Carvedilol suppresses fatty acid oxidation and stimulates glycolysis in C2C12 cells
Bibliographic record
Abstract
Beta adrenergic receptor blocking drugs (β-blockers) are used chronically in many cardiovascular diseases such as hypertension, ischemic heart disease, arrhythmia, and heart failure. Beneficial effects are associated with the inhibition of symphathetic nervous system hyperactivity, reduction of heart rate, and remodeling by blocking the mitogenic activity of catecholamines. A possible effect of β-blockers on substrate metabolism has also been suggested. The direct effects of β-blockers on mouse C2C12 cells were investigated in this study. C2C12 cells were grown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and differentiated into myotubes in the same medium that contained 1% FBS. Palmitic acid oxidation and glycolysis were measured by using [9,10-(3)H]palmitate and [5-(3)H]glucose, respectively. The amount of (3)H(2)O was measured as an indicator of substrate usage. Carvedilol (100 µmol/L) inhibited palmitate oxidation and increased glycolysis by nearly 50%. Prazosin altered substrate metabolism in a similar fashion as carvedilol, whereas propranolol or bisoprolol were devoid of metabolic effects. When added to mimic sympathetic activation, epinephrine stimulated glycolysis but did not alter fatty acid oxidation. Based on these results, carvedilol appears to have direct effects on substrate metabolism that are related to the blockade of α1 adrenergic receptors.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".