Reduced transforming growth factor β1 (TGF‐β1) in the repair of airway epithelial cells of children with asthma
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Evidence into the role of TGF-β1 in airway epithelial repair in asthma is still controversial. This study tested the hypothesis that the reduced TGF-β1 levels previously observed in paediatric asthmatic airway epithelial cells directly contribute to the dysregulated repair seen in these cells. METHODS: Primary airway epithelial cells (pAEC) from children with asthma (n = 16) and non-asthmatic subjects (n = 20) were isolated, and subcultured for investigation of TGF-β1 gene and protein via quantitative polymerase chain reaction (qPCR) and enzyme-linked immunosorbent assay (ELISA), respectively. Expression of other associated genes such as integrins αvβ6, αvβ8 and MT1-MMP were also tested. Small interfering RNA (siRNA) was employed to assess the role of TGF-β1 during wound repair. RESULTS: TGF-β1 gene and protein expression were significantly downregulated in asthmatic pAEC over the course of repair, compared with cells from non-asthmatic children. Messenger RNA (mRNA) expression of TGF-β1 was also directly implicated in non-asthmatic and asthmatic pAEC proliferation over their quiescent counterparts. Small interfering RNA-mediated knockdown of TGF-β1 compromised repair in non-asthmatic pAEC and exacerbated the dysregulated repair seen in asthmatic pAEC. Expression of major TGF-β1 activators of epithelial cells, integrin αvβ6 and αvβ8 was also measured and there was no difference in αvβ6 gene expression between the two cohorts. Although integrin αvβ8 gene expression was significantly higher in asthmatic pAEC, the expression of MT1-MMP (MMP14) which facilitates the αvβ8 mediated TGF-β1 activation was significantly downregulated. CONCLUSION: Our data has highlighted the importance of TGF-β1 in pAEC wound repair in vitro. The significantly lower levels seen in asthmatic pAEC subsequently contributes to the dysregulated repair observed in these cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".