Roles of iNOS and nNOS in sepsis-induced pulmonary apoptosis
Bibliographic record
Abstract
Apoptosis(programmed cell death) is induced in pulmonary cells and contributes to the pathogenesis of acute lung injury in septic humans. Previous studies have shown that nitric oxide (NO) is an important modulator of apoptosis; however, the functional role of NO derived from inducible NO synthase (iNOS) in sepsis-induced pulmonary apoptosis remains unknown. We measured pulmonary apoptosis in a rat model of Escherichia coli lipopolysaccharide (LPS)-induced sepsis in the absence and presence of the selective iNOS inhibitor 1400W. Four groups were studied 24 h after saline (control) or LPS injection in the absence and presence of 1400W pretreatment. Apoptosis was evaluated using DNA fragmentation, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling staining, and caspase activation. LPS administration significantly augmented pulmonary cell apoptosis and caspase-3 activity in airway and alveolar epithelial cells. Pretreatment with 1400W significantly enhanced LPS-induced pulmonary apoptosis and increased caspase-3 and -7 activation. The antiapoptotic effect of iNOS was confirmed in iNOS-/- mice, which developed a greater degree of pulmonary apoptosis both under control conditions and in response to LPS compared with wild-type mice. By comparison, genetic deletion of the neuronal NOS had no effect on LPS-induced pulmonary apoptosis. We conclude that NO derived from iNOS plays an important protective role against sepsis-induced pulmonary apoptosis.
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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 | 0.001 | 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 | 0.000 |
| 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".