Interleukin-1β, Src- and non-Src tyrosine kinases, and nitric oxide synthase induction in rat aorta in vitro
Bibliographic record
Abstract
We studied the potential roles for endogenous interleukin-1beta (IL-1beta) and for several signaling pathways in the spontaneous induction in vitro of inducible nitric oxide synthase (iNOS) in endothelium-denuded rat aorta rings. Added IL-1beta augmented, whereas the IL-1beta receptor antagonist IL-1ra blocked, spontaneous iNOS induction. Furthermore, increases in IL-1beta mRNA preceded those of iNOS mRNA. Mitogen-activated protein kinase kinase and phosphatidyl inositol 3' kinase inhibition did not block iNOS induction, whereas nuclear factor kappaB inhibition did. The sarcoma virus tyrosine kinase (Src) family-selective inhibitor 4-amino-5(4-methylphenyl)-7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1) blocked the upregulation of IL-1beta mRNA and the subsequent induction of iNOS but not the induction of iNOS stimulated by exogenously added IL-1beta. In contrast, the non-Src inhibitors TP 47/AG 213 and genistein and the tyrosine phosphatase inhibitor vanadate did not affect the spontaneous upregulation of IL-1beta mRNA but blocked both the IL-1beta-mediated and spontaneous induction of iNOS. We conclude that 1) the upregulation of tissue IL-1beta, via a signaling pathway involving a Src family kinase, plays a key role in rat vascular iNOS induction and 2) non-Src tyrosine kinases play roles downstream from IL-1beta for iNOS induction.
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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) | 0.000 | 0.001 |
| 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".