Skeletal muscle fatigue – regulation of excitation–contraction coupling to avoid metabolic catastrophe
Bibliographic record
Abstract
ATP provides the energy in our muscles to generate force, through its use by myosin ATPases, and helps to terminate contraction by pumping Ca(2+) back into the sarcoplasmic reticulum, achieved by Ca(2+) ATPase. The capacity to use ATP through these mechanisms is sufficiently high enough so that muscles could quickly deplete ATP. However, this potentially catastrophic depletion is avoided. It has been proposed that ATP is preserved not only by the control of metabolic pathways providing ATP but also by the regulation of the processes that use ATP. Considering that contraction (i.e. myosin ATPase activity) is triggered by release of Ca(2+), the use of ATP can be attenuated by decreasing Ca(2+) release within each cell. A lower level of Ca(2+) release can be accomplished by control of membrane potential and by direct regulation of the ryanodine receptor (RyR, the Ca(2+) release channel in the terminal cisternae). These highly redundant control mechanisms provide an effective means by which ATP can be preserved at the cellular level, avoiding metabolic catastrophe. This Commentary will review some of the known mechanisms by which this regulation of Ca(2+) release and contractile response is achieved, demonstrating that skeletal muscle fatigue is a consequence of attenuation of contractile activation; a process that allows avoidance of metabolic catastrophe.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".