Association of AMP kinase β <sub>2</sub> subunit with glycogen particles as revealed by immunoelectron microscopy
Bibliographic record
Abstract
AMP kinase β 2 subunit contains a functional glycogen binding domain (β‐GBD) that links AMPK to glycogen metabolism. By routine electron microscopy, glycogen deposits in cells are easily visualized as small rosettes of dark granules. However, immunocytochemistry requires weak fixation protocols that allow preservation of protein antigenicity but have the drawback of preventing retention of certain cellular elements such as glycogen. The cells thus appear vacuolated. Immunogold for AMPK subunits on such tissues leads to specific labelings located only in cytoplasmic areas surrounding the endoplasmic reticulum. We herein report the development of a new protocol for immunoelectron microscopy that retains glycogen deposits within the cells with the possibility of performing successfully the immunolabeling for the AMPK subunits. Upon applying specific antibodies against the various AMPK subunits on rat liver tissue, quantitative immunogold revealed that the labeling for the β 2 subunit is closely associated, for its very large majority, with the glycogen particles of the cell. The other subunits, α 1 and α 2 , are more abundant in cytoplasmic areas close to the endoplasmic reticulum and mitochondria. These results demonstrate the existence of a structural link between AMPK β 2 subunit and glycogen, a major energy store of the cell.
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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 | 0.001 |
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".