Immunologic, Anti-Inflammatory, and Anti-Muscle Damage Profile of Supplemented Vitamin D3 in Healthy Adults on Strenuous Endurance Exercise

Reportedly, strenuous endurance exercise can depress the immune system and induce inflammation and muscle damage. Therefore, this double-blinded, matched-pair study aimed to investigate the impact of vitamin D₃ supplementation on immune response (leukocyte, neutrophil, lymphocyte, CD4⁺, CD8⁺, CD19⁺, and CD56⁺ counts), inflammatory profile (TNF-α and IL-6), muscle damage (CK and LDH levels), as well as aerobic capacity after strenuous endurance exercise in 18 healthy men taking 5000 IU of vitamin D₃ (n = 9) or placebo (n = 9) daily for 4 weeks. Total and differential blood leukocyte counts, levels of cytokines, and muscle damage biomarkers were determined before, immediately after, and 2, 4, and 24 h after exercise. The IL-6, CK, and LDH levels were significantly lower in vitamin D₃ group at 2, 4, and 24 h post exercise (p < 0.05). Maximal and average heart rates during exercise were also significantly lower (p < 0.05). In the vitamin D₃ group, the CD4⁺/CD8⁺ ratio after 4 weeks of supplementation was only significantly lower at post-0 than at baseline and significantly higher at post-2 than at baseline and post-0 (all p < 0.05). Taken together, 5000 IU of daily vitamin D₃ supplementation for 4 weeks exhibited positive effects in terms of increased blood 25(OH)D levels, CD4⁺/CD8⁺ ratio (immune response), and aerobic capacity while inhibiting inflammatory cytokines and CK and LDH (muscle damage) in people performing strenuous endurance exercise.

Evaluation of High-Intensity Interval Training and Beta-Alanine Supplementation on Efficiency of Electrical Activity and Electromyographic Fatigue Threshold

ABSTRACT

Herda, AA, Smith-Ryan, AE, Kendall, KL, Cramer, JT, and Stout, JR. Evaluation of high-intensity interval training and beta-alanine supplementation on efficiency of electrical activity and electromyographic fatigue threshold. J Strength Cond Res 35(6): 1535-1541, 2021-The purpose of this study was to determine the effects of high-intensity interval training (HIIT) with or without β-alanine (BA) supplementation on the electromyographic fatigue threshold (EMGFT) and efficiency of electrical activity (EEA) in young women. Forty-four women (mean ± SD; age [yrs]: 21.7 ± 3.7; height [cm]: 166.3 ± 6.4; body mass [kg]: 66.1 ± 10.3) were randomly assigned to one of 3 treatment groups. The supplement groups performed HIIT on the cycle ergometer 3 times·wk-1 for 6 weeks. Electromyographic fatigue threshold and EEA were assessed at baseline (PRE), after 3 weeks of training (MID), and after 6 weeks of HIIT (POST). Two 2-way mixed factorial analyses of variance (time [PRE vs. MID vs. POST] × treatment (BA vs. PL vs. CON)] were used to analyze EMGFT and EEA with a predetermined level of significance α of 0.05. For EMGFT, there was no interaction (p = 0.26) and no main effect for time (p = 0.28) nor treatment (p = 0.86); thus, there were no changes in EMGFT regardless of training or supplementation status. For EEA, there was no interaction (p = 0.70) nor treatment (p = 0.79); however, there was a main effect for time (p < 0.01). Our findings indicated that neither training nor supplementation was effective in improving EMGFT in women. Efficiency of electrical activity was altered, potentially because of a learning effect. Coaches and practitioners may not use these tests to monitor training status; however, they may find EEA as a useful tool to track cycling efficiency.

Evaluation of the Electromyography Test for the Analysis of the Aerobic-Anaerobic Transition in Elite Cyclists during Incremental Exercise

(1) Background: The aim of this study was to investigate the validity and reliability of surface electromyography (EMG) for automatic detection of the aerobic and anaerobic thresholds during an incremental continuous cycling test using 1 min exercise periods in elite cyclists. (2) Methods: Sixteen well-trained cyclists completed an incremental exercise test (25 W/1 min) to exhaustion. Surface bipolar EMG signals were recorded from the vastus lateralis, vastus medialis, biceps femoris, and gluteus maximus, and the root mean square (RMS) were assessed. The multi-segment linear regression method was used to calculate the first and second EMG thresholds (EMGT1 and EMGT2). During the test, gas exchange data were collected to determine the first and second ventilatory thresholds (VT1 and VT2). (3) Results: Two breakpoints (thresholds) were identified in the RMS EMG vs. time curve for all muscles in 75% of participants. The two breakpoints, EMGT1 and EMGT2, were detected at around 70%–80% and 90%–95% of VO2MAX, respectively. No significant differences were found between the means of VT1 and EMGT1 for the vastii and biceps femoris muscles (p > 0.05). There were no significant differences between means of EMGT2 and VT2 (p > 0.05). (4) Conclusions: It is concluded that the multi-segment linear regression algorithm is a valid non-invasive method for analyzing the aerobic-anaerobic transition during incremental tests with 1 min stage durations.

Detecting fatigue thresholds from electromyographic signals: A systematic review on approaches and methodologies

The aim of the current paper was to systematically review the relevant existing electromyographic threshold concepts within the literature. The electronic databases MEDLINE and SCOPUS were screened for papers published between January 1980 and April 2015 including the keywords: neuromuscular fatigue threshold, anaerobic threshold, electromyographic threshold, muscular fatigue, aerobic-anaerobictransition, ventilatory threshold, exercise testing, and cycle-ergometer. 32 articles were assessed with regard to their electromyographic methodologies, description of results, statistical analysis and test protocols. Only one article was of very good quality. 21 were of good quality and two articles were of very low quality. The review process revealed that: (i) there is consistent evidence of one or two non-linear increases of EMG that might reflect the additional recruitment of motor units (MU) or different fiber types during fatiguing cycle ergometer exercise, (ii) most studies reported no statistically significant difference between electromyographic and metabolic thresholds, (iii) one minute protocols with increments between 10 and 25W appear most appropriate to detect muscular threshold, (iv) threshold detection from the vastus medialis, vastus lateralis, and rectus femoris is recommended, and (v) there is a great variety in study protocols, measurement techniques, and data processing. Therefore, we recommend further research and standardization in the detection of EMGTs.