Interleukin-9 Upregulates Mucus Expression in the Airways
Bibliographic record
Abstract
Interleukin (IL)-9 has recently been shown to play an important role in allergic disease because its expression is strongly associated with the degree of airway responsiveness and the asthmatic-like phenotype. IL-9 is a pleiotropic cytokine that is active on many cell types involved in the allergic immune response. Mucus hypersecretion is a clinical feature of chronic airway diseases; however, the mechanisms underlying the induction of mucin are poorly understood. In this report, we show that IL-9 regulates the expression of a subset of mucin genes in lung cells both in vivo and in vitro. In vivo, the constitutive expression of IL-9 in transgenic mice results in elevated MUC2 and MUC5AC gene expression in airway epithelial cells and periodic acid-Schiff-positive staining (reflecting mucous glycogenates). Similar results were observed in C57BL/6J mice after IL-9 intratracheal instillation. In contrast, instillation of the T helper 1-associated cytokine interferon gamma failed to induce mucin production. In vitro, our studies showed that IL-9 also induces expression of MUC2 and MUC5AC in human primary lung cultures and in the human muccoepidermoid NCI-H292 cell line, indicating a direct effect of IL-9 on inducing mucin expression in these cells. Altogether, these results suggest that upregulation of mucin by IL-9 might contribute to the pathogenesis of human inflammatory airway disorders, such as asthma. These data extend the role of the biologic processes that IL-9 has on regulating the many clinical features of asthma and further supports the IL-9 pathway as a key mediator of the asthmatic response.
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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".