Ischemia-induced activation of AMPK does not increase glucose uptake in glycogen-replete isolated working rat hearts
Bibliographic record
Abstract
Alterations in myocardial glucose metabolism are a key determinant of ischemia-induced depression of left ventricular mechanical function. Since myocardial glycogen is an important source of endogenous glucose, we compared the effects of ischemia on glucose uptake and utilization in isolated working rat hearts in which glycogen content was either replete (G replete, 114 micromol/g dry wt) or partially depleted (G depleted, 71 mumol/g dry wt). The effects of low-flow ischemia (LFI, 0.5 ml/min) on glucose uptake, glycogen turnover (glycogenolysis and glycogen synthesis), glycolysis, adenosine 5'-monophosphate-activated protein kinase (AMPK) activity, and GLUT4 translocation were measured. Relative to preischemic values, LFI caused a time-dependent reduction in glycogen content in both G-replete and G-depleted groups due to an acceleration of glycogenolysis (by 12-fold and 6-fold, respectively). In G-replete hearts, LFI (15 min) decreased glucose uptake (by 59%) and did not affect GLUT4 translocation. In G-depleted hearts, LFI also decreased initially glucose uptake (by 90%) and glycogen synthesis, but after 15 min, when glycogenolysis slowed due to exhaustion of glycogen content, glucose uptake increased (by 31%) in association with an increase in GLUT4 translocation. After 60 min of LFI, glucose uptake, glycogenolysis, and glycolysis recovered to near-preischemic values in both groups. LFI increased AMPK activity in a time-dependent manner in both groups (by 6-fold and 4-fold, respectively). Thus, when glycogen stores are replete before ischemia, ischemia-induced AMPK activation is not sufficient to increase glucose uptake. Under these conditions, an acceleration of glycogen degradation provides sufficient endogenous substrate for glycolysis during 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".