Parallel effects of β-adrenoceptor blockade on cardiac function and fatty acid oxidation in the diabetic heart: Confronting the maze
Bibliographic record
Abstract
Diabetic cardiomyopathy is a disease process in which diabetes produces a direct and continuous myocardial insult even in the absence of ischemic, hypertensive or valvular disease. The β-blocking agents bisoprolol, carvedilol and metoprolol have been shown in large-scale randomized controlled trials to reduce heart failure mortality. In this review, we summarize the results of our studies investigating the effects of β-blocking agents on cardiac function and metabolism in diabetic heart failure, and the complex inter-related mechanisms involved. Metoprolol inhibits fatty acid oxidation at the mitochondrial level but does not prevent lipotoxicity; its beneficial effects are more likely to be due to pro-survival effects of chronic treatment. These studies have expanded our understanding of the range of effects produced by β-adrenergic blockade and show how interconnected the signaling pathways of function and metabolism are in the heart. Although our initial hypothesis that inhibition of fatty acid oxidation would be a key mechanism of action was disproved, unexpected results led us to some intriguing regulatory mechanisms of cardiac metabolism. The first was upstream stimulatory factor-2-mediated repression of transcriptional master regulator PGC-1α, most likely occurring as a consequence of the improved function; it is unclear whether this effect is unique to β-blockers, although repression of carnitine palmitoyltransferase (CPT)-1 has not been reported with other drugs which improve function. The second was the identification of a range of covalent modifications which can regulate CPT-1 directly, mediated by a signalome at the level of the mitochondria. We also identified an important interaction between β-adrenergic signaling and caveolins, which may be a key mechanism of action of β-adrenergic blockade. Our experience with this labyrinthine signaling web illustrates that initial hypotheses and anticipated directions do not have to be right in order to open up meaningful directions or reveal new information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".