Resistance Training Increases Skeletal Muscle Capillarization in Healthy Older Men
Bibliographic record
Abstract
PURPOSE: Skeletal muscle capillarization plays a key role in oxygen and nutrient delivery to muscle. The loss of muscle mass with aging and the concept of anabolic resistance have been, at least partly, attributed to changes in skeletal muscle capillary structure and function. We aimed to compare skeletal muscle capillarization between young and older men and evaluate whether resistance-type exercise training increases muscle capillarization in older men. METHODS: Muscle biopsies were obtained from the vastus lateralis of healthy young (n = 14, 26 ± 2 yr) and older (n = 16, 72 ± 1 yr) adult men, with biopsies before and after 12 wk of resistance-type exercise training in the older subjects. Immunohistochemistry was used to assess skeletal muscle fiber size, capillary contacts (CC) per muscle fiber, and the capillary-to-fiber perimeter exchange (CFPE) index in type I and II muscle fibers. RESULTS: Type II muscle fibers were smaller in old versus young (4507 ± 268 vs 6084 ± 497 μm, respectively, P = 0.007). Type I and type II muscle fiber CC and CFPE index were smaller in old compared with young muscle (CC type I: 3.8 ± 0.2 vs 5.0 ± 0.3; CC type II: 3.2 ± 0.2 vs 4.2 ± 0.2, respectively; both P < 0.001). Resistance-type exercise training increased type II muscle fiber size only. In addition, CC and CFPE index increased in both the type I (26% ± 9% and 27% ± 8%) and type II muscle fibers (33% ± 7% and 24% ± 6%, respectively; all P ≤ 0.001) after 12 wk resistance training in older men. CONCLUSIONS: We conclude that resistance-type exercise training can effectively augment skeletal muscle fiber capillarization in older men. The greater capillary supply may be an important prerequisite to reverse anabolic resistance and support muscle hypertrophy during lifestyle interventions aiming to support healthy aging.
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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) | 0.001 | 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".