iNOS expression requires NADPH oxidase‐dependent redox signaling in microvascular endothelial cells
Bibliographic record
Abstract
Redox regulation of inducible nitric oxide synthase (iNOS) expression was investigated in lipopolysaccharide and interferon-gamma (LPS + IFNgamma)-stimulated microvascular endothelial cells from mouse skeletal muscle. Unstimulated endothelial cells produced reactive oxygen species (ROS) sensitive to inhibition of NADPH oxidase (apocynin and DPI), mitochondrial respiration (rotenone) and NOS (L-NAME). LPS + IFNgamma caused a marked increase in ROS production; this increase was abolished by inhibition of NADPH oxidase (apocynin, DPI and p47phox deficiency). LPS + IFNgamma induced substantial expression of iNOS protein. iNOS expression was prevented by the antioxidant ascorbate and by NADPH oxidase inhibition (apocynin, DPI and p47phox deficiency), but not by inhibition of mitochondrial respiration (rotenone) and xanthine oxidase (allopurinol). iNOS expression also was prevented by selective antagonists of ERK, JNK, Jak2, and NFkappaB activation. LPS + IFNgamma stimulated activation/phosphorylation of ERK, JNK, and Jak2 and activation/degradation of IkappaB, but only the activation of JNK and Jak2 was sensitive to ascorbate, apocynin and p47phox deficiency. Ascorbate, apocynin and p47phox deficiency also inhibited the LPS + IFNgamma-induced DNA binding activity of transcription factors IRF1 and AP1 but not NFkappaB. In conclusion, LPS + IFNgamma-induced NFkappaB activation is necessary for iNOS induction but is not dependent on ROS signaling. LPS + IFNgamma-stimulated NADPH oxidase activity produces ROS that activate the JNK-AP1 and Jak2-IRF1 signaling pathways required for iNOS induction. Since blocking either NFkappaB activation or NADPH oxidase activity is sufficient to prevent iNOS expression, they are separate targets for therapeutic interventions that aim to modulate iNOS expression in sepsis.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".