Hypoxia-Inducible Factor-1 Stimulates Postnatal Lung Development but Does Not Prevent O2-Induced Alveolar Injury
Bibliographic record
Abstract
This study investigated whether hypoxia-inducible factor (HIF)-1 influences postnatal vascularization and alveologenesis in mice and whether stable (constitutive-active) HIF could prevent hyperoxia-induced lung injury. We assessed postnatal vessel and alveolar formation in transgenic mice, expressing a stable, constitutive-active, HIF1α-subunit (HIF-1αΔODD) in the distal lung epithelium. In addition, we compared lung function, histology, and morphometry of neonatal transgenic and wild-type mice subjected to hyperoxia. We found that postnatal lungs of HIF-1αΔODD mice had a greater peripheral vessel density and displayed advanced alveolarization compared with control lungs. Stable HIF-1α expression was associated with increased postnatal expression of angiogenic factors, including vascular endothelial growth factor, angiopoietins 1 and 2, Tie2, and Ephrin B2 and B4. Hyperoxia-exposed neonatal HIF-1αΔODD mice exhibited worse lung function but had similar histological and surfactant abnormalities compared with hyperoxia-exposed wild-type controls. In conclusion, expression of constitutive-active HIF-1α in the lung epithelium was associated with increased postnatal vessel growth via up-regulation of angiogenic factors. The increase in postnatal vasculature was accompanied by enhanced alveolar formation. However, stable HIF-1α expression in the distal lung did not prevent hyperoxia-induced lung injury in neonates but instead worsened lung function.
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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 | 0.000 |
| 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) | 0.001 | 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 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".