Loss of eNOS in Endothelial Cells Promotes Proliferation
Bibliographic record
Abstract
Background Endothelial cells help maintain vascular homeostasis mainly by balancing interplay between vasorelaxation and vasoconstriction via regulating availability of Nitric Oxide (NO). Endothelial nitric oxide synthase (eNOS) is one of three NOS isoforms that catalyses the synthesis of NO to regulate endothelial function. To date, however, eNOS’s role in endothelial cell proliferation, remains unclear. Methods and Results To gain a better understanding about eNOS and cell proliferation, we genetically inhibited eNOS via silencing by transfecting cultured human umbilical vein endothelial cells with sieNOS or scrambled control. Successful eNOS silencing was confirmed at transcript and protein levels, and then endothelial cell proliferation was evaluated. Surprisingly, loss of eNOS significantly induced endothelial cell proliferation, concomitant with significant downregulation of both cell cycle inhibitor p21 and cell proliferation antigen Ki‐67. To confirm the specificity of eNOS silencer, we used another sieNOS molecule, which also showed the similar results as endothelial proliferation was significantly induced in eNOS‐silenced endothelial cells. Later, to demonstrate that the induced endothelial cell proliferation is due to eNOS inhibition, we pharmacologically inhibited eNOS by treating endothelial cells with L‐NAME. Contrastingly, L‐NAME‐treatment significantly inhibited endothelial cell proliferation in a dose‐dependent manner. Conclusion Our findings, for the first time, indicate that eNOS regulate endothelial function by directly controlling endothelial cell proliferation. Observed inhibition of endothelial cell proliferation by L‐NAME, may be due to its non‐specific effects. The findings also indicate that eNOS and L‐NAME might employ different pathways regulating endothelial cell proliferation warranting further investigation.
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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 | 0.001 |
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".