IL-23 induced in keratinocytes by endogenous TLR4 ligands polarizes dendritic cells to drive IL-22 responses to skin immunization
Bibliographic record
Abstract
Atopic dermatitis (AD) is a Th2-dominated inflammatory skin disease characterized by epidermal thickening. Serum levels of IL-22, a cytokine known to induce keratinocyte proliferation, are elevated in AD, and Th22 cells infiltrate AD skin lesions. We show that application of antigen to mouse skin subjected to tape stripping, a surrogate for scratching, induces an IL-22 response that drives epidermal hyperplasia and keratinocyte proliferation in a mouse model of skin inflammation that shares many features of AD. DC-derived IL-23 is known to act on CD4(+) T cells to induce IL-22 production. However, the mechanisms that drive IL-23 production by skin DCs in response to cutaneous sensitization are not well understood. We demonstrate that IL-23 released by keratinocytes in response to endogenous TLR4 ligands causes skin DCs, which selectively express IL-23R, to up-regulate their endogenous IL-23 production and drive an IL-22 response in naive CD4(+) T cells that mediates epidermal thickening. We also show that IL-23 is released in human skin after scratching and polarizes human skin DCs to drive an IL-22 response, supporting the utility of IL-23 and IL-22 blockade in AD.
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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) | 0.002 | 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".