Ivabradine reduces heart rate while preserving metabolic fluxes and energy status of healthy normoxic working hearts
Bibliographic record
Abstract
Heart rate reduction (HRR) is an important target in the management of patients with chronic stable angina. Most available drugs for HRR, such as β-blockers, have adverse effects, including on cardiac energy substrate metabolism, a well-recognized determinant of cardiac homeostasis. This study aimed at 1) testing whether HRR by ivabradine (IVA) alters substrate metabolism in the healthy normoxic working heart and 2) comparing the effect of IVA with that of the β-blocker metoprolol (METO). This was assessed using our well-established model of ex vivo mouse heart perfusion in the working mode, which enables concomitant evaluation of myocardial contractility and metabolic fluxes using (13)C-labeled substrates. Hearts were perfused in the absence (controls; n = 10) or presence of IVA (n = 10, 3 μM) with or without atrial pacing to abolish HRR in the IVA group. IVA significantly reduced HR (35 ± 5%) and increased stroke volume (39 ± 9%) while maintaining similar cardiac output, contractility, power, and efficiency. Effects of IVA on HR and stroke volume were reversed by atrial pacing. At the metabolic level, IVA did not impact on substrate selection to citrate formation, rates of glycolysis, or tissue levels of high-energy phosphates. In contrast, METO, at concentrations up to 40 μM, decreased markedly cardiac function (flow: 25 ± 6%; stroke volume: 30 ± 10%; contractility: 31 ± 9%) as well as glycolysis (2.9-fold) but marginally affected HR. Collectively, these results demonstrate that IVA selectively reduces HR while preserving energy substrate metabolism of normoxic healthy working mouse hearts perfused ex vivo, a model that mimics to some extent the denervated transplanted heart. Our results provide the impetus for testing selective HRR by IVA on cardiac substrate metabolism in pathological models.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".