A role for CD47 in the development of experimental colitis mediated by SIRPα+CD103− dendritic cells
Bibliographic record
Abstract
Mesenteric lymph node (mLN) CD103 (alphaE integrin)(+) dendritic cells (DCs) induce regulatory T cells and gut tolerance. However, the function of intestinal CD103(-) DCs remains to be clarified. CD47 is the ligand of signal regulatory protein alpha (SIRPalpha) and promotes SIRPalpha(+) myeloid cell migration. We first show that mucosal CD103(-) DCs selectively express SIRPalpha and that their frequency was augmented in the lamina propria and mLNs of mice that developed Th17-biased colitis in response to trinitrobenzene sulfonic acid. In contrast, the percentage of SIRPalpha(+)CD103(-) DCs and Th17 responses were decreased in CD47-deficient (CD47 knockout [KO]) mice, which remained protected from colitis. We next demonstrate that transferring wild-type (WT), but not CD47 KO, SIRPalpha(+)CD103(-) DCs in CD47 KO mice elicited severe Th17-associated wasting disease. CD47 expression was required on the SIRPalpha(+)CD103(-) DCs for efficient trafficking to mLNs in vivo, whereas it was dispensable on both DCs and T cells for Th17 polarization in vitro. Finally, administration of a CD47-Fc molecule resulted in reduced SIRPalpha(+)CD103(-) DC-mediated Th17 responses and the protection of WT mice from colitis. We thus propose SIRPalpha(+)CD103(-) DCs as a pathogenic DC subset that drives Th17-biased responses and colitis, and the CD47-SIRPalpha axis as a potential therapeutic target for inflammatory bowel disease.
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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".