Congenic hematopoietic stem cell transplantation promotes survival of heart allografts in murine models of acute and chronic rejection
Bibliographic record
Abstract
The ability to induce tolerance would be a major advance in the field of solid organ transplantation. Here, we investigated whether autologous (congenic) hematopoietic stem cell transplantation (HSCT) could promote tolerance to heart allografts in mice. In an acute rejection model, fully MHC-mismatched BALB/c hearts were heterotopically transplanted into C57BL/6 (CD45.2) mice. One week later, recipient mice were lethally irradiated and reconstituted with congenic B6 CD45.1 Lin-Sca1+ckit+ cells. Recipient mice received a 14-day course of rapamycin both to prevent rejection and to expand regulatory T cells (Tregs). Heart allografts in both untreated and rapamycin-treated recipients that did not undergo HSCT were rejected within 33 days (median survival time = 8 days for untreated recipients, median survival time = 32 days for rapamycin-treated recipients), whereas allografts in HSCT-treated recipients had a median survival time of 55 days (P < 0.001 vs. both untreated and rapamycin-treated recipients). Enhanced allograft survival following HSCT was associated with increased intragraft Foxp3+ Tregs, reduced intragraft B cells, and reduced serum donor-specific antibodies. In a chronic rejection model, Bm12 hearts were transplanted into C57BL/6 (CD45.2) mice, and congenic HSCT was performed two weeks following heart transplantation. HSCT led to enhanced survival of allografts (median survival time = 70 days vs. median survival time = 28 days in untreated recipients, P < 0.01). Increased allograft survival post-HSCT was associated with prevention of autoantibody development and absence of vasculopathy. These data support the concept that autologous HSCT can promote immune tolerance in the setting of allotransplantation. Further studies to optimize HSCT protocols should be performed before this procedure is adopted clinically.
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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".