Monomeric C‐reactive protein activates endothelial cells <i>via</i> interaction with lipid raft microdomains
Bibliographic record
Abstract
Emerging evidence indicates that in addition to native pentameric C-reactive protein (CRP), monomeric CRP (mCRP) also plays an active role in inflammation associated with cardiovascular diseases. mCRP activates endothelial cells, one of the critical events in cardiovascular diseases; however, the underlying molecular mechanisms are incompletely understood. Here we report that association of mCRP with human aortic and coronary artery endothelial cells is predominantly due to membrane insertion rather than binding to the surface proteins Fc gammaRs and proteoglycans. We identify lipid rafts as the preferential membrane microdomains for mCRP anchorage. mCRP binding depends on membrane cholesterol content and is synergistically mediated by the putative cholesterol binding consensus sequence of CRP (aa 35-47) and the C-terminal octapeptide (aa 199-206). Conversely, disrupting lipid rafts with methyl-beta cyclodextrin or nystatin abrogated mCRP-induced cytokine release, reactive oxygen species generation, and adhesion molecule expression in endothelial cells. Furthermore, ex vivo treatment of rabbit thoracic aorta and carotid artery segments with nystatin prevented mCRP-induced IL-8 release. Our data identify mCRP-lipid raft interaction as an important mechanism in mediating cellular responses to mCRP and lend further support to the notion of mCRP regulation of endothelial cell function during inflammation.
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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".