The Sexes Do Not Differ for Neural Responses to Submaximal Elbow Extensor Fatigue
Bibliographic record
Abstract
PURPOSE: To investigate possible sex-related differences in group III/IV muscle afferent feedback with isometric fatigue, we aimed to assess the effect of a sustained submaximal elbow extensor contraction on motoneuronal excitability (cervicomedullary motor evoked potential [CMEP]) and voluntary activation (VA). METHODS: Twenty-four participants (12 females) performed a 15-min contraction at the level of EMG activity recorded at 15% of maximal torque. Each minute, CMEP were elicited by cervicomedullary stimulation with and without conditioning transcranial magnetic stimulation (TMS) delivered 100 ms earlier. Unconditioned and conditioned motor evoked potentials (MEP) in response to TMS were also recorded to assess motor cortical excitability. CMEP and MEP were normalized for changes in downstream excitability and expressed as percentage of their prefatigue (control) values. Postfatigue, VA was calculated from superimposed and resting tetani evoked by stimulation over triceps brachii. RESULTS: Males were twice as strong as females, but the sexes did not differ for any variable during the fatigue protocol. On a 0-10 scale, RPE increased from ~2.5 to 9. The unconditioned CMEP did not change, whereas the conditioned CMEP was reduced by ~50%. By contrast, the unconditioned and conditioned MEP increased to ~200% and ~320% of the control values, respectively. At task termination, maximal torque was reduced ~40%, and VA was ~80%, down from a prefatigue value of ~96%. CONCLUSIONS: Results support the scant published data on the elbow extensors and indicate no sex-related differences for isometric fatigue of this muscle group. The motoneuronal and VA data suggest that metabolite buildup and group III/IV muscle afferent activity were similar for females and males.
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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) | 0.008 | 0.001 |
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".