Imaging Tolerance Induction in Neonatal Mice: Hierarchical Interplay Between Allogeneic Adult and Neonatal Immune Cells
Bibliographic record
Abstract
BACKGROUND: In Medawar's murine neonatal tolerance model, injection of adult semiallogeneic lymphohematopoietic cells (spleen cells [SC] and bone marrow cells [BMC]) tolerizes the neonatal immune system. An eventual clinical application would require fully allogeneic (allo) cells, yet little is known about the complex in vivo/in situ interplay between those cells and the nonconditioned neonatal immune system. METHODS: To this end, labeled adult SC and BMC were injected into allogeneic neonates; interactions between donor and host cells were analyzed and modulated by systematic depletion/inactivation of specific donor and host immune effector cell types. RESULTS: Consistent with effector cell compositions, allo-SC and allo-SC/BMC each induced lethal acute graft-versus-host disease, whereas allo-BMC alone did so infrequently. CD8 T cells from SC inoculum appeared naïve, while those of BMC were more memory-like. Age-dependent, cell-type dominance defined the interplay between adult donor cells and the neonatal host immune system such that if the dominant adult effector type was removed, then the equivalent neonatal one became dominant. Depletion of donor/host peripheral T cells protected against acute graft-versus-host disease and prolonged heart allograft survival; peripheral CD8 T-cell depletion together with CD4 T cell-costimulation blockade induced more robust tolerance. CONCLUSIONS: This comprehensive study provides direct observation of the cellular interplay between allogeneic donor and host immune systems, adds to our previous work with semiallogeneic donor cells, and provides important insights for robust tolerance induction. Induction of transplant tolerance in neonates will likely require "crowd sourcing" of multiple tolerizing cell types and involve depletion of immune effector cells with costimulation blockade.
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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 | 0.000 |
| 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".