Improvement of cardiac function and β-adrenergic signal transduction by propionyl L-carnitine in congestive heart failure due to myocardial infarction
Bibliographic record
Abstract
OBJECTIVES: Earlier studies have revealed beneficial effects of metabolic therapy in animals with congestive heart failure (CHF) due to myocardial infarction. Because heart failure is also associated with attenuated response to catecholamines, we examined the effects of propionyl L-carnitine (PLC) (a carnitine derivative) therapy on the beta-adrenoceptor (beta-AR) signal transduction in the failing heart. METHODS: Heart failure in rats was induced by occluding the coronary artery and 3 weeks later the animals were treated with or without 100 mg/kg (intraperitoneally, daily) PLC for 5 weeks. The animals were assessed for their left ventricular function and inotropic responses to isoproterenol. Crude membranes were isolated from the remote, nonischemic (viable) left ventricle and examined for changes in beta-AR and adenylyl cyclase (AC) activity. RESULTS: Animals with heart failure exhibited depressions in ventricular function, positive inotropic response to isoproterenol, beta-AR receptor density and basal AC activity; these changes were also attenuated by PLC treatment. The stimulation of AC activities with isoproterenol, 5'-guanyl imidodiphosphate, forskolin and sodium fluoride was decreased in the failing hearts and these changes were also prevented by PLC treatment. CONCLUSION: The results indicate that metabolic therapy with PLC not only attenuates the defects in heart function but also prevents changes in the beta-AR signal transduction in CHF due to myocardial infarction.
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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".