Energy metabolism during fatigue in FDB muscle is impaired by the lack of K <sub>ATP</sub> channel activity
Bibliographic record
Abstract
The KATP channel is crucial in preventing fiber damage during exercise and muscle fatigue. The channel is activated when energy levels fall and thus behaves as an energy sensor. Once activated, it directly reduces action potential amplitude lowering Ca2+ release and force production in order to prevent damaging ATP depletion. So far, it remains unknown how the KATP channel affects energy metabolism during muscle fatigue. The objective of this study was to determine whether KATP channel deficient FDB muscle from Kir6.2−/− mice have lower ATP levels and impaired ATP generation during fatigue compared to wild type FDB. The decreases in PCr was not different between W.T. and Kir6.2−/− FDB while ATP levels were significantly lower in Kir6.2−/− FDB. Glucose uptake was less and glycogen breakdown greater in Kir6.2−/− FDB; but the amount of glucosyl units entering glycolysis was not different between the two muscle groups. Surprisingly, Kir6.2−/− FDB produced less lactate and similar amount of 14CO2 when compared to wild type FDB, which suggests that the amount of unaccounted glucosyl units was greater in Kir6.2−/− FDB; i.e., energy metabolism appeared impaired in FDB lacking KATP channel activity.
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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) | 0.002 | 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".