Anti-CD3 prevents factor VIII inhibitor development in hemophilia A mice by a regulatory CD4+CD25+-dependent mechanism and by shifting cytokine production to favor a Th1 response
Bibliographic record
Abstract
Non-Fc-receptor binding anti-CD3 Ab therapy, in the setting of several different autoimmune disorders, can induce antigen-specific and long-lasting immunologic tolerance. Because factor VIII (FVIII) inhibitor formation is the most serious treatment-related complication for hemophilia A patients, we tested the efficacy of anti-CD3 to prevent FVIII inhibitor formation in hemophilia A BALB/c and C57BL/6 mice. A short course of low-dose anti-CD3 significantly increased expression of CD25 and the proportion of CD4+CD25+ regulatory T cells in the spleen and potently prevented the production of inhibitory and non-neutralizing anti-FVIII antibodies in both strains of mouse. Depleting the CD4+CD25+ cells during anti-CD3 therapy completely ablated tolerance to FVIII. Further phenotypic characterization of regulatory cells in tolerant mice showed a consistently higher number of CD4+GITR+ and CD4+FoxP3+ cells in both strains of mice. In addition, in tolerant C57BL/6 mice we observed an increase in CD4+CD25+ CTLA-4+ and CD4+CD25+mTGF-beta1+ cells. Finally, in vitro cytokine profiling demonstrated that splenocytes from tolerant BALB/c and C57BL/6 were polarized toward a Th1-immune response. Taken together, these findings indicate that anti-CD3 induces tolerance to FVIII and that the mechanism(s) regulating this response almost certainly occurs through the generation of several distinct regulatory T-cell lineages and by influencing cytokine production and profile.
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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 | 0.000 | 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".