Quantitative assessment of human muscle glycogen granules size and number in subcellular locations during recovery from prolonged exercise
Bibliographic record
Abstract
Although data relating to muscle glycogen are interpreted as showing it is homogenous when quantified biochemically, it is actually in granules in specific subcellular locations. We hypothesized that postexercise restoration of muscle glycogen would occur initially by an increase in granule number followed by an increase in size, and also that restoration would differ in various subcellular locations. Five men performed prolonged exercise and had muscle biopsies taken at 0, 4, 24 and 48 h of recovery. We quantified granule number and size as well as the total volume of glycogen in the subsarcolemmal and the intra- and intermyofibrillar regions, using transmission electron microscopy. Muscle glycogen was reduced to 36 +/- 8.3 mmol glucosyl units (kg dry weight)(-1) at exhaustion, and was preferentially depleted and subsequently repleted in the intramyofibrillar space. The repletion rate was greatest in the first 4 h; this was associated with a 186% increase in number (P < or = 0.05) and no change in particle size (P > or = 0.05). From 4 h to 48 h, there was an increase in particle size (P < or = 0.05) but not number (P > or = 0.05). Net rate of G volume synthesis per unit area was 50% greater (P < or = 0.05) in the subsarcolemmal than the myofibrillar compartment. Conversely, the net rate of single-particle volume synthesis was greater (P < or = 0.05) in the myofibrillar than the subsarcolemmal compartment. Glycogen granules varied in size and number depending on location, and in all compartments resynthesis of glycogen was characterized initially by an increase in granule number and later by an increase in size.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".