than HRV, suggesting that cortisol may be less sensitive to stress than HRV. Moreover, our results indicated that during the competition season, recovery for young endurance athletes increased in duration and additional sleep may be beneficial., (© Journal of Sports Science and Medicine.)

This study investigated acute responses and post 24-h recovery to four running sessions performed at different intensity zones by supine heart rate variability, countermovement jump, and a submaximal running test. A total of 24 recreationally endurance-trained male subjects performed 90 min low-intensity (LIT), 30 min moderate-intensity (MOD), 6×3 min high-intensity interval (HIIT) and 10×30 s supramaximal-intensity interval (SMIT) exercises on a treadmill. Heart rate variability decreased acutely after all sessions, and the decrease was greater after MOD compared to LIT and SMIT (p<0.001; p<0.01) and HIIT compared to LIT (p<0.01). Countermovement jump decreased only after LIT (p<0.01) and SMIT (p<0.001), and the relative changes were different compared to MOD (p<0.01) and HIIT (p<0.001). Countermovement jump remained decreased at 24 h after SMIT (p<0.05). Heart rate during the submaximal running test rebounded below the baseline 24 h after all sessions (p<0.05), while the rating of perceived exertion during the running test remained elevated after HIIT (p<0.05) and SMIT (p<0.01). The current results highlight differences in the physiological demands of the running sessions, and distinct recovery patterns of the measured aspects of performance. Based on these results, assessments of performance and recovery from multiple perspectives may provide valuable information for endurance athletes, and help to improve the quality of training monitoring., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

The purpose of the study was to examine the effects of progressively increased training intensity or volume on the nocturnal heart rate (HR) and heart rate variability (HRV), countermovement jump, perceived recovery, and heart rate-running speed index (HR-RS index). Another aim was to analyze how observed patterns during the training period in these monitoring variables were associated with the changes in endurance performance. Thirty recreationally trained participants performed a 10-week control period of regular training and a 10-week training period of either increased training intensity (INT, n = 13) or volume (VOL, n = 17). Changes in endurance performance were assessed by an incremental treadmill test. Both groups improved their maximal speed on the treadmill (INT 3.4 ± 3.2%, p < 0.001; VOL 2.1 ± 1.8%, p = 0.006). In the monitoring variables, only between-group difference ( p = 0.013) was found in nocturnal HR, which decreased in INT ( p = 0.016). In addition, perceived recovery decreased in VOL ( p = 0.021) and tended to decrease in INT ( p = 0.056). When all participants were divided into low-responders and responders in maximal running performance, the increase in the HR-RS index at the end of the training period was greater in responders ( p = 0.005). In conclusion, current training periods of increased intensity or volume improved endurance performance to a similar extent. Countermovement jump and HRV remained unaffected, despite a slight decrease in perceived recovery. Long-term monitoring of the HR-RS index may help to predict positive adaptations, while interpretation of other recovery-related markers may need a more individualized approach.

Abstract: Myllyaho, MM, Ihalainen, JK, Hackney, AC, Valtonen, M, Nummela, A, Vaara, E, Häkkinen, K, Kyröläinen, H, and Taipale, RS. Hormonal contraceptive use does not affect strength, endurance, or body composition adaptations to combined strength and endurance training in women. J Strength Cond Res 35(2): 449-457, 2021-This study examined the effects of a 10-week period of high-intensity combined strength and endurance training on strength, endurance, body composition, and serum hormone concentrations in physically active women using hormonal contraceptives (HCs, n = 9) compared with those who had never used hormonal contraceptives (NHCs, n = 9). Training consisted of 2 strength training sessions and 2 high-intensity running interval sessions per week. Maximal bilateral isometric leg press (Isom), maximal bilateral dynamic leg press (one repetition maximum [1RM]), countermovement jump (CMJ), a 3,000-m running test (3,000 m), body composition, and serum hormone levels were measured before and after training between days 1-5 of each subject's menstrual cycle. Both groups increased 1RM and CMJ: HC = 13.2% (p < 0.001) and 9.6% (p < 0.05), and NHC = 8.3% (p < 0.01) and 8.5% (p < 0.001). Hormonal contraceptive improved 3,000 m by 3.5% (p < 0.05) and NHC by 1% (n.s.). Never used hormonal contraceptive increased lean mass by 2.1% (p < 0.001), whereas body fat percentage decreased from 23.9 ± 6.7 to 22.4 ± 6.0 (-6.0%, p < 0.05). No significant changes were observed in body composition in HC. No significant between-group differences were observed in any of the performance variables. Luteinizing hormone concentrations decreased significantly (p < 0.05) over 10 weeks in NHC, whereas other hormone levels remained statistically unaltered in both groups. It seems that the present training is equally appropriate for improving strength, endurance, and body composition in women using HC as those not using HC without disrupting hypothalamic-pituitary-gonadal axis function., (Copyright © 2018 National Strength and Conditioning Association.)

The present study investigated whether athletes can be classified as responders or non-responders based on their individual change in total hemoglobin mass (tHb-mass) following altitude training while also identifying the potential factors that may affect responsiveness to altitude exposure. Measurements were completed with 59 elite endurance athletes who participated in national team altitude training camps. Fifteen athletes participated in the altitude training camp at least twice. Total Hb-mass using a CO rebreathing method and other blood markers were measured before and after a total of 82 altitude training camps (1350-2500 m) in 59 athletes. In 46 (56%) altitude training camps, tHb-mass increased. The amount of positive responses increased to 65% when only camps above 2000 m were considered. From the fifteen athletes who participated in altitude training camps at least twice, 27% always had positive tHb-mass responses, 13% only negative responses, and 60% both positive and negative responses. Logistic regression analysis showed that altitude was the most significant factor explaining positive tHb-mass response. Furthermore, male athletes had greater tHb-mass response than female athletes. In endurance athletes, tHb-mass is likely to increase after altitude training given that hypoxic stimulus is appropriate. However, great inter- and intra-individual variability in tHb-mass response does not support classification of an athlete permanently as a responder or non-responder. This variability warrants efforts to control numerous factors affecting an athlete's response to each altitude training camp., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Vesterinen, V, Nummela, A, Laine, T, Hynynen, E, Mikkola, J, and Häkkinen, K. A submaximal running test with postexercise cardiac autonomic and neuromuscular function in monitoring endurance training adaptation. J Strength Cond Res 31(1): 233-243, 2017-The aim of this study was to investigate whether a submaximal running test (SRT) with postexercise heart rate recovery (HRR), heart rate variability (HRV), and countermovement jump (CMJ) measurements could be used to monitor endurance training adaptation. Thirty-five endurance-trained men and women completed an 18-week endurance training. Maximal endurance performance and maximal oxygen uptake were measured every 8 weeks. In addition, SRTs with postexercise HRR, HRV, and CMJ measurements were carried out every 4 weeks. Submaximal running test consisted of two 6-minute stages at 70 and 80% of maximum heart rate (HRmax) and a 3-minute stage at 90% HRmax, followed by a 2-minute recovery stage for measuring postexercise HRR, HRV, and CMJ test. The highest responders according to the change of maximal endurance performance showed a significant improvement in running speeds during stages 2 and 3 in SRT, whereas no changes were observed in the lowest responders. The strongest correlation was found between the change of maximal endurance performance and running speed during stage 3, whereas no significant relationships were found between the change of maximal endurance performance and the changes of postexercise HRR, HRV, and CMJ. Running speed at 90% HRmax intensity was the most sensitive variable to monitor adaptation to endurance training. The present submaximal test showed potential to monitor endurance training adaptation. Furthermore, it may serve as a practical tool for athletes and coaches to evaluate weekly the effectiveness of training program without interfering in the normal training habits.

Introduction: Measures of HR variability (HRV) have shown potential to be of use in training prescription., Purpose: The aim of this study was to investigate the effectiveness of using HRV in endurance training prescription., Methods: Forty recreational endurance runners were divided into the HRV-guided experimental training group (EXP) and traditional predefined training group (TRAD). After a 4-wk preparation training period, TRAD trained according to a predefined training program including two to three moderate- (MOD) and high-intensity training (HIT) sessions per week during an 8-wk intensive training period. The timing of MOD and HIT sessions in EXP was based on HRV, measured every morning. The MOD/HIT session was programmed if HRV was within an individually determined smallest worthwhile change. Otherwise, low-intensity training was performed. Maximal oxygen consumption (V˙O2max) and 3000-m running performance (RS3000m) were measured before and after both training periods., Results: The number of MOD and HIT sessions was significantly lower (P = 0.021, effect size = 0.98) in EXP (13.2 ± 6.0 sessions) compared with TRAD (17.7 ± 2.5 sessions). No other differences in training were found between the groups. RS3000m improved in EXP (2.1% ± 2.0%, P = 0.004) but not in TRAD (1.1% ± 2.7%, P = 0.118) during the intensive training period. A small between-group difference (effect size = 0.42) was found in the change in RS3000m. V˙O2max improved in both groups (EXP: 3.7% ± 4.6%, P = 0.027; TRAD: 5.0% ± 5.2%, P = 0.002)., Conclusion: The results of the present study suggest the potential of resting HRV to prescribe endurance training by individualizing the timing of vigorous training sessions.

Unlabelled: Regular monitoring of adaptation to training is important for optimizing training load and recovery, which is the main factor in successful training., Purpose: To investigate the usefulness of a novel submaximal running test (SRT) in field conditions in predicting and tracking changes of endurance performance., Methods: Thirty-five endurance-trained men and women (age 20-55 y) completed the 18-wk endurance-training program. A maximal incremental running test was performed at weeks 0, 9, and 18 for determination of maximal oxygen consumption (VO2max) and running speed (RS) at exhaustion (RSpeak) and lactate thresholds (LTs). In addition, the subjects performed weekly a 3-stage SRT including a postexercise heart-rate-recovery (HRR) measurement. The subjects were retrospectively grouped into 4 clusters according to changes in SRT results., Results: Large correlations (r = .60-.89) were observed between RS during all stages of SRT and all endurance-performance variables (VO2max, RSpeak, RS at LT2, and RS at LT1). HRR correlated only with VO2max (r = .46). Large relationships were also found between changes in RS during 80% and 90% HRmax stages of SRT and a change of RSpeak (r = .57, r = .79). In addition, the cluster analysis revealed the different trends in RS during 80% and 90% stages during the training between the clusters, which showed different improvements in VO2max and RSpeak., Conclusions: The current SRT showed great potential as a practical tool for regular monitoring of individual adaptation to endurance training without time-consuming and expensive laboratory tests.

Purpose: To examine acute responses of force production and oxygen uptake to combined strength (S) and endurance-running (E) loading sessions in which the order of exercises is reversed (ES vs SE)., Methods: This crossover study design included recreationally endurance-trained men and women (age 21-45 y; n=12 men, 10 women) who performed ES and SE loadings. Force production of the lower extremities including countermovement-jump height (CMJ) and maximal isometric strength (MVC) was measured pre-, mid-, and post-ES and -SE, and ground-reaction forces, ground-reaction times, and running economy were measured during E., Results: A significant decrease in CMJ was observed after combined ES and SE in men (4.5%±7.0% and 6.6%±7.7%, respectively) but not in women (0.2%±8.5% and 1.4%±7.3% in ES and SE). MVC decreased significantly in both men (20.7%±6.1% ES and 19.3%±9.4% SE) and women (12.4%±9.3% ES and 11.6%±12.0% SE). Stride length decreased significantly in ES and SE men, but not in women. No changes were observed in ground-reaction times during running in men or women. Performing S before E caused greater (P<.01) oxygen uptake during running in both men and women than if E was performed before S, although heart rate and blood lactate were similar between ES and SE., Conclusions: Performing S before E increased oxygen uptake during E, which is explained, in part, by a decrease in MVC in both men and women, decreased CMJ and stride length in men, and/or an increase in postexercise oxygen consumption.

The aim of this study was to investigate whether a novel heart rate (HR)-running speed index could be used in monitoring adaptation to endurance training. Forty-five recreational runners underwent a 2-phased 28-week training regime. The first 14 weeks included basic endurance training, whereas the second 14 weeks were more intensive (increased volume and intensity). A maximal treadmill running test was performed in the beginning of the experiment, in the middle of basic endurance training, and at the end of each training period (PRE, WEEK 7, WEEK 14, and POST). The novel HR-running speed index was calculated from every continuous-type running exercise during the 28-week experiment based on exercise HR-running speed relation accompanied by individual information on resting and maximal HR and speed. The change in the novel index correlated significantly with the changes of peak running speed in the treadmill tests (r = 0.43-0.61, p < 0.01) and speed at respiratory compensation threshold (r = 0.35-0.39, p ≤ 0.05) during the experiment. The change in the index also correlated significantly (r = 0.49, p = 0.001) with relative changes in maximal oxygen uptake (in ml·kg·min). According to these findings, it seems that the novel index based on exercise HR and running speed may serve as a practical tool for daily monitoring of individual's training adaptation without the need to realize a maximal running test in laboratory conditions.

Supervised periodized mixed maximal and explosive strength training added to endurance training in recreational endurance runners was examined during an 8-week intervention preceded by an 8-week preparatory strength training period. Thirty-four subjects (21-45 years) were divided into experimental groups: men (M, n = 9), women (W, n = 9), and control groups: men (MC, n = 7), women (WC, n = 9). The experimental groups performed mixed maximal and explosive exercises, whereas control subjects performed circuit training with body weight. Endurance training included running at an intensity below lactate threshold. Strength, power, endurance performance characteristics, and hormones were monitored throughout the study. Significance was set at p ≤ 0.05. Increases were observed in both experimental groups that were more systematic than in the control groups in explosive strength (12 and 13% in men and women, respectively), muscle activation, maximal strength (6 and 13%), and peak running speed (14.9 ± 1.2 to 15.6 ± 1.2 and 12.9 ± 0.9 to 13.5 ± 0.8 km Ł h). The control groups showed significant improvements in maximal and explosive strength, but Speak increased only in MC. Submaximal running characteristics (blood lactate and heart rate) improved in all groups. Serum hormones fluctuated significantly in men (testosterone) and in women (thyroid stimulating hormone) but returned to baseline by the end of the study. Mixed strength training combined with endurance training may be more effective than circuit training in recreational endurance runners to benefit overall fitness that may be important for other adaptive processes and larger training loads associated with, e.g., marathon training.

The study examined the acute neuromuscular and metabolic responses and recovery (24 and 48 h) to combined strength and endurance sessions (SEs). Recreationally endurance trained men (n = 12) and women (n = 10) performed: endurance running followed immediately by a strength loading (combined endurance and strength session (ES)) and the reverse order (SE). Maximal strength (MVC), countermovement jump height (CMJ), and creatine kinase activity were measured pre-, mid-, post-loading and at 24 and 48 h of recovery. MVC and CMJ were decreased (P < 0.05) at post-ES and SE sessions in men. Only MVC decreased in ES and SE women (P < 0.05). During recovery, no order differences in MVC were observed between sessions in men, but MVC and CMJ remained decreased. During recovery in women, a delayed decrease in CMJ was observed in ES but not in SE (P < 0.01), while MVC returned to baseline at 24 h. Creatine kinase increased (P < 0.05) during both ES and SE and peaked in all groups at 24 h. The present combined ES and SE sessions induced greater neuromuscular fatigue at post in men than in women. The delayed fatigue response in ES women may be an order effect related to muscle damage.

In this study, changes in skiing performance and poling kinetics during a simulated cross-country sprint skiing competition were investigated. Twelve elite male cross-country skiers performed simulated sprint competition (4 x 1,150 m heat with 20 min recovery between the heats) using the double-poling technique. Vertical and horizontal pole forces and cycle characteristics were measured using a force plate system (20-m long) during the starting spurt, racing speed, and finishing spurt of each heat. Moreover, heat and 20-m phase velocities were determined. Vertical and horizontal pole impulses as well as mean cycle length were calculated. The velocities of heats decreased by 2.7 +/- 1.7% (p = 0.003) over the simulated competition. The 20-m spurting velocity decreased by 16 +/- 5% (p < 0.002) and poling time increased by 18 +/- 9% (p < 0.003) in spurt phases within heats. Vertical and horizontal poling impulses did not change significantly during the simulation; however, the mean forces decreased (p < 0.039) (vertical by 24 +/- 11% and horizontal by 20 +/- 10%) within heats but not between the heats. Decreased heat velocities over the simulated sprint and spurting velocities within heats indicated fatigue among the skiers. Fatigue was also manifested by decreased pole force production and increased poling time.

Overload principle of training states that training load (TL) must be sufficient to threaten the homeostasis of cells, tissues, organs and/or body. However, there is no "golden standard" for TL measurement. The aim of the present study was to investigate if post-exercise heart rate variability (HRV) could be used to evaluate TL of interval running exercises with different intensities and durations. Thirteen endurance-trained men (35 ± 5 years) performed MO(250) [moderate intensity, 2 × 6 × 250 m/rec 30 s/5 min at 85% of the maximal velocity of the graded maximal test (V (max))], MO(500) (2 × 3 × 500 m/rec 1 min/5 min at 85% V (max)) and HI(250) (high intensity, 2 × 6 × 250 m/rec 30 s/5 min at 105% V (max)) interval exercises on a treadmill. HRV was analyzed during rest, exercise and immediate 15 min recovery. Fast recovery of LFP (P < 0.001), HFP (P < 0.01) and TP (P < 0.01) occurred during the first two recovery minutes after each exercise. Strong negative correlations (P < 0.01) were found between post-exercise HRV and perceived exertion as well as excess post-exercise oxygen consumption. Post-exercise HRV differentiated interval exercises of equal work, but varying intensity or distance of running bout. The results of the present study suggest that immediate post-exercise HRV may offer objective information on TL of interval exercises with different bout durations and intensities.

The purpose of this study was to assess the effects of heavy resistance, explosive resistance, and muscle endurance training on neuromuscular, endurance, and high-intensity running performance in recreational endurance runners. Twenty-seven male runners were divided into one of three groups: heavy resistance, explosive resistance or muscle endurance training. After 6 weeks of preparatory training, the groups underwent an 8-week resistance training programme as a supplement to endurance training. Before and after the 8-week training period, maximal strength (one-repetition maximum), electromyographic activity of the leg extensors, countermovement jump height, maximal speed in the maximal anaerobic running test, maximal endurance performance, maximal oxygen uptake ([V·]O(₂max)), and running economy were assessed. Maximal strength improved in the heavy (P = 0.034, effect size ES = 0.38) and explosive resistance training groups (P = 0.003, ES = 0.67) with increases in leg muscle activation (heavy: P = 0.032, ES = 0.38; explosive: P = 0.002, ES = 0.77). Only the heavy resistance training group improved maximal running speed in the maximal anaerobic running test (P = 0.012, ES = 0.52) and jump height (P = 0.006, ES = 0.59). Maximal endurance running performance was improved in all groups (heavy: P = 0.005, ES = 0.56; explosive: P = 0.034, ES = 0.39; muscle endurance: P = 0.001, ES = 0.94), with small though not statistically significant improvements in [V·]O(₂max) (heavy: ES = 0.08; explosive: ES = 0.29; muscle endurance: ES = 0.65) and running economy (ES in all groups < 0.08). All three modes of strength training used concurrently with endurance training were effective in improving treadmill running endurance performance. However, both heavy and explosive strength training were beneficial in improving neuromuscular characteristics, and heavy resistance training in particular contributed to improvements in high-intensity running characteristics. Thus, endurance runners should include heavy resistance training in their training programmes to enhance endurance performance, such as improving sprinting ability at the end of a race.

Heart rate (HR) as an estimator of oxygen consumption (VO(2) ) usually requires HR to be individually calibrated in a separate test. This study examined the validity of a new HR - and HR variability-based method (Firstbeat PRO heartbeat analysis software) in the estimation of VO(2) in real-life tasks. The method takes into account the respiration rate determined from HR variability and the differences in the on/off dynamics of HR and VO(2) , and no calibration tests are needed. Ten men and nine women performed 25 tasks representing different types of daily activities. Portable devices were used to measure R-to-R intervals (ECG), VO(2) and respiration rate. In pooled regression analysis, the estimated VO(2) accounted for 87% of the variability in the actual VO(2) , SEE 3·5 ml min(-1) kg(-1) (1 MET). At group level, the method underestimated slightly the measured VO(2) (mean difference - 1·5 ml min(-1) kg(-1) or - 0·4 METs). Some of the values at low exercise intensities were markedly underestimated, but the agreement was better during light and heavy activities. The limits of agreement for the data were from -8·4 to 5·4 ml min(-1) kg(-1) or from -2·4 to 1·5 METs. At individual level, the average deviations of the predicted VO(2) ranged from -1·0 to 0·6 METs and R(2) from 0·77 to 0·94, respectively. The present data indicate that the prediction method may be considered sufficiently accurate to determine the average VO(2) in field use, but it does not allow precise estimation of VO(2) ., (© 2011 The Authors. Clinical Physiology and Functional Imaging © 2011 Scandinavian Society of Clinical Physiology and Nuclear Medicine.)

The present study investigated the performance-predicting factors of a simulated cross-country (XC) skiing sprint competition on roller skis, on a slow surface. Sixteen elite male XC skiers performed a simulated sprint competition (4 x 850 m heat with a 20-minute recovery) using V2 skating technique on an indoor tartan track. Heat velocities, oxygen consumption, and peak lactate were measured during or after the heats. Maximal skiing velocity was measured by performing a 30-m speed test. Explosive and maximal force production in the upper body was determined by bench press (BP). Subjects also performed maximal anaerobic skiing test (MAST) and the 2 x 2-km double poling (DP) test. The maximal velocity of MAST (VMAST) and velocities at 3 (V3), 5 (V5), 7 (V7) mmol.L lactate levels in MAST were determined. In the 2 x 2-km test, DP economy (VO2SUBDP) and maximal 2-km DP velocity (VDP2KM) were determined. The best single performance-predicting factors for the sprint performance were VDP2KM (r = 0.73, p < 0.01), V7 (r = 0.70, p < 0.01), and VO2SUBDP (r = -0.70, p < 0.01). Faster skiers in sprint simulation had a higher absolute VO2 (L.min) (p < 0.05-0.01) during sprint heats, and higher anaerobic skiing power (VMAST, p < 0.05) and better anaerobic skiing economy (V3, V5, V7, p < 0.05-0.001) than slower skiers. Faster skiers were also stronger in BP, with regard to both absolute (p < 0.01) and relative (p < 0.05) values. In addition, anaerobic characteristics seem to be of importance at the beginning of the XC skiing sprint competition, whereas the aerobic characteristics become more important as the XC skiing sprint competition progressed. This study indicates that sprint skiers should emphasize sport-specific upper body training, and training skiing economy at high speeds.

The overload principle of training states that training load (TL) must be sufficient to threaten the homeostasis of cells, tissues, organs, and/or body. However, there is no "golden standard" for TL measurement. The aim of this study was to examine if any post-exercise heart rate variability (HRV) indices could be used to evaluate TL in exercises with different intensities and durations. Thirteen endurance-trained males (35 +/- 5 year) performed MODE (moderate intensity, 3 km at 60% of the maximal velocity of the graded maximal test (vVO(2max))), HI (high intensity, 3 km at 85% vVO(2max)), and PRO (prolonged, 14 km at 60% vVO(2max)) exercises on a treadmill. HRV was analyzed with short-time Fourier-transform method during rest, exercise, and 15-min recovery. Rating of perceived exertion (RPE), blood lactate (BLa), and HFP(120) (mean of 0-120 s post-exercise) described TL of these exercises similarly, being different for HI (P < 0.05) and PRO (P < 0.05) when compared with MODE. RPE and BLa also correlated negatively with HFP(120) (r = -0.604, -0.401), LFP(120) (-0.634, -0.601), and TP(120) (-0.691, -0.569). HRV recovery dynamics were similar after each exercise, but the level of HRV was lower after HI than MODE. Increased intensity or duration of exercise decreased immediate HRV recovery, suggesting that post-exercise HRV may enable an objective evaluation of TL in field conditions. The first 2-min recovery seems to give enough information on HRV recovery for evaluating TL.

The aim of this study was to assess fatigue during a simulated cross-country skiing sprint competition based on skating technique. Sixteen male skiers performed a 30-m maximal skiing speed test and four 850-m heats with roller skies on a tartan track, separated by 20 min recovery between heats. Physiological variables (heart rate, blood lactate concentration, oxygen consumption), skiing velocity, and electromyography (EMG) were recorded at the beginning of the heats and at the end of each 200-m lap during the heats. Maximal skiing velocity and EMG were measured in the speed test before the simulation. No differences were observed in skiing velocity, EMG or metabolic variables between the heats. The end (820-850 m) velocities and sum-iEMG of the triceps brachii and vastus lateralis in the four heats were significantly lower than the skiing velocity and sum-iEMG in the speed test. A significant correlation was observed between mean oxygen consumption and the change in skiing velocity over the four heats. Each single heat induced considerable neuromuscular fatigue, but recovery between the heats was long enough to prevent accumulation of fatigue. The results suggest that the skiers with a high aerobic power were less fatigued throughout the simulation.

Since heart rate variability (HRV) during the first minutes of the recovery after exercise has barely been studied, we wanted to find out HRV dynamics immediately after five different constant-speed exercises. Thirteen sedentary women performed two low-intensity (3,500 m [3,500(LI)] and 7,000 m [7,000(LI)] at 50% of the velocity of VO(2max) [vVO(2max)]), two moderate-intensity (3,500 m [3,500(MI)] and 7,000 m [7,000(MI)] at approximately 63% vVO(2max)) and one high-intensity (3,500 m at approximately 74% vVO(2max) [3,500(HI)]) exercises on a treadmill. HRV was analyzed with short-time Fourier transform method during the 30-min recovery. High frequency power (HFP) was for the first time higher than at the end of the exercise after the first minute of the recovery (3,500(LI) and 7,000(LI), P < 0.001), after the fourth (3,500(MI), P < 0.05) and the fifth (7,000(MI), P < 0.05) minute of the recovery and at the end of the 30-min recovery (3,500(HI), P < 0.01). There were no differences in HRV between 3,500(LI) and 7,000(LI) or between 3,500(MI) and 7,000(MI) during the recovery. The levels of HFP and TP were higher during the whole recovery after 3,500(LI) compared to 3,500(MI) and 3,500(HI). We found increased HFP, presumably caused by vagal reactivation, during the first 5 min of the recovery after each exercise, except for 3,500(HI). The increased intensity of the exercise resulted in slower recovery of HFP as well as lower levels of HFP and TP when compared to low-intensity exercise. Instead, the doubled running distance had no influence on HRV recovery.

The purpose of this experiment was to examine the effects of concurrent endurance and explosive strength training on electromyography (EMG) and force production of leg extensors, sport-specific rapid force production, aerobic capacity, and work economy in cross-country skiers. Nineteen male cross-country skiers were assigned to an experimental group (E, n = 8) or a control group (C, n = 11). The E group trained for 8 weeks with the same total training volume as C, but 27% of endurance training in E was replaced by explosive strength training. The skiers were measured at pre- and post training for concentric and isometric force-time parameters of leg extensors and EMG activity from the vastus lateralis (VL) and medialis (VM) muscles. Sport-specific rapid force production was measured by performing a 30-m double poling test with the maximal velocity (V(30DP)) and sport-specific endurance economy by constant velocity 2-km double poling test (CVDP) and performance (V(2K)) by 2-km maximal double poling test with roller skis on an indoor track. Maximal oxygen uptake (Vo(2)max) was determined during the maximal treadmill walking test with the poles. The early absolute forces (0-100 ms) in the force-time curve in isometric action increased in E by 18 +/- 22% (p < 0.05), with concomitant increases in the average integrated EMG (IEMG) (0-100 ms) of VL by 21 +/- 21% (p < 0.05). These individual changes in the average IEMG of VL correlated with the changes in early force (r = 0.86, p < 0.01) in E. V(30DP) increased in E (1.4 +/- 1.6%) (p < 0.05) but not in C. The V(2K) increased in C by 2.9 +/- 2.8% (p < 0.01) but not significantly in E (5.5 +/- 5.8%, p < 0.1). However, the steady-state oxygen consumption in CVDP decreased in E by 7 +/- 6% (p < 0.05). No significant changes occurred in Vo(2)max either in E or in C. The present concurrent explosive strength and endurance training in endurance athletes produced improvements in explosive force associated with increased rapid activation of trained leg muscles. The training also led to more economical sport-specific performance. The improvements in neuromuscular characteristics and economy were obtained without a decrease in maximal aerobic capacity, although endurance training was reduced by about 20%.

To develop a track version of the maximal anaerobic running test, 10 sprint runners and 12 distance runners performed the test on a treadmill and on a track. The treadmill test consisted of incremental 20-s runs with a 100-s recovery between the runs. On the track, 20-s runs were replaced by 150-m runs. To determine the blood lactate versus running velocity curve, fingertip blood samples were taken for analysis of blood lactate concentration at rest and after each run. For both the treadmill and track protocols, maximal running velocity (v max), the velocities associated with blood lactate concentrations of 10 mmol x l-1 (v10 mM) and 5 mmol x l(-1) (v5 mM), and the peak blood lactate concentration were determined. The results of both protocols were compared with the seasonal best 400-m runs for the sprint runners and seasonal best 1000-m time-trials for the distance runners. Maximal running velocity was significantly higher on the track (7.57 +/- 0.79 m x s(-1)) than on the treadmill (7.13 +/- 0.75 m x s(-1)), and sprint runners had significantly higher vmax, v10 mM, and peak blood lactate concentration than distance runners (P < 0.05). The Pearson product--moment correlation coefficients between the variables for the track and treadmill protocols were 0.96 (v max), 0.82 (v10 mM), 0.70 (v5 mM), and 0.78 (peak blood lactate concentration) (P < 0.05). In sprint runners, the velocity of the seasonal best 400-m run correlated positively with vmax in the treadmill (r = 0.90, P < 0.001) and track protocols (r = 0.92, P < 0.001). In distance runners, a positive correlation was observed between the velocity of the 1000-m time-trial and vmax in the treadmill (r = 0.70, P < 0.01) and track protocols (r = 0.63, P < 0.05). It is apparent that the results from the track protocol are related to, and in agreement with, the results of the treadmill protocol. In conclusion, the track version of the maximal anaerobic running test is a valid means of measuring different determinants of sprint running performance.

This study investigated the effects of the neuromuscular and force-velocity characteristics in distance running performance and running economy. Eighteen well-trained male distance runners performed five different tests: 20 m maximal sprint, running economy at the velocity of 4.28 m s(-1), 5 km time trial, maximal anaerobic running test (MART), and a treadmill test to determine VO2max. The AEMG ratio was calculated by the sum average EMG (AEMG) of the five lower extremity muscles during the 5 km divided by the sum AEMG of the same muscles during the maximal 20 m sprinting. The runners' capacity to produce power above VO2max (MART VO2gain) was calculated by subtracting VO2max from the oxygen demand of the maximal velocity in the MART (V MART). Velocity of 5 km (V 5K) correlated with V MART (r=0.77, p<0.001) and VO2max (r=0.49, p<0.05). Multiple linear regression analysis showed that MART VO2gain and VO2max explained 73% of the variation in V 5K. A significant relationship also existed between running economy and MART VO2gain (r=0.73, p<0.01). A significant correlation existed between V 5K and AEMG ratio during the ground contact phase at the 3 km (r=0.60, p<0.05) suggesting that neural input may affect distance running performance. The results of the present study support the idea that distance running performance and running economy are related to neuromuscular capacity to produce force and that the V MART can be used as a determinant of distance-running performance.

The purpose of this study was to examine power-type athletes to determine changes in amino acid and hormone concentrations in circulating blood following 2 different high-intensity exercise sessions before and after the 5-week training period. Eleven competitive male sprinters and jumpers performed 2 different running exercise sessions: a short run session (SRS) of 3 x 4 x 60 m (intensity of 91-95%) with recoveries of 120 and 360 seconds, and a long run session (LRS) with 20-second intervals (intensity of 56-100%) with recoveries of 100 seconds to exhaustion. The concentrations of serum amino acids, hormones, and lactate were determined from the blood samples drawn after an overnight fast and 10 minutes before and after both SRS and LRS. The average blood lactate concentrations were 12.7 +/- 1.6 mmol;pdL(-1) and 16.6 +/- 1.4 mmol;pdL(-1) (p < 0.01) following SRS and LRS, respectively. The average total running time was longer (p < 0.001) following LRS (164 +/- 20 seconds) than following SRS (91 +/- 8 seconds). The fasting levels of all amino acids decreased (p = 0.024; 19.4%) after the 5-week period, whereas an increase (p = 0.007; 24.5%) was observed in the fasting concentration of testosterone (TE). The exercise sessions induced no changes in the total sum of all amino acids, but significant increases or decreases were observed in single amino acids. When the range of the relative concentration changes before and after the training period was compared, significant decreases were found in valine (p = 0.048), asparagine (p = 0.029), and taurine (p = 0.030) following SRS. There were significant increases in the absolute hormonal concentration changes following LRS with TE (p = 0.002; 30.4%), cortisol (COR; p = 0.006; 12.0%), and in the TE/COR ratio (p = 0.047; 21.0%) but not in the concentration of growth hormone (GH). The results of the study indicate that the speed and strength training period strongly decreases the fasting concentrations of amino acids in the power-trained athletes in a good anabolic state with the daily protein intake of 1.26 g;pdkg(-1) body weight. At the same time the intensive lactic exercise session induces strong decreases, especially in valine, asparagine, and taurine.