When the close relationship between function and substrate metabolism in ex vivo working mouse hearts goes beyond differences in genetic background
Bibliographic record
Abstract
Transgenic mice are valuable study model for cardiovascular research. The choice of appropriate control is, however, crucial given the impact of mouse genetic background on various parameters, including cardiac function. In this study, we tested for a link between the cardiac functional and metabolic phenotype of 5 different mouse strains (Bl6J, Bl6CR, SJL, 129SV and ATX). We used our model of working hearts perfused ex vivo with physiological concentrations of 13C‐labeled carbohydrates (CHO) and fatty acids (FA) to assess flux through energy producing pathways. Results reveal marked differences in most functional and metabolic flux parameters measured amongst all control strains. Most striking was the 129SV heart, which showed a better ex vivo function and a shift from FA to glucose oxidation. Beyond all these variations, we found significant correlations between specific metabolic flux and functional parameters, suggesting the role of i) glycolysis as a determinant of cardiac work (cardiac power: r=0.54; dP/dtmax; contractility: r=0.43), ii) CHO oxidation of heart rate (r=0.51) and stroke volume (r=−0.72), and iii) FA oxidation of MVO2 (r=0.70) and coronary flow (r=0.64). Our results highlight a close link between specific functional and metabolic flux parameters in mouse hearts, which goes beyond differences in genetic background and ought to be considered for data interpretation. Supported by the CIHR.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".