Cyclooxygenase‐2 inhibition partially protects against 60% O<sub>2</sub>‐mediated lung injury in neonatal rats
Bibliographic record
Abstract
RATIONALE: Use of the anti-inflammatory agent dexamethasone in premature infants with bronchopulmonary dysplasia has been curtailed, and no alternative anti-inflammatory agents are approved for this use. Our objective was to use a neonatal rat model of bronchopulmonary dysplasia to determine if an highly selective cyclooxygenase-2 inhibitor, 5,5-dimethyl-3-(3-fluorophenyl)4-(4-methylsulfonyl)phenyl-2(5H)-furanone (DFU; 10 µg/g body weight), could prevent inflammatory cell influx and protect against lung injury. METHODS: Neonatal rats exposed to air or 60% O2 for 14 days from birth either received daily i.p. injections of (i) vehicle or DFU or (ii) vehicle or an EP(1) receptor antagonist, SC-19220. RESULTS: DFU attenuated the lung macrophage and neutrophil influx, prevented interstitial thickening and prevented the loss of peripheral blood vessels induced by 60% O2 , but did not protect against the variance in alveolar diameter induced by 60% O2 . Exposure to 60% O2 caused both an increase in lung prostaglandin E2 content and a reduction in lung mesenchymal cell mass which was reversed by DFU. Prostaglandin E2 binding to the EP(1) receptor inhibited DNA synthesis in cultures of lung fibroblasts in a dose dependent fashion. Treatment with SC-19220 attenuated the reduction in lung mesenchymal mass observed following exposure of rat pups to 60% O2 . CONCLUSIONS: An highly selective cyclooxygenase-2 inhibitor is an effective anti-inflammatory substitute for dexamethasone for preventing phagocyte influx into the neonatal lung during 60% O2 -mediated lung injury, and can modify the severity of that injury.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".