Malleability of human skeletal muscle Na<sup>+</sup>-K<sup>+</sup>-ATPase pump with short-term training
Bibliographic record
Abstract
To investigate the hypothesis that short-term submaximal training would result in changes in Na(+)-K(+)-ATPase content, activity, and isoform distribution in skeletal muscle, seven healthy, untrained men [peak aerobic power (peak oxygen consumption; Vo(2 peak)) = 45.6 ml x kg(-1) x min(-1) (SE 5.4)] cycled for 2 h/day at 60-65% Vo(2 peak) for 6 days. Muscle tissue, sampled from the vastus lateralis before training (0 days) and after 3 and 6 days of training and analyzed for Na(+)-K(+)-ATPase content, as assessed by the vanadate facilitated [(3)H]ouabain-binding technique, was increased (P < 0.05) at 3 days (294 +/- 8.6 pmol/g wet wt) and 6 days (308 +/- 15 pmol/g wet wt) of training compared with 0 days (272 +/- 9.7 pmol/g wet wt). Maximal Na(+)-K(+)-ATPase activity as evaluated by the 3-O-methylfluorescein phosphatase assay was increased (P < 0.05) by 6 days (53.4 +/- 5.9 nmol x h(-1) x mg protein(-1)) but not by 3 days (35.9 +/- 4.5 nmol x h(-1) x mg protein(-1)) compared with 0 days (37.8 +/- 3.7 nmol x h(-1) x mg protein(-1)) of training. Relative isoform distribution, measured by Western blot techniques, indicated increases (P < 0.05) in alpha(2)-content by 3 days and beta(1)-content by 6 days of training. These results indicate that prolonged aerobic exercise represents a potent stimulus for the rapid adaptation of Na(+)-K(+)-ATPase content, isoform, and activity characteristics.
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 | 0.001 |
| 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 | 0.000 |
| 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".