CD40 signaling augments IL-10 expression and the tolerogenicity of IL-10-induced regulatory dendritic cells
Bibliographic record
Abstract
CD40 expressed on stimulatory dendritic cells (DC) provides an important accessory signal for induction of effector T cell responses. It is also expressed at lower levels on regulatory DC (DCreg), but there is little evidence that CD40 signaling contributes to the tolerogenic activity of these cells. Indeed, CD40 silencing within DCreg has been reported to induce T cell tolerance in multiple disease models, suggesting that CD40 is superfluous to DC-induced tolerance. We critically assessed whether CD40 does have a role in tolerance induced by IL-10-differentiated DC (DC10) by using DC10 generating from the bone marrow of wild-type (w.t.) or CD40-/- donor mice, or IL-10-complemented CD40-/- DC10 to treat asthmatic mice. Wild-type DC10 ablated the OVA-asthma phenotype via induction of Foxp3+ Treg responses, but CD40-/- DC10 had no discernible effects on primary facets of the phenotype (e.g., IL-5, IL-9, IL-13 levels, IgE & IgG1 antibodies; p>0.05) and were ≤40% effective in reversal of others. Foxp3+ T cells from the lungs of CD40-/- DC10-treated mice expressed reduced levels of a panel of six Treg-specific activation markers relative to Treg from w.t. DC10-treated mice. Coculture with effector T cells from asthmatic mice induced a marked upregulation of cell surface CD40 on w.t. DC10. While untreated CD40-/- and w.t. DC10 secreted equally low levels of IL-10, stimulation of w.t. DC10 with anti-CD40 for 72 h increased their expression of IL-10 by ≈250%, with no parallel induction of IL-12. Complementing IL-10 expression in CD40-/- DC10 by IL-10 mRNA transfection fully restored the cells' abilities to suppress the asthma phenotype. In summary, CD40 signaling in DC10 contributes importantly to their expression of IL-10 and to a robust induction of tolerance, including activation of induced Treg.
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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 | 0.000 | 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) | 0.002 | 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".