The role of AMPK in cardiomyocyte health and survival
Bibliographic record
Abstract
Cellular energy homeostasis is a fundamental process that governs the overall health of the cell and is paramount to cell survival. Central to this is the control of ATP generation and utilization, which is regulated by a complex myriad of enzymatic reactions controlling cellular metabolism. In the cardiomyocyte, ATP generated from substrate catabolism is used for numerous cellular processes including maintaining ionic homeostasis, cell repair, protein synthesis and turnover, organelle turnover, and contractile function. In many instances, cardiovascular disease is associated with impaired cardiac energetics and thus the signalling that regulates pathways involved in cardiomyocyte metabolism may be potential targets for pharmacotherapy designed to help treat cardiovascular disease. An important regulator of cardiomyocyte energy homeostasis is adenosine monophosphate-activated protein kinase (AMPK). AMPK is a serine-threonine kinase that functions primarily as a metabolic sensor to coordinate anabolic and catabolic activities in the cell via the phosphorylation of multiple proteins involved in metabolic pathways. In addition to the direct role that AMPK plays in the regulation of cardiomyocyte metabolism, AMPK can also either directly or indirectly influence other cellular processes such as regulating mitochondrial function, post-translation acetylation, autophagy, mitophagy, endoplasmic reticulum stress, and apoptosis. Thus, AMPK is implicated in the control of a wide variety of cellular processes that can influence cardiomyocyte health and survival. In this review, we will discuss the important role that AMPK plays in regulating cardiac metabolism, as well as the additional cellular processes that may contribute to cardiomyocyte function and survival in the healthy and the diseased heart. This article is part of a Special Issue entitled: The role of post-translational protein modifications on heart and vascular metabolism edited by Jason R.B. Dyck & Jan. F.C. Glatz.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".