AMPK and the Metabolic Actions of Metformin in Heart‐derived H9c2 cells
Bibliographic record
Abstract
Metformin stimulates glucose use and fatty acid oxidation in skeletal muscle and liver cells, reportedly via activation of AMP‐activated protein kinase (AMPK). Whether the metabolic actions of metformin in heart muscle can be attributed to AMPK is not yet known with certainty. Thus, we set out to determine if metformin stimulates glucose use in heart muscle by activating AMPK. Lactate production and glucose use were measured in heart derived H9c2 cells with or without infection by adenovirus containing a dominant‐negative mutant form of AMPK (DN‐AMPK). AMPK activity was determined after immunoprecipitation from cell homogenates. Cells were exposed to Krebs‐Henseleit solution containing substrates at physiological concentrations (5.5mM glucose, 0.4 mM palmitate) and 10 −7 M insulin without (CON) or with metformin (MET) (2mM). Glucose use and lactate production were 1.7‐ and 2‐fold greater in MET‐treated cells than in CON cells, respectively (n=6 per group, P<0.05), and AMPK was activated by MET. DN‐AMPK significantly reduced AMPK activity in H9c2 cells and abrogated the response of AMPK to metformin, but had no effect on glucose utilization or lactate production. Thus, these findings suggest that the metabolic actions of metformin in H9c2 cells are independent of AMPK activity and are mediated by other mechanisms. However, it is possible that residual AMPK activity is sufficiently large to stimulate glucose use and lactate production in response to metformin.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".