Ivabradine and metoprolol differentially affect cardiac glucose metabolism despite similar heart rate reduction in a mouse model of dyslipidemia
Bibliographic record
Abstract
While heart rate reduction (HRR) is a target for the management of patients with heart disease, contradictory results were reported using ivabradine, which selectively inhibits the pacemaker If current, vs. β-blockers like metoprolol. This study aimed at testing whether similar HRR with ivabradine vs. metoprolol differentially modulates cardiac energy substrate metabolism, a factor determinant for cardiac function, in a mouse model of dyslipidemia (hApoB+/+;LDLR−/−). Following a longitudinal study design, we used 3- and 6-mo-old mice, untreated or treated for 3 mo with ivabradine or metoprolol. Cardiac function was evaluated in vivo and ex vivo in working hearts perfused with 13C-labeled substrates to assess substrate fluxes through energy metabolic pathways. Compared with 3-mo-old, 6-mo-old dyslipidemic mice had similar cardiac hemodynamics in vivo but impaired ( P < 0.001) contractile function (aortic flow: −45%; cardiac output: −34%; stroke volume: −35%) and glycolysis (−24%) ex vivo. Despite inducing a similar 10% HRR, ivabradine-treated hearts displayed significantly higher stroke volume values and glycolysis vs. their metoprolol-treated counterparts ex vivo, values for the ivabradine group being often not significantly different from 3-mo-old mice. Further analyses highlighted additional significant cardiac alterations with disease progression, namely in the total tissue level of proteins modified by O-linked N-acetylglucosamine ( O-GlcNAc), whose formation is governed by glucose metabolism via the hexosamine biosynthetic pathway, which showed a similar pattern with ivabradine vs. metoprolol treatment. Collectively, our results emphasize the implication of alterations in cardiac glucose metabolism and signaling linked to disease progression in our mouse model. Despite similar HRR, ivabradine, but not metoprolol, preserved cardiac function and glucose metabolism during disease progression.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".