Estradiol inhibits vascular endothelial cells pro-inflammatory activation induced by C-reactive protein
Bibliographic record
Abstract
In addition of being an important inflammatory biomarker and a risk factor for cardiovascular disease, much evidence indicates that the C-reactive protein (CRP) contributes to the atherosclerosis development process. This plasmatic protein synthesized by hepatocytes in response to inflammation and tissue injury induces pro-inflammatory molecules' expression by endothelial cells (ECs). Previous studies showed that the 17β-estradiol (E2) has beneficial effects on vascular cells by reducing in vitro pro-inflammatory molecules expressions in EC. Therefore, we hypothesize that E2 blocks or reduces CRP-mediated inflammatory responses by modulating endogenous production of CRP in EC and/or activation mechanisms. Using human aortic ECs (HAECs), we first evaluated CRP production by vascular EC and second demonstrated its self-induction. Indeed, recombinant human CRP stimulation induces a fivefold increase of CRP expression. A 1-h pre-treatment of E2 at a physiologic dose (10(-9 )M) leads to an important decrease of CRP production suggesting a partial blockage of its amplification loop mechanism. Furthermore, in HAEC, E2 reduces the secretion of the most potent agonist of CRP induction, the IL-6, by 21 %. E2 pre-treatment also decreased the expression of pro-inflammatory molecules IL-8, VCAM-1, and ICAM-1 induced by CRP and involved in leukocytes recruitment. In addition, we demonstrated that E2 could restore vascular endothelial growth factor-mediated EC migration response impaired by CRP suggesting another pro-angiogenic property of this hormone. These findings suggest that E2 can interfere with CRP pro-inflammatory effects via activation signals using its rapid, non-genomic pathway that may provide a new mechanism to improve vascular repair.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".