Endothelial cell-specific ET<sub>B</sub> receptor knockout: autoradiographic and histological characterisation and crucial role in the clearance of endothelin-1This article is one of a selection of papers published in the two-part special issue entitled 20 Years of Endothelin Research.
Bibliographic record
Abstract
Inactivation of endothelin B receptors (ETB), either through selective pharmacological antagonism or genetic mutation, increases the circulating concentration of endothelin-1 (ET-1), suggesting ETB plays an important role in clearance of this peptide. However, the cellular site of ETB-mediated clearance has not yet been determined. We have used a novel mouse model of endothelial cell-specific knockout (KO) of ETB (EC ETB(-/-)) to evaluate the relative contribution of EC-ETB to the clearance of ET-1. Phenotypic evidence of EC-specific ETB KO was confirmed by immunocytochemistry and autoradiography. Binding of the radiolabelled selective ETB ligand BQ3020 was significantly and selectively decreased in EC-rich tissues of EC ETB(-/-) mice, including the lung, liver, and kidney. By contrast, ETA binding was unaltered. RT-PCR confirmed equal expression of ET-1 in tissue from EC ETB(-/-) mice and controls, despite increased concentration of plasma ET-1 in EC ETB(-/-). Clearance of an intravenous bolus of [(125)I]ET-1 was impaired in EC ETB(-/-) mice. Pretreatment with the selective ETB antagonist A192621 impaired [(125)I]ET-1 clearance in control animals to a similar extent, but did not further impair clearance in EC ETB(-/-) mice. These studies suggest that EC-ETB are largely responsible for the clearance of ET-1 from the circulation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".