THE EFFECTS OF HYPEROXIA EXPOSURE ON LUNG FUNCTION AND PULMONARY SURFACTANT IN A RAT MODEL OF ACUTE LUNG INJURY
Bibliographic record
Abstract
The objective of this study was to determine if prolonged hyperoxia exposure would deplete antioxidants, resulting in excessive oxidative stress that would lead to oxidation of pulmonary surfactant and contribute to lung dysfunction. Rats were exposed to either hyperoxic (> 95% O(2)) or normoxic (21% O(2)) oxygen concentrations for 48 or 60 hours. Pulmonary compliance, inflammatory cells, and total protein levels were measured as indicators of lung injury. Bronchoalveolar lavage (BAL) samples were analyzed for surfactant composition, antioxidant content, and markers of oxidative stress. Antioxidants were also measured in lung tissue and plasma samples. Hyperoxia exposure for 60 hours resulted in increased protein and inflammatory cells in BAL, and lower pulmonary compliance, compared to all other groups. Total surfactant and surfactant large aggregates were increased following 48 hours of hyperoxia exposure, with a further increase following 60 hours. Animals exposed to 60 hours of hyperoxia also demonstrated lower ascorbate levels in lung tissue, increased lipid peroxides in BAL, and increased oxidation of phosphatidylglycerol species in surfactant. This study demonstrates that the balance of oxidant/antioxidant components is disrupted within the lung during periods of hyperoxia, and that although surfactant lipids may be susceptible to oxidative damage, they do not likely represent a major mechanism for the lung dysfunction observed.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".