Growth State-Dependent Activation of eNOS in Response to DHA: Involvement of p38 MAPK
Bibliographic record
Abstract
Our laboratory previously reported that docosahexaenoic acid (DHA) differentially activates p38 mitogen-activated protein kinase (MAPK) in growing and quiescent human endothelial cells, which represent the dysfunctional and healthy states in vivo, respectively. Since endothelial nitric oxide synthase (eNOS) activity differs between healthy and dysfunctional endothelial cells, and p38 MAPK reportedly regulates both the activity and expression of eNOS, we hypothesized that the beneficial actions of DHA on endothelial cells are due to eNOS activation by p38 MAPK. The contribution of mitogen- and stress-activated protein kinase (MSK), a p38 MAPK substrate, was also investigated. Growing and quiescent EA.hy926 cells, prepared on Matrigel®-coated plates, were incubated with inhibitors of p38MAPK or MSK before adding DHA. eNOS phosphorylation and levels were quantified by Western blotting. Treatment with 20 µM DHA activated eNOS in both growth states whereas 125 µM DHA suppressed eNOS activation in growing cells. Quiescent cells had higher basal levels of eNOS than growing cells, while 125 µM DHA decreased eNOS levels in both growth states. p38 MAPK inhibition enhanced eNOS activation in quiescent cells but suppressed it in growing cells. Interestingly, 125 µM DHA counteracted these effects of p38 MAPK inhibition in both growth states. MSK was required for eNOS activation in both growth states, but it only mediated eNOS activation by DHA in quiescent cells. MSK thus affects eNOS via a pathway independent of p38MAPK. Quiescent cells were also more resistant to the apoptosis-inducing effect of 125 µM DHA compared to growing cells. The growth state-dependent regulation of p38MAPK and eNOS by DHA provides novel insight into the molecular mechanisms by which DHA influences endothelial cell function.
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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 | 0.001 |
| 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 | 0.000 |
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".