Induction of nitric oxide synthase expression by lipopolysaccharide is mediated by calcium-dependent PKCα-β1 in alveolar epithelial cells
Bibliographic record
Abstract
Nitric oxide (NO) plays an important role in innate host defense and inflammation. In response to infection, NO is generated by inducible nitric oxide synthase (iNOS), a gene product whose expression is highly modulated by different stimuli, including lipopolysaccharide (LPS) from gram-negative bacteria. We reported recently that LPS from Pseudomonas aeruginosa altered Na⁺ transport in alveolar epithelial cells via a suramin-dependent process, indicating that LPS activated a purinergic response in these cells. To further study this question, in the present work, we tested whether iNOS mRNA and protein expression were modulated in response to LPS in alveolar epithelial cells. We found that LPS induced a 12-fold increase in iNOS mRNA expression via a transcription-dependent process in these cells. iNOS protein, NO, and nitrotyrosine were also significantly elevated in LPS-treated cells. Ca²⁺ chelation and protein kinase C (PKCα-β1) inhibition suppressed iNOS mRNA induction by LPS, implicating Ca²⁺-dependent PKC signaling in this process. LPS evoked a significant increase of extracellular ATP. Because PKC activation is one of the signaling pathways known to mediate purinergic signaling, we evaluated the hypothesis that iNOS induction was ATP dependent. Although high suramin concentration inhibited iNOS mRNA induction, the process was not ATP dependent, since specific purinergic receptor antagonists could not inhibit the process. Altogether, these findings demonstrate that iNOS expression is highly modulated in alveolar epithelial cells by LPS via a Ca²⁺/PKCα-β1 pathway independent of ATP signaling.
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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 | 0.001 |
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".