Effects of macrophage inducible nitric oxide synthase in murine septic lung injury
Bibliographic record
Abstract
Inducible nitric oxide synthase (iNOS) contributes importantly to septic pulmonary protein leak in mice with septic acute lung injury (ALI). However, the role of alveolar macrophage (AM) iNOS in septic ALI is not known. Thus we assessed the specific effects of AM iNOS in murine septic ALI through selective AM depletion (via intratracheal instillation of clodronate liposomes) and subsequent AM reconstitution (via intratracheal instillation of donor iNOS+/+ or iNOS-/- AM). Sepsis was induced by cecal ligation and perforation, and ALI was assessed at 4 h: protein leak by the Evans blue (EB) dye method, neutrophil infiltration via myeloperoxidase (MPO) activity, and pulmonary iNOS mRNA expression via RT-PCR. In iNOS+/+ mice, AM depletion attenuated the sepsis-induced increases in pulmonary microvascular protein leak (0.3 +/- 0.1 vs. 1.4 +/- 0.1 microg EB.g lung(-1).min(-1); P < 0.05) and MPO activity (37 +/- 4 vs. 67 +/- 8 U/g lung; P < 0.05) compared with that shown in non-AM-depleted mice. In AM-depleted iNOS+/+ mice, septic pulmonary protein leak was restored by AM reconstitution with iNOS+/+ AM (0.9 +/- 0.3 microg EB.g lung(-1).min(-1)) but not with iNOS-/- donor AM. In iNOS-/- mice, sepsis did not induce pulmonary protein leak or iNOS mRNA expression, despite increased pulmonary MPO activity. However, AM depletion in iNOS-/- mice and subsequent reconstitution with iNOS+/+ donor AM resulted in significant sepsis-induced pulmonary protein leak and iNOS expression. Septic pulmonary MPO levels were similar in all AM-reconstituted groups. Thus septic pulmonary protein leak is absolutely dependent on the presence of functional AM and specifically on iNOS in AM. AM iNOS-dependent pulmonary protein leak was not mediated through changes in pulmonary neutrophil influx.
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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) | 0.001 | 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 | 0.001 | 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".