The Shear Stress–Regulated Expression of Glypican-4 in Endothelial Dysfunction In Vitro and Its Clinical Significance in Atherosclerosis
Bibliographic record
Abstract
Retention of circulating lipoproteins by their interaction with extracellular matrix molecules has been suggested as an underlying mechanism for atherosclerosis. We investigated the role of glypican-4 (GPC4), a heparan sulfate (HS) proteoglycan, in the development of endothelial dysfunction and plaque progression; Expression of GPC4 and HS was investigated in human umbilical vein/artery endothelial cells (HUVECs/HUAECs) using flow cytometry, qPCR, and immunofluorescent staining. Leukocyte adhesion was determined in HUVECs in bifurcation chamber slides under dynamic flow. The association between the degree of inflammation and GPC4, HS, and syndecan-4 expressions was analyzed in human carotid plaques; GPC4 was expressed in HUVECs/HUAECs. In HUVECs, GPC4 protein expression was higher in laminar than in non-uniform shear stress regions after a 1-day or 10-day flow (p < 0.01 each). The HS expression was higher under laminar flow after a 1 day (p < 0.001). Monocytic THP-1 cell adhesion to HUVECs was facilitated by GPC4 knock-down (p < 0.001) without affecting adhesion molecule expression. GPC4 and HS expression was lower in more-inflamed than in less-inflamed plaque shoulders (p < 0.05, each), especially in vulnerable plaque sections; Reduced expression of GPC4 was associated with atherogenic conditions, suggesting the involvement of GPC4 in both early and advanced stages of atherosclerosis.
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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".