Mouse and human lung fibroblasts regulate dendritic cell trafficking, airway inflammation, and fibrosis through integrin αvβ8–mediated activation of TGF-β
Bibliographic record
Abstract
The airway is a primary portal of entry for noxious environmental stimuli that can trigger airway remodeling, which contributes significantly to airway obstruction in chronic obstructive pulmonary disease (COPD) and chronic asthma. Important pathologic components of airway remodeling include fibrosis and abnormal innate and adaptive immune responses. The positioning of fibroblasts in interstitial spaces suggests that they could participate in both fibrosis and chemokine regulation of the trafficking of immune cells such as dendritic cells, which are crucial antigen-presenting cells. However, physiological evidence for this dual role for fibroblasts is lacking. Here, in two physiologically relevant models - conditional deletion in mouse fibroblasts of the TGF-β-activating integrin αvβ8 and neutralization of αvβ8 in human COPD fibroblasts - we have elucidated a mechanism whereby lung fibroblast chemokine secretion directs dendritic cell trafficking, in a manner that is critically dependent on αvβ8-mediated activation of TGF-β by fibroblasts. Our data therefore indicate that fibroblasts have a crucial role in regulating both fibrotic and immune responses in the lung.
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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".