Anti-CD200R2, Anti-IL-9, Anti-IL-35, or Anti-TGF-β Abolishes Increased Graft Survival and Treg Induction Induced in Cromolyn-Treated CD200R1KO.CD200tg Mice
Bibliographic record
Abstract
BACKGROUND: Rejection is associated with early degranulation (≥80%) of graft-infiltrating CD200R1 receptor-positive mast cells (MCs). Survival is increased, and MC degranulation is decreased, in CD200 mice but not in CD200R1KO mice. CD200 engagement of CD200R2 (not present on MCs) alters dendritic cell differentiation and enhances induction of Foxp3 regulatory T cells (Tregs). We investigated whether attenuation of MC degranulation by sodium cromoglycate allowed CD200 to increase survival in CD200R1KO mice. METHODS: C57BL/6 control, CD200R1KO, CD200, or CD200R1KO.CD200 mice received BALB/c grafts with or without treatment with cromoglycate. Survival was monitored daily from day 10, with mixed lymphocyte culture responses measured on day 14 or 21 and graft immunohistology performed on day 14. RESULTS: Decreased MC degranulation and increased graft Foxp3 Treg infiltration/survival occurred in CD200 mice and in CD200-treated control mice or CD200R1KO.CD200 mice receiving cromoglycate. Neutralizing anti-CD200 or anti-CD200R1/R2 monoclonal antibody caused graft rejection, as did anti-interleukin (IL)-9, anti-IL-35, or anti-transforming growth factor-β antibodies, with the latter also decreasing graft-infiltrating Tregs. CONCLUSION: These data imply a coordinated effect of MCs and Tregs on increased graft survival induced by CD200, with a critical role for IL-9, IL-35, and transforming growth factor-β in the development/function of Tregs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".