Post‐fatigue ability to activate muscle is compromised across a wide range of torques during acute hypoxic exposure
Bibliographic record
Abstract
Abstract The purpose of this study was to assess how severe acute hypoxia alters the neural mechanisms of muscle activation across a wide range of torque output in a fatigued muscle. Torque and electromyography responses to transcranial and motor nerve stimulation were collected from 10 participants (27 years ± 5 years, 1 female ) following repeated performance of a sustained maximal voluntary contraction that reduced torque to 60% of the pre‐fatigue peak torque. Contractions were performed after 2 h of hypoxic exposure and during a sham intervention. For hypoxia, peripheral blood oxygen saturation was titrated to 80% over a 15‐min period and remained at 80% for 2 h. Maximal voluntary torque, electromyography root mean square, voluntary activation and corticospinal excitability (motor evoked potential area) and inhibition (silent period duration) were then assessed at 100%, 90%, 80%, 70%, 50% and 25% of the target force corresponding to the fatigued maximal voluntary contraction. No hypoxia‐related effects were identified for voluntary activation elicited during motor nerve stimulation. However, during measurements elicited at the level of the motor cortex, voluntary activation was reduced at each torque output considered ( P = .002, η p 2 = .829). Hypoxia did not impact the correlative linear relationship between cortical voluntary activation and contraction intensity or the correlative curvilinear relationship between motor nerve voluntary activation and contraction intensity. No other hypoxia‐related effects were identified for other neuromuscular variables. Acute severe hypoxia significantly impairs the ability of the motor cortex to voluntarily activate fatigued muscle across a wide range of torque output.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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 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".