Effects of adenosine on myocardial glucose and palmitate metabolism after transient ischemia: role of 5′-AMP-activated protein kinase
Bibliographic record
Abstract
Loss of cardioprotection by adenosine in hearts stressed by transient ischemia may be due to its effects on glucose metabolism. In the absence of transient ischemia, adenosine inhibits glycolysis, whereas it accelerates glycolysis after transient ischemia. Inasmuch as 5'-AMP-activated protein kinase (AMPK) is implicated as a regulator of glucose and fatty acid utilization, this study determined whether a differential alteration of AMPK activity contributes to acceleration of glycolysis by adenosine in hearts stressed by transient ischemia. Studies were performed in working rat hearts perfused aerobically under normal conditions or after transient ischemia (two 10-min periods of ischemia followed by 5 min of reperfusion). LV work was not affected by adenosine. AMPK phosphorylation was not affected by transient ischemia; however, phosphorylation and activity were increased nine- and threefold, respectively, by adenosine in stressed hearts. Phosphorylation of acetyl-CoA carboxylase and rates of palmitate oxidation were unaltered. Glycolysis and calculated proton production were increased 1.8- and 1.7-fold, respectively, in hearts with elevated AMPK activity. Elevated AMPK activity was associated with inhibition of glycogen synthesis and unchanged rates of glucose uptake and glycogenolysis. Phentolamine, an alpha-adrenoceptor antagonist, which prevents adenosine-induced activation of glycolysis in stressed hearts, prevented AMPK phosphorylation. These data demonstrate that adenosine-induced activation of AMPK after transient ischemia is not sufficient to alter palmitate oxidation or glucose uptake. Rather, activation of AMPK alters partitioning of glucose away from glycogen synthesis; the increase in glycolysis may in part contribute to loss of adenosine-induced cardioprotection in hearts subjected to transient ischemia.
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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 | 0.000 |
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".