Inhibition of STAT3 phosphorylation by sulforaphane reduces adhesion molecule expression in vascular endothelial cell
Bibliographic record
Abstract
Intercellular adhesion molecule 1 (ICAM-1) and vascular cell adhesion molecule 1 (VCAM-1) play key roles in the initiation of vascular inflammation. In this study, we explored whether sulforaphane, a dietary phytochemical, can inhibit the expression of ICAM-1 and VCAM-1 in human umbilical vein endothelial cells (HUVEC) stimulated with lipopolysaccharide (LPS), and the mechanisms involved. Sulforaphane prevented the LPS-mediated increase in ICAM-1 and VCAM-1 expression, (P < 0.01) in HUVEC. Sulforaphane also prevented the LPS-mediated increase in the phosphorylation of signal transducer and activator of transcription 3 (STAT3) (P < 0.01). Stattic, a STAT3 inhibitor, reduced the LPS-induced expression of ICAM-1 and VCAM-1, and STAT3 phosphorylation (P < 0.01). STAT3 small interfering RNA treatment reduced the LPS-induced expression of ICAM-1, VCAM-1, and STAT3 (P < 0.01). Sulforaphane reduced LPS-mediated THP-1 monocyte adhesion to HUVEC (P < 0.01). In C57BL/6 mice, injection of LPS increased aortic ICAM-1 and VCAM-1 expression, and this effect was prevented by sulforaphane. These data provide insight into the mechanism through which sulforaphane partly reduces the expression of ICAM-1 and VCAM-1 on the vascular wall by inhibiting STAT3 phosphorylation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".