Simultaneous administration of a low‐dose mixture of donor bone marrow cells and splenocytes plus adenovirus containing the CTLA4Ig gene result in stable mixed chimerism and long‐term survival of cardiac allograft in rats
Bibliographic record
Abstract
T-cell costimulatory blockade combined with donor bone marrow transfusion may induce mixed chimerism, rendering robust tolerance in transplanted organs and cells. However, most protocols entail high doses of donor bone marrow cells (BMCs) or repeated administration of costly agents that block costimulatory pathways, thus delaying clinical development. To circumvent these shortcomings, we developed a strategy in which the dosage of donor BMCs was reduced but compensated by donor splenocytes (SPLCs). Furthermore, repeated administration of costly agents was replaced with a single injection of adenovirus expressing a gene of interest. In rat cardiac transplantation models, cardiac allografts from DA (RT-1a) rats were transplanted heterotopically into the abdomen of LEW (RT-11) recipient rats. Immediately after cardiac transplantation, an adenovirus vector (AdCTLA4Ig; 5 x 10(9) plaque-forming units) containing the gene for CTLA4Ig was administered to recipients (n = 6) simultaneously with a low dose of donor BMCs (1 x 10(8)/rat) and SPLCs (5 x 10(7)/rat) via the portal vein. The treated LEW recipient rats developed long-lasting mixed chimerism (>10% at >100 days) and exhibited long-term cardiac allografts (mean survival time of > 200 days) compared with control recipients. Moreover, recipients displaying long-lasting mixed chimerism accepted subsequent donor skin allografts while promptly rejecting third-party skin allografts. These results suggest that blockade of the CD28-B7 pathway, using adenovirus-mediated CTLA4Ig gene transfer, in concert with a low dosage of donor BMCs and SPLCs, may represent a feasible strategy to induce stable mixed chimerism and permit long-term survival of cardiac allografts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 teacher head, 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".