The Influence of Pedaling Frequency on Blood Lactate Accumulation in Cycling Sprints.

Anaerobic performance diagnostics in athletes relies on accurate measurements of blood lactate concentration and the calculation of blood lactate accumulation resulting from glycolytic processes. In this study, we investigated the impact of pedaling frequency on blood lactate accumulation during 10-second maximal isokinetic cycling sprints. Thirteen trained males completed five 10-second maximal isokinetic cycling sprints on a bicycle ergometer at different pedaling frequencies (90 rpm, 110 rpm, 130 rpm, 150 rpm, 170 rpm) with continuous power and frequency measurement. Capillary blood samples were taken pre-exercise and up to 30 minutes post-exercise to determine the maximum blood lactate concentration.Blood lactate accumulation was calculated as the difference between maximal post-exercise and pre-start blood lactate concentration. Repeated measurement ANOVA with Bonferroni-adjusted post hoc t-tests revealed significant progressive increases in maximal blood lactate concentration and accumulation with higher pedaling frequencies (p<0.001; η2+>+0.782).The findings demonstrate a significant influence of pedaling frequency on lactate accumulation, emphasizing its relevance in anaerobic diagnostics. Optimal assessment of maximal lactate formation rate is suggested to require a pedaling frequency of at least 130 rpm or higher, while determining metabolic thresholds using the maximal lactate formation rate may benefit from a slightly lower pedaling frequency.

Variability of time series barbell kinematics in elite male weightlifters.

Introduction: Barbell kinematics are an essential aspect of assessing weightlifting performance. This study aimed at analyzing the total variability of time series barbell kinematics during repeated lifts in the snatch and the clean and jerk at submaximal and maximal barbell loads. Methods: In a test-retest design, seven male weightlifters lifted submaximal [85% planned one-repetition maximum (1RMp)] and maximal (97% 1RMp) loads in the snatch and the clean and jerk during training. Barbell trajectory, vertical velocity, and vertical acceleration were determined using video analysis. Standard error of measurement (SEM), intraclass correlation coefficient (ICC), and smallest real difference (SRD) were used to determine the total variability during the lifts. Hedge's g effect size was used to assess differences in SEM between submaximal and maximal loads. Results: The main findings indicated that variability-in particular for the barbell velocity-was lower at maximal compared to submaximal barbell loads (g = 0.52-2.93). SEM of time series data showed that variability increased in the snatch and the clean and jerk from the 1st pull/dip to the catch position irrespectively of the barbell load. Discussion: This study presents values of total variability of time series barbell kinematics during the snatch, the clean, and the jerk. Further, the SRD can be used to evaluate changes in barbell kinematics in response to training. In addition, when interpreting barbell kinematics, coaches should take into account that the variability of barbell kinematics can vary depending on the exercise and the barbell load.

The effectiveness of blood-flow restricted resistance training in the musculoskeletal rehabilitation of patients with lower limb disorders: A systematic review and meta-analysis.

OBJECTIVE: This meta-analysis aimed to evaluate the effectiveness of low-load Resistance Training (RT) with or without Blood Flow Restriction (BFR) compared with conventional RT on muscle strength in open and closed kinetic chains, muscle volume and pain in individuals with orthopaedic impairments. DATA SOURCES: Searches were conducted in the PubMed, Web of Science, Scopus and Cochrane databases, including the reference lists of randomised controlled trials (RCT's) up to January 2021. Review method: An independent reviewer extracted study characteristics, orthopaedic indications, exercise data and outcome measures. The primary outcome was muscle strength of the lower limb. Secondary outcomes were muscle volume and pain. Study quality and reporting was assessed using the TESTEX scale. RESULTS: A total of 10 RCTs with 386 subjects (39.2 ± 17.1 years) were included in the analysis to compare low-load RT with BFR and high or low-load RT without BFR. The meta-analysis showed no significant superior effects of low-load resistance training with BFR regarding leg muscle strength in open and closed kinetic chains, muscle volume or pain compared with high or low-load RT without BFR in subjects with lower limb impairments. CONCLUSION: Low-load RT with BFR leads to changes in muscle strength, muscle volume and pain in musculoskeletal rehabilitation that are comparable to conventional RT. This appears to be independent of strength testing in open or closed kinetic chains.

Adaption of Maximal Glycolysis Rate after Resistance Exercise with Different Volume Load.

The aim of this study was to investigate the effect of six-weeks of resistance training with different volume load on the maximum glycolysis rate. 24 male strength-trained volunteers were assigned in a high volume low load (50% of their 1RM with 5 sets and reps up to muscle failure) and a low volume high load (70% of their 1RM with 5 sets of ten reps) resistance exercise group. The resistance training performed 3 days per week over 6 weeks. The maximum glycolysis rate was determined using isokinetic force testing before and after the intervention. There was a significant increase in glycolysis rate over the training period across all subjects (p=0.032). High volume low load exercise increased significantly from 0.271±0.067 mmol·l -1 ·s -1 to 0.298±0.067 mmol·l -1 ·s -1 (p=0.022) and low volume high load exercise showed no significant changes from 0.249±0.122 mmol·l -1 ·s -1 to 0.291±0.089 mmol·l -1 ·s -1 (p=0.233). No significant effect on glycolysis rate was observed between the training groups (p=0.650). Resistance training increases glycolysis rate regardless of volume load.

Reproducibility of Blood Lactate Concentration Rate under Isokinetic Force Loads.

(1) Background: Maximum isokinetic force loads show strongly increased post-load lactate concentrations and an increase in the maximum blood lactate concentration rate ( V ˙ Lamax), depending on load duration. The reproducibility of V ˙ Lamax must be known to be able to better assess training-related adjustments of anaerobic performance using isokinetic force tests. (2) Methods: 32 subjects were assigned to two groups and completed two unilateral isokinetic force tests (210° s-1, Range of Motion 90°) within seven days. Group 1 (n = 16; age 24.0 ± 2.8 years, BMI 23.5 ± 2.6 kg m-2, training duration: 4.5 ± 2.4 h week-1) completed eight repetitions and group 2 (n = 16; age 23.7 ± 1.9 years, BMI 24.6 ± 2.4 kg m-2, training duration: 5.5 ± 2.1 h week-1) completed 16 repetitions. To determine V ˙ Lamax, capillary blood (20 µL) was taken before and immediately after loading, and up to the 9th minute post-load. Reproducibility and variability was determined using Pearson and Spearman correlation analyses, and variability were determined using within-subject standard deviation (Sw) and Limits of Agreement (LoA) using Bland Altman plots. (3) Results: The correlation of V ˙ Lamax in group 1 was r = 0.721, and in group 2 r = 0.677. The Sw of V ˙ Lamax was 0.04 mmol L-1 s-1 in both groups. In group 1, V ˙ Lamax showed a systematic bias due to measurement repetition of 0.02 mmol L-1 s-1 in an interval (LoA) of ±0.11 mmol L-1 s-1. In group 2, a systematic bias of -0.008 mmol L-1 s-1 at an interval (LoA) of ±0.11 mmol L-1 s-1 was observed for repeated measurements of V ˙ Lamax. (4) Conclusions: Based on the existing variability, a reliable calculation of V ˙ Lamax seems to be possible with both short and longer isokinetic force loads. Changes in V ˙ Lamax above 0.11 mmol L-1 s-1 due to training can be described as a non-random increase or decrease in V ˙ Lamax.

The influence of body composition on exercise-associated skin temperature changes after resistance training.

Resistance exercise leads to an increase in skin temperature (Tskin) in the area of the exercised muscle. Infrared thermography seems to be applicable to identify these primary used functional muscles with measuring Tskin changes. The aim of the current study was to investigate the influence of body composition on Tskin patterns after resistance exercise. 38 male subjects (19-32 years, BMI 20.4-55.2 kg/m2) participated. Body fat percentage and biceps skinfold thickness were calculated. The subjects were divided into two groups: lean group (LG) with body fat percentage < 25%, obese group (OG) with body fat percentage ≥ 25%. All participants completed three sets with ten repetitions of unilateral biceps curl at 50% of the one repetition maximum. To represent exercise-induced changes of Tskin to rest (Trest), the algebraic difference of each time point to Trest was calculated. The resulting delta values (∆) are as follows: immediately after the first, second, and third set (∆Tset1,∆Tset2,∆Tset3), and at 1,2,3,4,5,6,7,8,9,10,15,20,25,30 min after the third set (∆T1-∆T30). The maximum positive difference to Trest was defined as ∆Tmax, and the time to reach ∆Tmax was defined as Time to ∆Tmax. LG and OG differed significantly at Trest (32.8 ±â€¯0.9 vs. 31.1 ±â€¯1.4 °C), ∆Tmax (1.9 ±â€¯0.4 vs. 0.9 ±â€¯0.8 °C), Time to ∆Tmax (4.5 ±â€¯2.0 vs. 17.6 ±â€¯10.2 min) and at ∆Tset2 to ∆T15 (p < 0.005). Correlations between body composition (BMI, body fat percentage, biceps skinfold thickness) and Trest, ∆Tset2, ∆Tset3, ∆Tmax (-0.47