Glycogenin protein levels in sub‐cellular fractions of different muscle fiber types from stimulated rodent hind limb following changes in glycogen content
Bibliographic record
Abstract
Glycogenin (GN) is bound to glycogen. At rest, GN distribution mimics glycogen (cytosolic/ membrane‐associated). GN may also co‐localize with actin. GN distribution across muscle fiber types following contraction was examined. One hind limb (40 F Sprague Dawley rats) was stimulated for 40 min to lower glycogen. Unstimulated and stimulated soleus (SOL), red (RG), and white (WG) gastrocnemius muscles were separated into sub‐cellular fractions [pellet 1/supernatant 1= P1/S1; S1 separated into S2 (cytosolic) + S3 (membrane/glycogen) + P3 (cytoskeletal)] and examined for total and unglycosylated GN levels. Tissue (corresponding unstimulated and stimulated) was grouped (n=6) by post‐stimulation glycogen level (WGI <40; WGII <100; RGI <100, RGII >100; SOL >100 μmol▸ dry wt.‐1). At rest, ~50% of GN was located in each P1 and S1. In S1, ~4, 87, and 9% of GN was located in S2, S3 and P3 fractions, respectively. Post‐stimulation, GN increased in S2 and decreased in S3 and P3 fractions (P≤0.05). <25% of GN in S2 was unglycosylated, suggesting re‐distribution of mostly small granules. In WGI, however, glycogen content decreased the most and the distribution of total GN (and glycogen synthase) in the P1 fraction increased. Low glycogen content in WG may lead to sequestering of GN (and GS) in the P1 fraction (potentially with actin) for glycogen re‐synthesis following acute stimulation in rodents. Funded by NSERC of Canada.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".