A novel mouse model to characterize the mechanisms of endothelin-1-induced vascular injury
Bibliographic record
Abstract
We demonstrated previously that ET-1 and cAMP may synergistically induce IL-6 release from adipocytes, mainly through their strong stimulatory effect on IL-6 gene expression.In the present study, we further examined the signaling pathways that may be involved.A luciferase reporter driven by promoter (-1310/+ 198) of mouse IL-6 gene was transfected into 3T3-L1 adipocytes to monitor IL-6 transcription in response to ET-1 and 8-bromo cAMP, and the effects of various inhibitory agents were tested.Whereas the stimulatory effect of ET-1 alone was inhibited by pertussis toxin (PT), GF109203X, U0126, N-acetylcysteine, salicylate, dominant negative CREB (dn-CREB) and mithramycin A, the stimulatory effect of 8-bromo cAMP was only inhibited by dn-CREB.On the other hand, the synergistic effect of ET-1 and cAMP was suppressed by GF109203X, U0126, salicylate, c-Junspecific antisense oligonucleotide (AS-cJun) and dn-CREB.PT had a partial inhibitory effect, while NAC and mithramycin A had no influence.Since NF-kB activation by ET-1 is mediated by a PKC&epsilon/ROS cascade, the observation that the synergistic effect of ET-1 and cAMP was inhibited by salicylate but not NAC suggests salicylate inhibited some factor in addition to NF-kB.Indeed, we found that another salicylate target p90 ribosomal S6 Kinase (RSK) was involved.Taken together, the synergistic effect of ET-1 and cAMP on IL-6 gene transcription seems to be mediated by pathways involving PKC, MAPK, CREB, AP-1 and RSK.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".