Cellular responses in skeletal muscle to a season of ice hockey
Bibliographic record
Abstract
We hypothesized that a season of ice hockey would result in extensive remodeling of muscle. Tissue sampled from the vastus lateralis of 15 players (age = 20.6 ± 0.4 years; mean ± SE) prior to (PRE) and following (POST) a season was used to characterize specific adaptations. Measurement of representative metabolic pathway enzymes indicated higher maximal activities in POST than in PRE (p < 0.05) for succinic dehydrogenase (3.26 ± 0.31 vs. 3.91 ± 0.11 mol mg protein(-1) min(-1)), citrate synthase (7.26 ± 0.70 vs. 8.70 ± 0.55 mol mg protein(-1) min(-1)), and phosphofructokinase (12.8 ± 1.3 vs. 14.4 ± 0.96 mol mg protein(-1) min(-1)) only. The season resulted in an increase in Na+-K+-ATPase concentration (253 ± 6.3 vs. 265 ± 6.0 pmol g(-1) wet weight), a decrease (p < 0.05) in maximal activity of the sarcoplasmic reticulum Ca2+-ATPase (107 ± 4.2 micromol g protein(-1) min(-1) vs. 92.0 ± 4.6 micromol g protein(-1) min(-1)), and no change in the distribution (%) of fibre types. A smaller (p < 0.05) cross-sectional area (CSA) for both type I (-11.7%) and type IIA (-18.2%) fibres and a higher (p < 0.05) capillary count/CSA for type I (+17.9%) and type IIA (+17.2%) were also found over the season. No changes were found in peak oxygen consumption (51.4 ± 1.2 mL kg(-1) min(-1) vs. 52.3 ± 1.3 mL kg(-1) min(-1)). The results suggest, based on the alterations in oxidative and perfusion potentials and muscle mass, that the dominant adaptations are in support of oxidative metabolism, which occurs at the expense of fibre CSA and possibly force-generating potential.
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 | 0.001 | 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".