Ets‐1 and the mitogen activated protein kinases are modulated by nitric oxide
Bibliographic record
Abstract
Luminal splitting via internal division of capillaries is a form of angiogenesis caused by increased shear stress. While the mechanism behind luminal splitting is unknown, it is known that nitric oxide (NO) production and the mitogen activated protein (MAP) kinases are affected by shear stress. The transcription factor Ets‐1 is known to cause transcription of many proteins used in angiogenesis. We hypothesized that shear stress increases Ets‐1 via NO and the MAP kinases. Skeletal muscle endothelial cells (SMEC) were exposed to shear stress with or without the NO inhibitor L‐NG‐Nitroarginine (LNNA), and Ets‐1 mRNA was measured. Ets‐1 mRNA increased 4‐fold (± 1.4) after 2 hours of shear stress compared to control (p=0.003, n=3), and this was attenuated by LNNA (1.8 ± 0.4 fold increase vs. control, ns, n=3). SMEC stimulated by the NO donor S‐nitroso‐N‐acetylpenicillamine (SNAP) for 2 hours showed a trend towards an increase in Ets‐1 protein at 10 μM SNAP (1.5 ± 0.2 fold increase, p=0.06, n=3), but no change in Ets‐1 protein at 100 μM SNAP (1.0 ± 0.3, ns, n=3). Stimulation of SMEC with 100 μM SNAP caused a trend towards an increase in p38 phosphorylation (2.16 ± 0.5, p=0.08, n=3), a decrease in ERK phosphorylation (0.5 ± 0.14, p=0.02, n=3), and no change in phosphorylated c‐jun (1.3 ± 0.24, ns, n=2). These experiments will be repeated using 10 μM SNAP to determine if a dose‐dependent effect is occurring. Our results support a role for shear stress modulation of Ets‐1 via NO. Further studies will clarify the involvement of the MAP kinases in this signal pathway. Funded by CIHR.
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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) | 0.002 | 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".