An analysis of the duration of non-local muscle fatigue effects
Bibliographic record
Abstract
Introduction Non-local muscle fatigue (NLMF) is a temporary impairment in the performance of a non-exercised muscle following a fatigue protocol of a different muscle group. Since the tested muscle has not experienced prior activity or fatigue, any impairments due to the fatigue of another muscle cannot be due to peripheral factors and thus must be due to global or central influences. The majority of NLMF post-tests were conducted immediately after the fatiguing protocols. Thus, how long these effects can last is unknown. Purpose There is some uncertainty and conflicting results in literature regarding NLMF effects. The purpose of this study was to examine post-test durations of NLMF in four different time conditions (Control, 1, 3, and 5 min) to investigate the duration of the possible effects. Methods In a randomized crossover study design with only five recreationally trained participants (due to COVID) were recruited for this study (four females: height 159.1 ±2.9 cm, body mass 62.7 ± 7 kg, age 26.6 ± 9.8 yrs. and one male: height 182.2 cm, body mass 90.3 kg, age 40 yrs.) to examine the duration of acute effects of unilateral knee extensors muscle fatigue on the contralateral homologous muscle strength, activation, and fatigue resistance (endurance). Four of the participants were determined to be right-leg dominant, while one participant was left-leg dominant. In five randomized separate sessions (48 hours between visits) each condition was presented which included testing at one, three, five minutes post-test or Control. Non-dominant knee extensors muscle force, and an endurance test as well as vastus lateralis and biceps femoris electromyography III (EMG) data were collected. The fatigue protocol consisted of two sets of continuous 100-seconds MVC by the dominant leg, separated by 1-min of rest. Results The major finding was the lack of significant NLMF-induced single (discrete) MVC force decrements at any post-test duration. Conclusions NLMF was not evident in both single discrete MVC and muscle endurance (fatigue resistance). This finding was in agreement with a recent meta-analysis that reported trivial NLMF effects on single MVCs but contradicts the review’s finding of small to moderate NLMF effects on muscle endurance. The lack of NLMF effects on endurance might be attributed to a lack of statistical power, the recruitment of recreationally active rather than trained individuals, the greater fatigue endurance of female participants or recovery effects within 1-minute of the unilateral fatigue intervention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".