AMP-activated protein kinase influences metabolic remodeling in H9c2 cells hypertrophied by arginine vasopressin
Bibliographic record
Abstract
Substrate use switches from fatty acids toward glucose in pressure overload-induced cardiac hypertrophy with an acceleration of glycolysis being characteristic. The activation of AMP-activated protein kinase (AMPK) observed in hypertrophied hearts provides one potential mechanism for the acceleration of glycolysis. Here, we directly tested the hypothesis that AMPK causes the acceleration of glycolysis in hypertrophied heart muscle cells. The H9c2 cell line, derived from the embryonic rat heart, was treated with arginine vasopressin (AVP; 1 microM) to induce a cellular model of hypertrophy. Rates of glycolysis and oxidation of glucose and palmitate were measured in nonhypertrophied and hypertrophied H9c2 cells, and the effects of inhibition of AMPK were determined. AMPK activity was inhibited by 6-[4-(2-piperidin-1- yl-ethoxy)-phenyl]-3-pyridin-4-yl-pyrrazolo-[1,5-a]pyrimidine (compound C) or by adenovirus-mediated transfer of dominant negative AMPK. Compared with nonhypertrophied cells, glycolysis was accelerated and palmitate oxidation was reduced with no significant alteration in glucose oxidation in hypertrophied cells, a metabolic profile similar to that of intact hypertrophied hearts. Inhibition of AMPK resulted in the partial reduction of glycolysis in AVP-treated hypertrophied H9c2 cells. Acute exposure of H9c2 cells to AVP also activated AMPK and accelerated glycolysis. These elevated rates of glycolysis were not altered by AMPK inhibition but were blocked by agents that interfere with Ca(2+) signaling, including extracellular EGTA, dantrolene, and 2-aminoethoxydiphenyl borate. We conclude that the acceleration of glycolysis in AVP-treated hypertrophied heart muscle cells is partially dependent on AMPK, whereas the acute glycolytic effects of AVP are AMPK independent and at least partially Ca(2+) dependent.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".