Angiopoietin-1 inhibits toll-like receptor 4 signalling in cultured endothelial cells: role of miR-146b-5p
Bibliographic record
Abstract
AIMS: Bacterial lipopolysaccharides (LPS) induce innate immune inflammatory responses in endothelial cells by activating toll-like receptor 4 (TLR4) signalling. Here, we investigate the effects of angiopoietin-1 (Ang-1) on LPS-induced TLR4 signalling and the role of the miR-146 family of micro RNAs in the effects of Ang-1 on TRL4 signalling. METHODS AND RESULTS: Leucocyte adhesion to human umbilical vein endothelial cells (HUVECs) was detected using fluorescence microscopy. Adhesion molecule, pro-inflammatory cytokine, miR-146a, and miR-146b-5p expressions in HUVECs were quantified using real-time PCR. TLR4 signalling protein levels were measured using immunoblotting. Exposure of HUVECs to LPS for 4-6 h induces robust inflammatory responses, including enhanced leucocyte adhesion, up-regulation of adhesion molecule expression (VCAM1, ICAM1, E-SELECTIN), enhanced cytokine production (TNFα, IL1β, IL6, and IL8), and increased NFκB luciferase reporter activity. Addition of Ang-1 to the culture medium for 24 h prior to LPS exposure significantly attenuates these responses. Prolonged Ang-1 exposure significantly decreases IRAK1 and TRAF6 protein levels but has no effect on TLR4, MYD88, IRAK4, or TAK1 expressions. Ang-1 triggers significant up-regulation of miR-146b-5p levels but has no effect on miR-146a or miR-146b-3p expressions. Transfection of HUVECs with a miR-146b-5p mimic significantly attenuates LPS-induced inflammatory responses and IRAK1 and TRAF6 expressions. In HUVECs transfected with a miR-146b-5p inhibitor, Ang-1 has no effect on LPS-induced inflammatory responses or IRAK1 and TRAF6 expressions. CONCLUSION: Ang-1 disrupts TLR4 signalling, resulting in inhibition of LPS-induced inflammatory responses in endothelial cells. This inhibition occurs through selective targeting of IRAK1 and TRAF6 proteins by miR-146b-5p.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".