Failing mouse hearts utilize energy inefficiently and benefit from improved coupling of glycolysis and glucose oxidation
Bibliographic record
Abstract
AIMS: To determine whether post-infarction LV dysfunction is due to low energy availability or inefficient energy utilization, we compared energy metabolism in normal and failing hearts. We also studied whether improved coupling of glycolysis and glucose oxidation by knockout of malonyl CoA decarboxylase (MCD-KO) would have beneficial effects on LV function and efficiency. METHODS AND RESULTS: Male C57BL/6 mice were subjected to coronary artery ligation (CAL) or sham operation (SHAM) procedure. After 4 weeks and echocardiographic evaluation, hearts were perfused (working mode) to measure LV function and rates of energy metabolism. Similar protocols using MCD-KO mice and wild-type (WT) littermates were used to assess consequences of MCD deficiency. Relative to SHAM, CAL hearts had impaired LV function [lower % ejection fraction (%EF, 49%) and LV work (46%)]. CAL hearts had higher rates (expressed per LV work) of glycolysis, glucose oxidation, and proton production. LV work per ATP production from exogenous sources was lower in CAL hearts, indicative of inefficient exogenous energy substrate utilization. Fatty acid oxidation rates, ATP, creatine, and creatine phosphate contents were unaffected. Utilization of endogenous substrates, triacylglycerol and glycogen, was similar in CAL and SHAM hearts. MCD-KO CAL hearts had 31% higher %EF compared with that of WT-CAL, and lower rates of glycolysis, glucose oxidation, proton production, and ATP production, indicative of improved efficiency. CONCLUSION: CAL hearts are inefficient in utilizing energy for mechanical function, possibly due to higher proton production arising from mismatched glycolysis and glucose oxidation. MCD deficiency lessens proton production, LV dysfunction, and inefficiency of exogenous energy substrate utilization.
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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".