Targeting IL6-Edn1-FoxO1 axis enables lung growth in mechanically ventilated newborn mice
Bibliographic record
Abstract
Rationale Mechanical ventilation is a life-saving treatment for preterm infants that often leads to bronchopulmonary dysplasia (BPD). We previously demonstrated a reduced number of alveolar epithelial cells with a depletion of alveolar epithelial type 2 cells (AT2) in lungs of infants with BPD. Objective To investigate and target the mechanisms by which mechanical ventilation causes an arrest of alveolarisation. Methods Experimental mouse model of neonatal ventilation-induced lung injury (VILI) in wild-type mice, Il6 -null mice, and pharmacological inhibition of interleukin (IL)-6 and endothelin receptors. Complementary, precision-cut lung slices (PCLS) and primary cells were analysed. Moreover, lungs of infants with BPD were studied. Results Mechanical ventilation leads to an AT2 depletion and arrest of alveolar growth. Transcriptomic profiling, measurement of gene and protein expression, immunofluorescent staining as well as cell culture studies identified an IL-6-mediated expression of Endothelin-1 (Edn1) and a nuclear sequestration of the antiproliferative transcription factor FoxO1 in AT2. These findings were confirmed using murine PCLS, lung epithelial cells and transgenic mice with inducible constitutive active FoxO1. In vivo , Il6 -null mice and pharmacological inhibition of IL-6 or endothelin A and B receptors prevented nuclear sequestration of FoxO1, thereby enabling lung growth of newborn mice exposed to mechanical ventilation. Conclusion Mechanical ventilation causes an arrest of alveolarisation in newborn mice through an IL-6-mediated activation of Edn1 signalling and nuclear sequestration of FoxO1 in AT2. Thus, this study provides rationale for considering pharmacological inhibition of IL-6 and/or endothelin receptors as a therapeutic strategy for preterm newborns at risk of VILI-associated lung growth arrest.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".