Can increases in capillarization explain the early adaptations in metabolic regulation in human muscle to short-term training?
Bibliographic record
Abstract
To investigate the hypothesis that increases in fibre capillary density would precede increases in oxidative potential following training onset, tissue was extracted from the vastus lateralis prior to (0 days) and following 3 and 6 consecutive days of submaximal cycle exercise (2 h·day(-1)). Participants were untrained males (age = 21.4 ± 0.58 years; peak oxygen consumption = 46.2 ± 1.6 mL·kg(-1)·min(-1); mean ± standard error (SE)). Tissue was assessed for succinic dehydrogenase activity (SDH) by microphotometry and indices of capillarization based on histochemically assessed area and capillary counts (CC) in specific fibre types. Three days of training (n = 13) resulted in a generalized decrease (p < 0.05) in fibre area (-14.2% ± 3.0%; mean ± SE) and increase (p < 0.05) in CC/Area (20.4% ± 2.7%) and no change in either CC or SDH activity. Following 6 days of treatment (n = 6), increases (p < 0.05) in CC (18.2% ± 4.2%), CC/Area (28.9% ± 3.2%), and SDH activity (22.9% ± 6.0%) occurred that was not specific to major fibre type. No changes in either fibre area or fibre-type distribution were observed with additional training. We conclude that increases in angiogenic-based capillary density and oxidative potential occur coincidentally following training onset, while increases in capillary density, mediated by reductions in fibre area, represent an initial isolated response, the significance of which may be linked to the metabolic alterations that also result.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".