Endothelial NOTCH1 is suppressed by circulating lipids and antagonizes inflammation during atherosclerosis
Bibliographic record
Abstract
Although much progress has been made in identifying the mechanisms that trigger endothelial activation and inflammatory cell recruitment during atherosclerosis, less is known about the intrinsic pathways that counteract these events. Here we identified NOTCH1 as an antagonist of endothelial cell (EC) activation. NOTCH1 was constitutively expressed by adult arterial endothelium, but levels were significantly reduced by high-fat diet. Furthermore, treatment of human aortic ECs (HAECs) with inflammatory lipids (oxidized 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine [Ox-PAPC]) and proinflammatory cytokines (TNF and IL1β) decreased Notch1 expression and signaling in vitro through a mechanism that requires STAT3 activation. Reduction of NOTCH1 in HAECs by siRNA, in the absence of inflammatory lipids or cytokines, increased inflammatory molecules and binding of monocytes. Conversely, some of the effects mediated by Ox-PAPC were reversed by increased NOTCH1 signaling, suggesting a link between lipid-mediated inflammation and Notch1. Interestingly, reduction of NOTCH1 by Ox-PAPC in HAECs was associated with a genetic variant previously correlated to high-density lipoprotein in a human genome-wide association study. Finally, endothelial Notch1 heterozygous mice showed higher diet-induced atherosclerosis. Based on these findings, we propose that reduction of endothelial NOTCH1 is a predisposing factor in the onset of vascular inflammation and initiation of atherosclerosis.
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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 | 0.001 | 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 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".