Non‐myeloablative mixed chimerism approaches and tolerance, a split decision
Bibliographic record
Abstract
Stable mixed chimerism has been considered the most robust tolerance strategy. However, rejection of solid donor tissues by chimeras has been observed, a state termed split tolerance. Since new non-myeloablative mixed chimerism approaches are being actively pursued, we sought to determine whether they lead to full tolerance or split tolerance and to define the mechanisms involved. Fully mismatched mixed chimeras generated by induction with various lymphocyte-depleting antibodies along with either low-dose irradiation or busulfan and temporary sirolimus, maintained stable mixed chimerism but nevertheless rejected donor skin grafts. Generation of stable mixed chimerism using antibody targeting CD40L, but not depleting antibodies to CD4 and CD8, could prevent split tolerance when skin grafts were given together with donor bone marrow. Minor antigen matching abrogated the ability of effector T cells to reject donor skin grafts. A CFSE killing assay indicated that chimeras were both directly and indirectly tolerant of donor hematopoietic cell antigens, suggesting that minor mismatches triggered a tissue-specific response. Thus, split tolerance due to tissue-restricted polymorphic antigens prevents full tolerance in a number of non-myeloablative mixed chimerism protocols and a 'tolerizing' agent is required to overcome split tolerance. A model of the requirements for split tolerance is presented.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".