Ivabradine but not metoprolol preserves ex vivo function and glycolysis of working dyslipidemic mouse hearts without activation of stress signaling pathways
Bibliographic record
Abstract
Objective Elevated heart rate (HR) increases the risk for severe complications in patients with coronary heart diseases. This study aimed at testing the functional and metabolic impact of chronic HR reduction (HRR) induced by the selective inhibitor of the pacemaker I f current ivabradine (IVA) in comparison to the commonly used β‐blocker metoprolol (MET) in a dyslipidemic mouse model. Methods We assessed i) the functional and metabolic phenotype of dyslipidemic mouse hearts (ATX: hApoB +/+ LDLR −/− ) perfused ex vivo in working mode, and ii) activity of nutrient signaling pathways in non‐perfused hearts, at 3 and 6 months either untreated or treated for 3 months with IVA or MET (10% HRR in vivo ). Results Compared to their 3‐month‐old counterparts, 6‐month‐old ATX hearts displayed i) similar HR but decreased values (p<0.05) for cardiac output (25%) and power (22%), stroke volume (30%) and glycolysis (29%) when perfused ex vivo , and ii) exacerbated activation of energy and stress signaling pathways related to Akt, AMP kinase and the hexosamine biosynthetic pathway. All these alterations, except Akt, were attenuated by IVA (p<0.05) but tended to be exacerbated by MET. Conclusion In vivo chronic HRR induced by IVA but not MET limits alterations of ex vivo cardiac function and glycolysis, as well as of in vivo exacerbated activation of energy and stress signaling pathways associated with disease progression in ATX mouse.
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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) | 0.000 | 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) | 0.002 | 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".