Blunted muscle angiogenic training-response in COPD patients<i>versus</i>sedentary controls
Bibliographic record
Abstract
The impaired skeletal muscle of chronic obstructive pulmonary disease (COPD) patients reduces exercise capacity. Similar to the oxidative muscle fibres, the angio-adaptation of muscle to training may be blunted in these patients, as in other chronic conditions. We therefore compared muscle functional responses and angio-adaptations after training in COPD patients and sedentary healthy subjects (SHS). 24 COPD patients (forced expiratory volume in 1 s 45.6 ± 17.5% predicted) and 23 SHS (<150 min · week(-1) of moderate-to-vigorous exercise) completed a 6-week rehabilitation programme based on individualised moderate-intensity endurance training. Histomorphological muscle analysis and measurements of pro-angiogenic vascular endothelial growth factor (VEGF)-A and anti-angiogenic thrombospondin (TSP)-1 were conducted before and after training. COPD patients and SHS showed improved symptom-limited oxygen consumption and muscle endurance, although improvements were lower in COPD patients (+0.96 ± 2.4 versus +2.9 ± 2.6 mL · kg(-1) · min(-1), p<0.05, and +65% versus +108%, p = 0.06, respectively). The capillary-to-fibre (C/F) ratio increased less in COPD patients than SHS (+16 ± 10% versus +37 ± 20%, p<0.05) and no fibre type switch occurred in COPD patients. The VEGF-A/TSP-1 ratio increased in COPD patients and SHS (+65% versus +35%, p<0.05). Changes in C/F and symptom-limited oxygen consumption were correlated (r = 0.51, p<0.05). In addition to a lack of fibre switch, COPD patients displayed a blunted angiogenic response to training.
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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 | 0.000 |
| 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".