Not all skeletal muscle fibers depend on the myoprotection of K <sub>ATP</sub> channels during fatigue (1102.15)
Bibliographic record
Abstract
During fatigue, KATP channels are crucial in reducing action potential amplitude to eventually lower Ca 2+ release by sarcoplasmic reticulum, which helps preserve ATP during a metabolic stress by decreasing Ca 2+ ATPase and myosin ATPase activity. In the absence of KATP channel activity, skeletal muscle muscles suffer major contractile dysfunctions, which lead to faster fatigue rate because of fiber damage. In our studies at 37°C, we have observed a tremendous variability in the fatigue kinetics among mouse single FDB muscle fibers. Under control conditions, such variability is expected as fatigue resistance is in the order of type I>IIA>IIX>IIB (note IIB fibers are not present in FDB). However, we also observed a large variability in fatigue kinetics when KATP channels are completely blocked with 10 µM glibenclamide. Our results suggest that the importance of the KATP channel for myoprotection during fatigue is in the order of type IIX > IIA > I types, an order similar to the difference in KATP channel content between fiber types; i.e., the KATP channels are the most important in glycolytic fibers and the least important in oxidative fibers. Grant Funding Source : NSERC
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".