High-Altitude Acclimatization Improves Recovery from Muscle Fatigue
Bibliographic record
Abstract
PURPOSE: We investigated the effect of high-altitude acclimatization on peripheral fatigue compared with sea level and acute hypoxia. METHODS: At sea level (350 m), acute hypoxia (environmental chamber), and chronic hypoxia (5050 m, 5-9 d) (partial pressure of inspired oxygen = 140, 74 and 76 mm Hg, respectively), 12 participants (11 in chronic hypoxia) had the quadriceps of their dominant leg fatigued by three bouts of 75 intermittent electrically evoked contractions (12 pulses at 15 Hz, 1.6 s between train onsets, and 15 s between bouts). The initial peak force was ~30% of maximal voluntary force. Recovery was assessed by single trains at 1, 2, and 3 min postprotocol. Tissue oxygenation of rectus femoris was recorded by near-infrared spectroscopy. RESULTS: At the end of the fatigue protocol, the impairments of peak force and peak rates of force development and relaxation were greater (all P < 0.05) in acute hypoxia (~51%, 53%, and 64%, respectively) than sea level (~43%, 43%, and 52%) and chronic hypoxia (~38%, 35%, and 48%). Peak force and rate of force development recovered faster (P < 0.05) in chronic hypoxia (pooled data for 1-3 min: ~84% and 74% baseline, respectively) compared with sea level (~73% and 63% baseline) and acute hypoxia (~70% and 55% baseline). Tissue oxygenation did not differ among conditions for fatigue or recovery (P > 0.05). CONCLUSIONS: Muscle adaptations occurring with chronic hypoxia, independent of other adaptations, positively influence muscle contractility during and after repeated contractions at high altitude.
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) | 0.002 | 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".