Induction of Endothelial Nitric Oxide Synthase Expression by IL-17 in Human Vascular Endothelial Cells: Implications for Vascular Remodeling in Transplant Vasculopathy
Bibliographic record
Abstract
IL-17 is a signature cytokine of Th17 cells, a recently described subset of effector CD4 T cells implicated in the development of several pathologies. We have examined the role of IL-17 in regulating endothelial NO synthase (eNOS) expression in human vascular endothelial cells (ECs) because of the key role of eNOS in determining the pathological outcome of immune-mediated vascular diseases. In cultured ECs, IL-17 increased expression of eNOS, eNOS phosphorylation at Ser(1177), and NO production. The induction of eNOS expression by IL-17 was prevented by the pharmacological inhibition of NF-κB, MEK, and JNK, as well as by small interfering RNA-mediated gene silencing of these signaling pathways. The expression of IL-17 was then examined by immunohistochemistry in human arteries affected by transplant vasculopathy (TV), a vascular condition that is a leading reflection of chronic heart transplant rejection. IL-17 was expressed by infiltrating leukocytes in the intima of arteries with TV, and the majority of IL-17-positive cells were T cells. The number of IL-17-positive cells was not correlated with the intima/media ratio, but was negatively correlated with the amount of luminal occlusion. There was also a significant positive correlation between the number of IL-17-positive cells and the density of eNOS-expressing luminal ECs in arteries with TV. Altogether, these findings show that IL-17 induces the expression of eNOS in human ECs and that this may facilitate outward expansion of arteries afflicted with TV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".