Excess nitric oxide decreases cytochrome<i>P</i>-450 2J4 content and<i>P</i>-450-dependent arachidonic acid metabolism in lungs of rats with acute pneumonia
Bibliographic record
Abstract
Recently, we demonstrated that pulmonary CYP2J4 content, a prominent source of EETs and HETEs formation in rat lungs, is reduced in pneumonia. Therefore, the purpose of this study was to determine the role of iNOS-derived NO in reduced pulmonary CYP2J4 protein content and decreased CYP metabolites in pneumonia. Rats were randomized to control, control plus 1400W (iNOS inhibitor), pneumonia, and pneumonia plus 1400W groups. Pseudomonas organisms were injected into lungs of pneumonia rats. At 40 h after surgery, rats were treated with either saline or 1400W for 4 h before death. Venous plasma samples were obtained for measuring nitrites/nitrates (NOx). There was no significant effect of 1400W on blood pressure measured in control or pneumonia rats, whereas 1400W reduced the elevated plasma NOx levels in pneumonia rats by half. CYP primary metabolites of AA formed at significantly lower rates in pulmonary microsomes from pneumonia rats compared with control rats. Treatment of pneumonia rats with 1400W resulted in a significant increase in the rate of formation of pulmonary EETs and omega-terminal HETEs compared with untreated pneumonia rats. The reduction in CYP2J4 protein content in pneumonia lung microsomes was also partially prevented by 1400W. Therefore, excess NO from iNOS decreases the pulmonary production of EETs and omega-HETEs in acute pneumonia. Inhibition of iNOS restores CYP2J4 protein content and CYP activity in acute pneumonia, indicating an important NO-CYP interaction in pulmonary responses to infection. We speculate CYP2J4 and its AA metabolites are involved in the modulation of pulmonary function in health and disease.
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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 | 0.000 |
| 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".