Long term shear stress leads to increased phosphorylation of multiple MAPK species in cultured human aortic endothelial cells
Bibliographic record
Abstract
Fluid dynamics strongly influences endothelial cell function, and participates in the localization of atherosclerotic plaques at blood vessel branches. We investigated the hypothesis that wild-type human aortic endothelial cells (HAEC) exposed to prolonged pulsatile flow stimulation have levels of phosphorylated mitogen-activated protein kinases (MAPK) that are significantly greater than those observed in statically grown cultures. HAEC were exposed to pulsatile laminar shear stress in a parallel-plate flow chamber and analyzed for levels of phosphorylated ERK, JNK and p38 at 1, 10 and 20 h. While some MAPK exhibited alternating patterns of phosphorylation, others were characterized by steady increases or unchanged profiles until the terminal (20 h) time point. However, at 20 h, each MAPK demonstrated an increase in phosphorylation versus statically cultivated cells. Further, 20 h cultures from 10 dyn/cm(2) pulsatile shear stress had higher levels of phosphorylation for each MAPK than those from 2 dyn/cm(2). The finding that MAPK species can be phosphorylated in response to a prolonged pulsatile shear stress in both a time and magnitude dependent manner is an interesting result that may help to explain how the differential behaviors observed between cells from different flow environments can be generated and maintained.
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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 | 0.000 |
| 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".