IL6 - ET1 signaling inhibits alveolar growth through FoxO1-dependent AT2 survival in mechanically ventilated newborn mice
Bibliographic record
Abstract
Rational: Preterm infants with mechanical ventilation (MV) often evolve bronchopulmonary dysplasia (BPD), a neonatal chronic lung disease. Our group previously showed that lung inflammation of infants with BPD leads to a loss of alveolar epithelial type 2 (AT2) cells and thus of the alveolar epithelium. We now aimed to decipher the molecular mechanisms underlying MV-induced arrest of alveolar growth and to test new therapeutic strategies. Methods: (i) Five-day-old mice underwent MV for 8h: wildtype (WT), IL6-/-, and WT with anti IL6 antibody or endothelin-1 receptor inhibitors (ET-1R). (ii) Cell culture: pulmonary microvascular endothelial cells (PMVEC), MLE12, primary AT2 from WT and FoxO1ADA mice with constitutive active FoxO1. Results: (i) Transcriptomic profiling, gene expression and protein analyses of lungs after MV revealed activation of IL6-STAT3 signaling and increased Edn1 expression, which was associated with nuclear translocation of the anti-proliferative FoxO1 in AT2. IL6-/- and pharmacologic inhibition of IL6 and ET1-R protected against nuclear trapping of pFoxO1, loss of AT2, and arrest of alveolar formation after MV. (ii) Cell culture studies: cyclic elongation and ET1 increase Il6 mRNA in MLE-12; in contrast, IL-6 induces End1 in PMVEC and MLE-12. Moreover, IL6 reduces cell survival via nuclear pFoxO1. FoxO1 knockdown improved MLE-12 survival, whereas FoxO1 overexpression reversed this effect. Finally, AT2 from FoxO1ADA mice showed reduced survival. Conclusion: Pharmacologic inhibition of IL6 and ET-1R prevents FoxO1-mediated loss of AT2 after MV and thereby opens promising therapeutic avenues for preterm infants requiring MV and at risk for BPD.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".