Pressure-overload-induced heart failure induces a selective reduction in glucose oxidation at physiological afterload
Bibliographic record
Abstract
AIMS: Development of heart failure is known to be associated with changes in energy substrate metabolism. Information on the changes in energy substrate metabolism that occur in heart failure is limited and results vary depending on the methods employed. Our aim is to characterize the changes in energy substrate metabolism associated with pressure overload and ischaemia-reperfusion (I/R) injury. METHODS AND RESULTS: We used transverse aortic constriction (TAC) in mice to induce pressure overload-induced heart failure. Metabolic rates were measured in isolated working hearts perfused at physiological afterload (80 mmHg) using (3)H- or (14)C-labelled substrates. As a result of pressure-overload injury, murine hearts exhibited: (i) hypertrophy, systolic, and diastolic dysfunctions; (ii) reduction in LV work, (iii) reduced rates of glucose and lactate oxidations, with no change in glycolysis or fatty acid oxidation and a small decrease in triacylglycerol oxidation, and (iv) increased phosphorylation of AMPK and a reduction in malonyl-CoA levels. Sham hearts produced more acetyl CoA from carbohydrates than from fats, whereas TAC hearts showed a reverse trend. I/R in sham group produced a metabolic switch analogous to the TAC-induced shift to fatty acid oxidation, whereas I/R in TAC hearts greatly exacerbated the existing imbalance, and was associated with a poorer recovery during reperfusion. CONCLUSIONS: Pressure overload-induced heart failure and I/R shift the preference of substrate oxidation from glucose and lactate to fatty acid due to a selective reduction in carbohydrate oxidation. Normalizing the balance between metabolic substrate utilization may alleviate pressure-overload-induced heart failure and ischaemia.
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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) | 0.001 | 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".