A century of exercise physiology: effects of muscle contraction and exercise on skeletal muscle Na+,K+-ATPase, Na+ and K+ ions, and on plasma K+ concentration—historical developments
Bibliographic record
Abstract
Abstract This historical review traces key discoveries regarding K + and Na + ions in skeletal muscle at rest and with exercise, including contents and concentrations, Na + ,K + -ATPase (NKA) and exercise effects on plasma [K + ] in humans. Following initial measures in 1896 of muscle contents in various species, including humans, electrical stimulation of animal muscle showed K + loss and gains in Na + , Cl − and H 2 0, then subsequently bidirectional muscle K + and Na + fluxes. After NKA discovery in 1957, methods were developed to quantify muscle NKA activity via rates of ATP hydrolysis, Na + /K + radioisotope fluxes, [ 3 H]-ouabain binding and phosphatase activity. Since then, it became clear that NKA plays a central role in Na + /K + homeostasis and that NKA content and activity are regulated by muscle contractions and numerous hormones. During intense exercise in humans, muscle intracellular [K + ] falls by 21 mM (range − 13 to − 39 mM), interstitial [K + ] increases to 12–13 mM, and plasma [K + ] rises to 6–8 mM, whilst post-exercise plasma [K + ] falls rapidly, reflecting increased muscle NKA activity. Contractions were shown to increase NKA activity in proportion to activation frequency in animal intact muscle preparations. In human muscle, [ 3 H]-ouabain-binding content fully quantifies NKA content, whilst the method mainly detects α 2 isoforms in rats. Acute or chronic exercise affects human muscle K + , NKA content, activity, isoforms and phospholemman (FXYD1). Numerous hormones, pharmacological and dietary interventions, altered acid–base or redox states, exercise training and physical inactivity modulate plasma [K + ] during exercise. Finally, historical research approaches largely excluded female participants and typically used very small sample sizes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".