Synergistic effect of vincristine with tacrolimus or sirolimus in prevention of acute heart allograft rejection in the rat
Bibliographic record
Abstract
The application of multiple immunosuppressive therapy for organ transplantation could enhance therapeutic efficacy, while minimizing the toxicity of individual drugs used in the regimen. In this study, the effect of the combined therapy of vincristine (VCR) with tacrolimus (FK506) or sirolimus (rapamycin, RAPA) was tested in prevention of acute heart allograft rejection in the rat. A Brown Norway (BN, RT 1(n)) to Lewis (LEW, RT 1(1)) rat combination was used in a heart allografting model. VCR was administered intraperitoneally once daily, while FK506 and RAPA were given by gavage once daily for 14 days after transplantation. There were dose-related prolongations of mean survival time (MST) to monotherapy of VCR, FK506, or RAPA. The MST in combination therapy indicated that a synergistic interaction was produced when compared with the respective monotherapies: VCR 0.05 mg/kg/day + FK506 0.5 mg/kg/day (16.00 +/- 1.79 days, P = 0.001; combination index (CI) = 0.557); VCR 0.05 mg/kg/day + FK506 1.0 mg/kg/day (29.00 +/- 10.54 days, P = 0.001; CI = 0.598); VCR 0.05 mg/kg/day + RAPA 0.2 mg/kg/day (17.33 +/- 1.97 days, P = 0.001; CI = 0.500); and VCR 0.05 mg/kg/day + RAPA 0.4 mg/kg/day (21.17 +/- 3.19 days, P = 0.001; CI = 0.838). Combination therapy of VCR and FK506 or RAPA produced synergistic effects in prevention of acute heart allograft rejection in the rat.
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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 | 0.001 | 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".