The anti-inflammatory effect of inhaled nitric oxide on pulmonary inflammation in a swine model
Bibliographic record
Abstract
Cardiopulmonary bypass (CPB) is associated with an inflammatory process that leads to lung injury. In this study, we hypothesized that inhaled nitric oxide (INO) possesses the ability to modulate CPB-induced inflammation. Fifteen male pigs were randomly divided into 3 groups: Sham, CPB+LPS (CPB and lipopolysaccharide), and CPB+LPS+INO. INO (20 parts per million) was administered for 24 h after anesthesia. CPB was performed for 90 min, and LPS was infused (1 microg/kg) after CPB. Bronchoalveolar lavage (BAL) fluid and blood were collected at T0 (before CPB), at 4 h, and at 24 h. At 24 h, BAL interleukin-8 (IL-8) levels were not increased as expected in the CPB+LPS group compared with the Sham group, but they were reduced significantly in the CPB+LPS+INO group. Cell hypo reactivity observed in the groups receiving LPS also seemed to downregulate endothelial nitric oxide synthase NOS protein expression relative to the Sham group. Nitrite and nitrate (NOx) concentrations were decreased significantly in the groups without INO. Moreover, animals treated with INO showed higher rates of pulmonary apoptosis compared with their respective controls. These results demonstrate that NOx production is reduced after CPB and that INO acts on the inflammatory process by diminishing neutrophils and their major chemoattractant, IL-8. INO also increases cell apoptosis in the lungs under inflammatory conditions, which may explain, in part, how it resolves pulmonary inflammation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".