Mechanical Circulatory Unloading Promotes Proteins Synthesis and Maintains Leucine Oxidation
Bibliographic record
Abstract
Mechanical ventricular unloading by arterial‐venous extracorporeal membrane oxygenation (ECMO) serves as a bridge to recovery in infants with severe acute heart failure. The influence of mechanical circulatory support on protein synthesis and degradation is unknown. We tested the hypothesis: ECMO induces reductions in myocardial protein synthesis and promotes increased amino acid oxidation. Anesthetized immature swine (n=20) received intracoronary infusion of 13 C 6 , 15 N L‐leucine alone or with 2‐ 13 C pyruvate after 8 hours of loading (LOAD) or ECMO. Leucine incorporation into protein and contribution to the citric acid cycle (CAC) relative to pyruvate was determined using 13 C‐magnetic resonance spectroscopy and GCMS. ECMO increased the protein fractional synthesis rate (0.91%±0.04% vs. 0.63%±0.10%, p<0.06), but did not alter leucine oxidation relative to pyruvate. ECMO also increased mTOR phosphorylation (by immunoblot) and decreased eukaryotic‐Elongation factor‐2 phosphorylation. Conclusions Mechanical unloading in the form of ECMO enhances protein synthesis without reducing amino acid contribution of acetyl‐CoA to the CAC. The protein synthesis occurs with activation of the mTOR pathway. These data suggest that atrophy induced by clinical mechanical circulatory support and ventricular unloading is caused by accelerated protein degradation.
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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) | 0.000 | 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 | 0.000 |
| 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".