Development of Atopic Dermatitis-Like Skin Lesions in STAT6-Deficient NC/Nga Mice
Bibliographic record
Abstract
Atopic dermatitis (AD) is a pruritic inflammatory skin disease characterized by elevation of plasma levels of total IgE, infiltration of mast cells and eosinophils, and the expression of cytokines by Th2 T cells. However, the role of Th2 cells in the pathogenesis of AD is not fully understood. In this study we examined the NC/Nga (NC) mouse model of AD and established STAT6-deficient (SATA6(-/-)) NC mice to investigate the relevance of IL-4-mediated immune responses. Surprisingly, these mice elicited AD-like skin lesions at equivalent frequency and time of onset compared with normal NC littermates. Histological features of the lesion in STAT6(-/-) NC mice fulfilled the criteria for the pathogenesis of AD, although these mice fail to produce IgE and Th2 cytokines. The lymph nodes proximal to the regions of skin that developed lesions exhibited massive enlargement elicited by the accumulation of activated IFN-gamma-secreting T cells. Moreover, caspase I, IL-18, IL-12, and IFN-gamma are found to be highly expressed at the skin lesion, occurring simultaneously with elevation of eotaxin 2 and CCR3 expression. Therefore, the Th2-mediated immune response is not necessary for the development of AD-like skin disease in NC mice. The skin microenvironment that favored IFN-gamma production tightly correlates with the skin disease in NC mice through the infiltration of eosinophils.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".