Overlapping and distinct biological effects of IL-6 classic and trans-signaling in vascular endothelial cells
Bibliographic record
Abstract
IL-6 affects tissue protective/reparative and inflammatory properties of vascular endothelial cells (ECs). This cytokine can signal to cells through classic and trans-signaling mechanisms, which are differentiated based on the expression of IL-6 receptor (IL-6R) on the surface of target cells. The biological effects of these IL-6-signaling mechanisms are distinct and have implications for vascular pathologies. We have directly compared IL-6 classic and trans-signaling in ECs. Human ECs expressed IL-6R in culture and in situ in coronary arteries from heart transplants. Stimulation of human ECs with IL-6, to model classic signaling, triggered the activation of phosphatidylinositol 3-kinase (PI3K)-Akt and ERK1/2 signaling pathways, whereas stimulation with IL-6 + sIL-6R, to model trans-signaling, triggered activation of STAT3, PI3K-Akt, and ERK1/2 pathways. IL-6 classic signaling reduced persistent injury of ECs in an allograft model of vascular rejection and inhibited cell death induced by growth factor withdrawal. When inflammatory effects were examined, IL-6 classic signaling did not induce ICAM or CCL2 expression but was sufficient to induce secretion of CXCL8 and support transmigration of neutrophil-like cells. IL-6 trans-signaling induced all inflammatory effects studied. Our findings show that IL-6 classic and trans-signaling have overlapping but distinct properties in controlling EC survival and inflammatory activation. This has implications for understanding the effects of IL-6 receptor-blocking therapies as well as for vascular responses in inflammatory and immune conditions.
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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) | 0.001 | 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".