Reversal of peanut anaphylaxis by retinoic acid-differentiated dendritic cell immunotherapy. IL-27-dependent induction of Foxp3- non-Tr1 regulatory T cells (VAC4P.1100)
Bibliographic record
Abstract
Abstract Background. Semi-mature IL-10-induced DC (DC10) induce human or mouse effector Th2 cells (Teff) to differentiate into Foxp3+ Treg and thereby induce asthma tolerance. Retinoic acid (RA) and TGFβ-induced gut DC similarly induce tolerance to gut contents via Foxp3+ Treg, while immature hDC-10 induce IL-10-dependent Foxp3- Tr1 cells. Methods. We assessed the abilities of mature RA-induced DC to reverse anaphylaxis sensitivity, characterizing LPS-matured DC-RA and their tolerogenic activities in mouse models of OVA and peanut systemic anaphylaxis. Results. Mature DC-RA strongly expressed CD103 (αE integrin), MHCII, co-stimulatory markers, PDL1 & -L2, ICOSL, TGFβ, IL-27 and the RA-metabolizing enzyme Aldh1A2. They induced Th2 cells to convert into CD25+LAG3+CD49b-IL-10-Foxp3- Treg in an IL-10-independent, IL-27-dependent fashion, although IL-27 was dispensable for Th2 suppression by DC-RA. Wild-type, but not IL-27-/- DC-RA therapy reversed systemic anaphylaxis, including clinical scores, diarrhea, mast cell activation and Th2 responses, and lowered serum allergen-specific IgE and IgG1 levels. Conclusions. Allergen-presenting DC-RA induce food allergen tolerance by activating CD25+Foxp3-, non-Tr1 responses in an IL-27-dependent fashion. This data indicates that, like DC10, DC-RA can also be used for allergic disease immunotherapy, but that these two populations of DCreg induce distinct Treg responses, and this potentially provides us with important options DCreg immunotherapy
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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".