AMP-Activated Protein Kinase and O-GlcNAcylation, Two Partners Tightly Connected to Regulate Key Cellular Processes
Bibliographic record
Abstract
The AMP-activated protein kinase (AMPK) is an important cellular energy sensor. Its activation under energetic stress is known to activate energy-producing pathways and to inactivate energy-consuming pathways, promoting ATP preservation and cell survival. AMPK has been shown to play protective role in many pathophysiological processes including cardiovascular diseases, diabetes, and cancer. Its action is multi-faceted and comprises short-term regulation of enzymes by direct phosphorylation as well as long-term adaptation via control of transcription factors and cellular events such as autophagy. During the last decade, several studies underline the particular importance of the interaction between AMPK and the post-translational modification called O-GlcNAcylation. O-GlcNAcylation means the O-linked attachment of a single N-acetylglucosamine moiety on serine or threonine residues. O-GlcNAcylation plays a role in multiple physiological cellular processes but is also associated with the development of various diseases. The first goal of the present review is to present the tight molecular relationship between AMPK and enzymes regulating O-GlcNAcylation. We then draw the attention of the reader on the putative importance of this interaction in different pathophysiological events.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".