Tissue Antioxidant Capacity During Anesthesia: Propofol Enhances In Vivo Red Cell and Tissue Antioxidant Capacity in a Rat Model
Bibliographic record
Abstract
UNLABELLED: The effects of anesthesia on ischemia-reperfusion injury are of considerable scientific and clinical interest. We examined the effects of propofol (known to possess antioxidant activity) and halothane (devoid of antioxidant activity in vitro) on tissue and red blood cell (RBC) antioxidant capacity. Adult male Wistar rats were anesthetized with halothane 0.5%-1.0% (n = 7), propofol 500 microg x kg(-1) x min(-1) with halothane 0.25%-0.5% (small-dose propofol; n = 9), or propofol 2000 microg x kg(-1) x min(-1) (large-dose propofol; n = 8) for 45 min. Blood and tissue samples of liver, kidney, heart, and lung were then harvested for in vitro exposure to a peroxidizing agent. Red cell malondialdehyde and tissue thiobarbituric acid reactive substances were determined spectrophotometrically. Antioxidant capacities of blood and tissues in the Large-Dose Propofol group, and of blood and all tissues except lung in the Small-Dose Propofol group, were increased significantly compared with halothane (P < 0.003). The increases in tissue antioxidant capacities varied in their magnitude: RBC > liver > kidney > heart > lung. There was a high correlation between changes in RBC susceptibility to oxidative damage and corresponding changes in tissues. These findings demonstrate that large-dose propofol significantly enhances tissue antioxidant capacity, and RBC antioxidant capacity can serve as a functional measure of tissue activity, in vivo. IMPLICATIONS: We designed this study to investigate the antioxidant effects of propofol in various tissues in a rat model. Pretreatment of animals with propofol led to a reduction in the susceptibility to an in vitro oxidative stress of five different tissues investigated, demonstrating the drug's ability to limit oxidative injury. This may have future application in limiting organ dysfunction after periods of tissue ischemia (which results in oxidative damage).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".