Modulation of CPT‐1 activity and sensitivity by metoprolol
Bibliographic record
Abstract
Carnitine palmitoyltransferase‐1 (CPT‐1) activity is decreased by increasing malonyl CoA levels, increasing the sensitivity of CPT‐1 to malonyl CoA, or decreasing catalytic activity. We have previously reported that chronic metoprolol treatment decreases both CPT‐1 activity and sensitivity to malonyl CoA (MCoA). The aim of this study was to investigate the mechanism of this effect. We measured the expression of CPT‐1, PPAR‐α and pyruvate dehydrogenase kinase‐4 (PDK‐4) in control and diabetic hearts following chronic metoprolol treatment. To measure the acute effect of metoprolol on cardiac CPT‐1, control and diabetic hearts were perfused for 30 minutes with metoprolol. CPT‐1 activity and the IC 50 of MCoA were measured. Metoprolol decreased total CPT‐1 expression, but did not induce a CPT‐1 isoform shift. PDK‐4 expression did not correlate with CPT‐1 expression, and PPAR‐α expression was not altered by metoprolol. CPT‐1 expression changes are therefore unlikely to be attributable to PPAR‐α. Metoprolol acutely decreased both the activity and sensitivity of CPT‐1. MCoA levels were decreased by metoprolol only in control hearts. MCoA levels did not correspond with fatty acid oxidation rates. These results indicate that metoprolol acutely regulates CPT‐1 independent of the classical MCoA control mechanism. This work was supported by the Heart and Stroke Foundation of B.C. and Yukon.
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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".