TGF-β, Eosinophils and IL-13 in Allergic Airway Remodeling: A Critical Appraisal with Therapeutic Considerations
Bibliographic record
Abstract
Airway remodeling is a characteristic feature of allergic asthma that is now thought to contribute to airway dysfunction and, ultimately, to clinical symptoms. A prevalent hypothesis holds that eosinophil-derived transforming growth factor-beta (TGF-beta) is a predominant underlying mechanism driving the development of remodeling and thus, represent promising targets for therapeutic intervention. This notion is supported by in vivo evidence from loss of function experiments conducted in animal models employing the surrogate allergen ovalbumin (OVA), and by indirect evidence from studies in human asthmatics. However, it is important to note that various studies in OVA systems have reported disconnects between eosinophils, TGF-beta and allergic remodeling. Moreover, recent investigations in a mouse model induced by respiratory exposure to a house dust mite extract have shown that remodeling can develop independently of TGF-beta. These findings challenge the above hypothesis and suggest that the mechanisms governing remodeling may be context specific. In addition to TGF-beta and eosinophils, several other factors have been implicated in the development of airway remodeling. Among these, interleukin (IL)-13 may be of particular importance given its role in type-2 immunity and in the tissue repair/fibrotic response. This review will appraise the evidence pertaining to the roles of TGF-beta, eosinophils and IL-13 in allergic remodeling, and will suggest that identifying robust targets for therapeutic intervention might benefit from a reconsideration of our approach to understanding remodeling.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".