Glucose and glycogen affects Ca <sup>2+</sup> <scp>transient during</scp> fatigue to a greater extent in the least than in the most fatigue resistant mouse <scp>FDB</scp> fibers
Bibliographic record
Abstract
Abstract The overall objective was to determine how no extracellular glucose and/or low glycogen content affect fatigue kinetics in mouse flexor digitorum brevis (FDB) single muscle fibers. High glycogen content (Hi GLY), near normal in situ level, was obtained by incubating fibers in culture medium containing glucose and insulin while low glycogen content (Lo GLY), at about 19% of normal in situ level, was achieved by incubating fibers without glucose. Neither Lo GLY nor the absence of extracellular glucose (0GLU) affected tetanic [Ca 2+ ] i prior to fatigue. The number of contracting unfatigued fibers versus stimulus strength relationship of Lo GLY‐0GLU fibers was shifted to higher voltages compared to Hi GLY fibers exposed to 5.5 mM glucose (5GLU). The relationship for Lo GLY‐0GLU fibers was shifted back toward that of Hi GLY‐5GLU fibers when glucose was reintroduced, whereas the removal of glucose from Hi GLY‐5GLU fibers had no effect. Fatigue was elicited with one 200 ms long tetanic contraction every s for 3 min. Both Lo GLY and 0GLU increased the rate at which intracellular tetanic concentration ([Ca 2+ ] i ) declined and unstimulated [Ca 2+ ] i increased during fatigue in the order of the least fatigue resistant > mid fatigue resistant > the most fatigue resistant fibers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".