New Evidence for a Role of Allograft Accommodation in Long-Term Tolerance
Bibliographic record
Abstract
BACKGROUND: Progressively better therapies have largely prevented or at least effectively treated acute allograft rejection. Consequently, the long-term survival of solid organ transplants has increasingly become limited primarily by the development of chronic allograft rejection. The mechanisms of chronic rejection remain largely unknown and the induction of specific tolerance would be the ultimate achievement in transplant immunology. We previously demonstrated, in a fully major histocompatibility complex (MHC)-mismatched rat cardiac allograft combination, that a 20-day treatment with a deoxyspergualin (DSG) analogue, LF15-0195, induces allograft tolerance with the development of potent CD4CD25 regulatory T cells. In order to better characterize the mechanisms involved in allograft tolerance, we compared long-term tolerated allografts with allografts exhibiting signs of chronic rejection induced by donor-specific blood transfusion. METHODS: We analyzed both types of allografts for infiltration, alloantibody production and gene expression by histology, exhaustive microarray and quantitative reverse-transcriptase polymerase chain reaction. RESULTS: Interestingly, we observed in tolerated allografts an infiltrate as dense as the one observed in chronically rejected allografts and alloantibody deposits on graft endothelial cells. Prominent gene expression of many putative proinflammatory cytokines and genes related to cell activation or cytotoxicity were observed in tolerated allografts. However, we observed a specific upregulation of cytoprotective genes such as nitric oxide synthase, BclXL, and indoleamine 2,3 dioxygenase, and a poor in situ expression of immunoglobulin chain gene. CONCLUSIONS: This study demonstrates a state of accommodation of tolerated allografts and suggests the importance of early control of humoral immunity for the prevention of chronic rejection and the maintenance of long-term tolerance.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".