Fatigue preconditioning increases fatigue resistance in mouse FDB using a different intracellular signalling pathway to ischemic preconditioning.
Bibliographic record
Abstract
The objective of this study was to determine the nature of the intracellular signalling pathway that regulates fatigue preconditioning (FPC) whereby one fatigue bout (FAT1) acutely increases the fatigue resistance of muscle during a second fatigue bout (FAT2). All fatigue bouts were elicited with one tetanic contraction every s for 3 min and FAT2 was elicited 60 min after FAT1. The decreases in peak tetanic Ca 2+ i and force were significantly slower while the increases in unstimulated Ca 2+ i and force were significantly less during FAT2 than during FAT1. The differences between FAT2 and FAT1 were even greater when KATP channels were blocked with 10 µM glibenclamide. Ischemic preconditioning (IPC) is a phenomenon in which short, non‐ damaging ischemic periods increase muscle resistance to the damaging effects of a long and damaging ischemic period. While adenosine, sarcolemmal and mitochondrial KATP channels, protein kinase C and reactive oxygen species have all been implicated in IPC, the addition of their specific blockers during FAT1 did not prevent the increased fatigue resistance during FAT2. We therefore conclude that IPC and FPC have different intracellular signalling pathways.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".