ILC2 activation by keratinocyte-derived IL-25 drives IL-13 production at sites of allergic skin inflammation
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis skin lesions demonstrate increased expression of IL-25 by keratinocytes and increased numbers of type 2 innate lymphoid cells (ILC2s) that express high levels of IL-25 receptor (IL-25R). IL-13 is expressed in atopic dermatitis skin lesions and plays an important role in pathogenesis of the disease. OBJECTIVE: Our aim was to determine the role of IL-25 and ILC2s in a mouse model of antigen-driven allergic skin inflammation. METHODS: Wild-type mice; mice that express an Il13-driven enhanced green fluorescent protein; and mice that lack IL-25R, IL-25 in keratinocytes, or IL-13 or IL-25R in ILC2s were subjected to acute or chronic epicutaneous sensitization with ovalbumin. Sensitized skin was examined by histology for epidermal thickening. Cellular infiltrates were analyzed for surface markers and intracellular expression of enhanced green fluorescent protein by flow cytometry. Gene expression was quantitated by RT quantitative PCR. RESULT: 2-cell-attracting chemokines Cc17 and Ccl22. ILCs are the major source of IL-13 in acutely sensitized mouse skin, whereas T cells are its major source in chronically sensitized mouse skin. CONCLUSION: ILC2 activation by IL-25 is essential for IL-13 expression at sites of allergic skin inflammation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".