Endothelin axis induces metalloproteinase activation and invasiveness in human lymphatic endothelial cellsThis article is one of a selection of papers published in the two-part special issue entitled 20 Years of Endothelin Research.
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
The molecular mechanisms involved in lymphangiogenesis were unknown until recently. We previously demonstrated that the endothelin-1 (ET-1) axis stimulates lymphatic endothelial cells (LEC) and lymphatic vessels to grow and invade. Here we further investigated the effect of ET-1 on lymphatic vessels and evaluated whether ET-1 actions result in the functional activation of lymphangiogenesis. Using highly purified human LEC, characterized for the expression of ET-1 axis members by quantitative real-time PCR, we found that the endothelin B receptor (ETB), upon activation by ET-1, induced matrix-metalloproteinase activation, demonstrating that ET-1 influenced the activity of the proteolytic enzymes required for LEC invasion. Functional assays performed by using intradermal lymphangiography demonstrated that ET-1 promoted the formation of lymphatic vessels and that these vessels were capable of lymphatic flow. ETB blockade with the specific antagonist BQ788 inhibited matrix-metalloproteinase activation and dye transport within the lymphatic vessels, demonstrating that ETB is involved in the regulation of the growth of and in the formation of functional vessels upon activation by ET-1. Our results suggest that ET-1 is a lymphangiogenic mediator and that targeting pharmacologically ETB may be therapeutically exploited in a variety of diseases, including cancer.
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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) | 0.003 | 0.001 |
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".