Desensitization using imlifidase and EndoS enables chimerism induction in allosensitized recipient mice
Bibliographic record
Abstract
Mixed hematopoietic chimerism induction as a way to foster tolerance to donor organs in recipients who have been sensitized to donor antigens is challenging. Donor-specific antibodies (DSA) are a dominant barrier toward successful donor bone marrow engraftment. Although desensitization methods are routinely used in recipients with allosensitization for allogeneic bone marrow transplantation, engraftment is frequently unsuccessful. To overcome the barrier of prior sensitization we tested enzymatic desensitization of donor-specific IgG using imlifidase and endoglycosidase of Streptococcus pyogenes (EndoS), which both partially block the function of DSA in mice, as a novel approach to improve murine bone marrow engraftment in primed hosts. We found that EndoS was capable of inhibiting antibody-mediated killing of donor cells in vivo. Furthermore, the effect of EndoS depended on the titer of DSA and the genetic background of the recipients. In combination with imlifidase, EndoS improved the survival of donor bone marrow cells. Together with cyclophosphamide, bortezomib, T cell depletion, and nonlethal irradiation, imlifidase in combination with EndoS allowed allogeneic bone marrow engraftment in sensitized recipients. We conclude that enzymatic inactivation of DSA, using the combination of imlifidase and EndoS, can be used for inducing donor hematopoietic chimerism in allosensitized recipient mice in combination with other desensitization strategies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".