Estradiol blocks the induction of CD40 and CD40L expression on endothelial cells and prevents neutrophil adhesion: An ERα-mediated pathway
Bibliographic record
Abstract
OBJECTIVE: Interferon gamma (IFN-gamma) was shown to induce CD40 and CD40L expression on endothelial cells (ECs) and consequently to promote neutrophil adhesion. The pro- and anti-inflammatory effects of estrogens are well recognized but their role on the regulation of CD40 and CD40L expression on ECs remains undefined. METHODS AND RESULTS: Treatment of porcine aortic endothelial cells (PAEC) with IFN-gamma for 24 h enhanced CD40 and CD40L expression by 97% and 78%, respectively. Pretreatment of PAEC with 17-beta-estradiol (17betaE) for 24 h prevented the latter expression of CD40/CD40L. Treatment of PAEC with antisense oligomers targeting ERalpha mRNA attenuated the ability of 17betaE to inhibit the IFN-gamma-induced CD40 and CD40L protein expression. The IFN-gamma activation pathway of CD40 is known to involve the phosphorylation of the Janus activated kinase (JAK) and the signal transducer and activator of transcription 1 (Stat1). 17betaE, acting via the estrogen receptor alpha (ERalpha), abrogated IFN-gamma-mediated effects on Stat1 but failed to inhibit Jak1 and Jak2 phosphorylation. Furthermore, 17betaE prevented neutrophil adhesion induced by IFN-gamma. CONCLUSION: In summary, 17betaE binding to ERalpha blocked IFN-gamma-induced Stat1 phosphorylation, CD40 and CD40L protein expression, and neutrophil adhesion onto ECs.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".