Induction of Tolerance across Fully Mismatched Barriers by a Nonmyeloablative Treatment excluding Antibodies or Irradiation Use
Bibliographic record
Abstract
A mixed-chimerism approach is a major goal to circumvent sustained immunosuppression, but most of the proposed protocols need antibody treatment or host irradiation. Another promising experience involves busulfan combined with cyclophosphamide treatment. Additionally, recent publications demonstrated that, differing from busulfan, treosulfan administration does not present severe organ or hemato toxicities. Currently, Duchenne muscular dystrophy (DMD) patients are treated with chronic immunosuppression for muscle precursor cell transplantation (MT). We have developed a safe tolerance approach within this cellular allotransplantation therapy background. Thus, we have conditioned, prior to a donor BALB/c MT, the dystrophic mouse model C57Bl10J mdx/mdx, with our treatment based on a donor-specific transfusion, then a treosulfan treatment combined with single cyclophosphamide dose, and finally a donor bone marrow transplantation (TTCB). A first MT was performed in all mixed chimeric mice resulting from the TTCB treatment in the left tibialis anterior (TA) muscles. A second MT from the same donor strain was performed 100 days later in the right TA without any additional therapy. Results show that all treated mice developed permanent mixed chimerism. Long-lasting donor-positive fibers were present in both TAs of the mice, which received MT after the TTCB treatment. Only a basal level of infiltration was observed around donor fibers and mixed chimeric mice rejected third-party haplotype skin grafts. Thus, mixed chimerism development with this TTCB conditioning regimen promotes donor-specific stable tolerance, avoiding costimulatory blockade antibodies or irradiation use and side effects of sustained immunosuppressive treatments. This protocol could be eventually applied for MT to DMD patients or others tissue transplantations.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".