Cyclooxygenase Inhibition in Ventilator-Induced Lung Injury
Bibliographic record
Abstract
BACKGROUND: We tested the hypothesis that inhibition of cyclooxygenase (COX) attenuates in vivo ventilator-induced lung injury (VILI) in a prospective, randomized laboratory investigation in a university-affiliated laboratory. Adult male rats were anesthetized and randomized with or without nonselective COX inhibition (ibuprofen) and were subjected to injurious mechanical ventilation (positive end-expiratory pressure = 0; peak inspiratory pressure = 21 mm Hg). METHODS: We investigated the profile of VILI (respiratory mechanics, cytokines, eicosanoids), expression of COX enzymes, and activation of nuclear factor (NF)-κB in ibuprofen- versus vehicle-treated animals. Injurious ventilation caused lung injury (i.e., decrement in compliance, tissue edema, and elevated inflammatory cytokines, eicosanoids, and COX-2). RESULTS: Pretreatment with ibuprofen that effectively inhibited eicosanoid synthesis and COX-2 activity increased survival and attenuated lung edema and decrement in respiratory mechanics. Ibuprofen had no modulatory effect on ventilator-induced activation of NF-κB or inflammatory cytokines (tumor necrosis factor-α, interleukin [IL]-1β, IL-6, GRO/KC [growth-related oncogene/keratinocyte chemoattractant]). COX activity seems important in the pathogenesis of VILI in the in vivo rat. Inhibition of COX provides significant protection (i.e., survival, pulmonary function) in VILI, but without affecting levels of important mediators (tumor necrosis factor-α, IL-1β, IL-6, GRO/KC) or activation of NF-κB. CONCLUSIONS: These data confirm that nonselective COX inhibition provides partial protection against VILI and that the NF-κB signaling pathway is not exclusively eicosanoid dependent. Studies of COX inhibition in ventilator-associated lung injury might benefit from multimodal targeting that includes a comprehensive focus on inflammatory cytokines and NF-κB.
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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 | 0.001 |
| 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".