The metabolic “switch” AMPK regulates cardiac heparin-releasable lipoprotein lipase
Bibliographic record
Abstract
The "fuel gauge" AMP-activated protein kinase (AMPK) facilitates ATP production to meet energy demands during metabolic stress. Given the importance of lipoprotein lipase (LPL) in providing hearts with fatty acids (FA), the preferred substrate consumed by the heart, the objective of the present study was to investigate whether activation of AMPK influences LPL at its functionally relevant location, the coronary lumen. Hearts from overnight-fasted rats were first perfused with heparin to release LPL, and homogenates from these hearts were then used to measure total and phospho-AMPK-alpha by Western blotting. Manipulation of AMPK activity [with drugs like adenine 9-beta-D-arabinofuranoside (Ara-A) and insulin (that inhibit) or perhexiline and oligomycin (that stimulate)] and its influence on LPL was also determined. Fasting augmented the activity of both AMPK and luminal LPL on immediate removal of hearts, effects that still remained even after in vitro perfusion of hearts for 1 h. Inhibition of AMPK in fasted hearts using an inhibitor like Ara-A or through provision of insulin markedly lowered the enhanced luminal LPL activity. In contrast, AMPK activators, like perhexiline and oligomycin, produced a significant elevation in heparin-releasable LPL activity. Thus, with fasting or drugs that influence AMPK, a strong correlation between this metabolic switch and cardiac LPL activity was established. Our data suggest that, in addition to its direct role in promoting FA oxidation, AMPK-mediated recruitment of LPL to the coronary lumen could represent an immediate compensatory response by the heart to guarantee FA supply.
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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".