Impact of bronchopulmonary dysplasia on brain and retina
Bibliographic record
Abstract
Many premature newborns develop bronchopulmonary dysplasia (BPD), a chronic lung disease resulting from prolonged mechanical ventilation and hyperoxia. BPD survivors typically suffer long-term injuries not only to the lungs, but also to the brain and retina. However, currently it is not clear whether the brain and retinal injuries in these newborns are related only to their prematurity, or also to BPD. We investigated whether the hyperoxia known to cause histologic changes in the lungs similar to BPD in an animal model also causes brain and retinal injuries. Sprague Dawley rat pups were exposed to hyperoxia (95% O2, 'BPD' group) or room air (21% O2, 'control' group) from postnatal day 4-14 (P4-14); the rat pups were housed in room air between P14 and P28. At P28, they were sacrificed, and their lungs, brain, and eyes were extracted. Hematoxylin and eosin staining was performed on lung and brain sections; retinas were stained with Toluidine Blue. Hyperoxia exposure resulted in an increased mean linear intercept in the lungs (P<0.0001). This increase was associated with a decrease in some brain structures [especially the whole-brain surface (P=0.02)], as well as a decrease in the thickness of the retinal layers [especially the total retina (P=0.0008)], compared to the room air control group. In addition, a significant negative relationship was observed between the lung structures and the brain (r=-0.49,P=0.02) and retina (r=-0.70,P=0.0008) structures. In conclusion, hyperoxia exposure impaired lung, brain, and retina structures. More severe lung injuries correlated with more severe brain and retinal injuries. This result suggests that the same animal model of chronic neonatal hyperoxia can be used to simultaneously study lung, brain and retinal injuries related to hyperoxia.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".