Cytochrome p450 2C Contributes to Peri‐Transplant Ischemic Injury and Cardiac Allograft Vasculopathy Following Heterotopic Heart Transplantation in Rats
Bibliographic record
Abstract
Peritransplant ischemia and reperfusion (I/R) injury contributes to post‐transplant vascular dysfunction and cardiac allograft vasculopathy (CAV). We have shown that cytochrome p450 (CYP) 2C inhibition significantly reduces I/R‐induced myocardial infarction and post‐ischemic vascular dysfunction. The objective of this study was to assess the contribution of CYP2C to CAV. Rat heterotopic heart transplants were performed between Lewis donors and Fisher recipients. Rats received CYP2C inhibition by sulfaphenazole (SP) or vehicle control 1hr prior to surgery. Organs were harvested 4, 7 and 30 days post‐transplant. Luminal narrowing was measured using morphometric analysis and immune infiltration was scored from absent to severe in a blinded manner. Smooth muscle cell (SMC) proliferation and apoptotic cells were detected by Ki‐67 and TUNEL staining, respectively. SP did not affect post‐transplant morbidity, mortality or weight gain. Coronary blood vessels from rats treated with SP showed significantly reduced luminal narrowing compared to control (12.07±4.09% vs 66.21±13.61%, p<0.05) and demonstrated a reduced SMC proliferation (3.32±3.27% vs. 7.20±2.32%). SP did not alter immune infiltration (p>0.1) nor did it significantly alter TUNEL positivity in myocardial, endothelial or SMC populations. In conclusion, CYP2C contributes to SMC proliferation CAV without affecting general immune infiltration.
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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 | 0.001 | 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".