Heparin suppresses lipid raft‐mediated signaling and ligand‐independent EGF receptor activation
Why this work is in the frame
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Bibliographic record
Abstract
Heparin is well known to suppress vascular smooth muscle cell (VSMC) proliferation, and attempts to exploit this therapeutically have led to recognition of multiple pathways for heparin's anti-mitogenic actions. At low concentrations (ca. 1 microg.ml(-1)), these suppressive effects may reflect physiological activities of endogenous heparan sulfates, and appear to be rapid responses to extracellular or cell surface-associated heparin. Because heparin has been shown to influence expression of caveolin proteins, and caveolae/lipid rafts are critical structures modulating cell signaling, we examined the effect of heparin on signaling involving cholesterol-rich membrane microdomains. The VSMC line PAC-1 activates the MAP kinase Erk in response to the cholesterol-sequestering agents methyl-beta-cyclodextrin and nystatin. This follows a temporal sequence that involves Ras-GTP activation of MEK, and is independent of PKC, Src, and PI3 kinase. However, ligand-independent phosphorylation of the EGF receptor (EGFR) by removal of cholesterol precedes Ras activation, and the EGFR kinase inhibitor AG1478 blocks Erk phosphorylation, supporting occurrence of the signaling sequence EGFR-Ras-MEK-Erk. Phosphorylation of EGFR occurs predominantly in caveolin-rich microdomains as identified by Western blotting of fractions from density gradient centrifugation of membranes prepared under detergent-free conditions. In these situations, heparin inhibits phosphorylation of EGFR on the Src-dependent site Tyr(845), but not the autophosphorylation of Tyr(1173), and decreases Ras activation and Erk phosphorylation. We conclude that heparin can suppress Erk signaling in VSMC with effects on site-specific phosphorylation of EGFR localized in caveolin-enriched lipid rafts.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it