Shear stress‐induced Ets‐1 modulates protease inhibitor expression in microvascular endothelial cells
Bibliographic record
Abstract
Elevated shear stress within the skeletal muscle microvasculature is implicated in the induction of a longitudinal splitting form of angiogenesis, which is characterized by the lack of basement membrane breakage. We investigated whether the transcriptional regulator, Ets-1, is responsive to changes in hemodynamic forces and if so, whether Ets-1 controls microvascular endothelial cell integrity by inducing the expression of inhibitors of matrix degrading proteases. Rats were treated with prazosin for 2, 4, and 7 days to increase in microvascular shear stress in hindlimb skeletal muscles. In complimentary in vitro experiments, rat microvascular skeletal muscle endothelial cells were exposed to laminar shear stress (15 dyne/cm(2)) for 0.5, 2, and 24 h. TaqMan PCR analysis of laser microdissected capillaries isolated from EDL muscles demonstrated transient (after 2 days) induction of Ets-1 gene expression. In cultured cells, a transient up-regulation of Ets-1 mRNA was observed after 2 h shear stimulation, accompanied by increased phosphorylation of Ets-1 and enhanced Ets-1 DNA binding activity. This response was modulated by ERK1/2 and p38 MAP kinases, but was not dependent on NOS or COX-2 activity. PAI-1, TIMP-1 and TIMP-3 mRNA were elevated significantly in prazosin treated EDL, and in response to shear stimulation in vitro. In cultured endothelial cells, Ets-1 RNA interference abolished the shear-induced increases in Ets-1, PAI-1, TIMP-1, and TIMP-3 mRNA expression. These results suggest that enhanced laminar shear stress may act to preserve the integrity of microvascular walls in part through Ets-1-dependent induction of protease inhibitors.
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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".