The Effects of Sex and Motoneuron Pool on Central Fatigue
Bibliographic record
Abstract
PURPOSE: It is uncertain if sex influences central fatigue because the reduction in voluntary activation (VA) has been reported as not different between the sexes for elbow flexors (EF) but greater in males compared with females for knee extensors. This disparity could result from the facilitatory and inhibitory effects of group III/IV muscle afferents on flexor versus extensor motoneurons, respectively. The purpose of this study was to examine central fatigue and motoneuron responsiveness of EF and elbow extensors (EE) in males and females. METHODS: Twenty-two participants (11 females) performed a 2-min isometric maximal voluntary contraction of EF and EE (on separate days) followed by 2 min of recovery. EMG potentials were recorded from biceps or triceps brachii in response to the stimulation of the brachial plexus (Mmax), corticospinal tract (cervicomedullary motor evoked potential [CMEP]), and motor cortex (motor evoked potential [MEP]). Superimposed and resting doublets (for determining VA) were evoked via muscle belly stimulation of biceps or triceps brachii. Only CMEP and superimposed doublets were recorded during fatigue. RESULTS: There was no effect of sex on CMEP area for either muscle group during fatigue or recovery. During the 2 min after EE fatigue, mean normalized CMEP and MEP area were ∼85% and ∼141% of control, indicating inhibition and facilitation of the motoneurons and motor cortex, respectively. VA during recovery was significantly reduced in males but not females for the EF, and unchanged in either sex for the EE. CONCLUSION: The findings do not support the concept that equivocal findings regarding sex differences in central fatigue are related to augmented effects of group III/IV afferent feedback in males compared with females.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".