Chronic Hypoxia in an EXTrauterine Environment for Neonatal Development Impairs Lung Development
Bibliographic record
Abstract
Severe fetal hypoxia poses a significant risk to lung development, resulting in severe postnatal complications. Existing chronic hypoxia animal models lack the ability to achieve pathologically reduced fetal oxygen without compromising animal development, placental blood flow, or maternal health. Using an established model of isolated chronic hypoxia involving the Extrauterine Environment for Neonatal Development, we are able to investigate the direct impact of fetal hypoxia on lung development. Oxygen delivery to preterm fetal lambs (105-110 d gestational age) delivered by cesarean section was reduced, and animals were supported using the Extrauterine Environment for Neonatal Development through the canalicular or saccular stage of lung development. Fetal lambs in hypoxic conditions showed significant growth restriction compared with their normoxic counterparts. We also observed modest aberrant vascular remodeling in the saccular group after hypoxic conditions, with decreased macrovessel numbers and microvascular endothelial cell numbers and increased peripheral vessel muscularization. In addition, fetal hypoxia resulted in enlarged distal airspaces and decreased septal wall volume. Moreover, there was a reduction in mature SFTPB (surfactant protein B) and processed SFTPC protein expression concomitant with a decrease in alveolar type 2 cell number. These findings demonstrate that maternally independent fetal hypoxia predominantly affects distal airway development, alveolar type 2 cell number, and surfactant production, with mild effects on the vasculature.
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) | 0.001 | 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".