Application of high-dose propofol during ischemia improves postischemic function of rat hearts: effects on tissue antioxidant capacity
Bibliographic record
Abstract
Previous studies have shown that reactive oxygen species mediated lipid peroxidation in patients undergoing cardiac surgery occurs primarily during cardiopulmonary bypass. We examined whether application of a high concentration of propofol during ischemia could effectively enhance postischemic myocardial functional recovery in the setting of global ischemia and reperfusion in an isolated heart preparation. Hearts were subjected to 40 min of global ischemia followed by 90 min of reperfusion. During ischemia, propofol (12 microg/mL in saline) was perfused through the aorta at 60 microL/min. We found that application of high-concentration propofol during ischemia combined with low-concentration propofol (1.2 microg/mL) administered before ischemia and during reperfusion significantly improved postischemic myocardial functional recovery without depressing cardiac mechanics before ischemia, as is seen when high-concentration propofol was applied prior to ischemia and during reperfusion. The functional enhancement is associated with increased heart tissue antioxidant capacity and reduced lipid peroxidation. We conclude that high-concentration propofol application during ischemia could be a potential therapeutic and anesthetic strategy for patients with preexisting myocardial dysfunction.
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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".