Post‐endocytotic trafficking of ETB receptors in cardiomyocytes: effects of pressure‐overload hypertrophy on their subcellular distribution.
Bibliographic record
Abstract
Endothelins are implicated in both cardiac function and pathophysiology via their actions on ETA (selective for ET‐1>>ET‐3) and ETB (non selective) receptors. To date, the cellular signaling evoked by ET‐1 has been studied by activating receptors at the cell surface. However, ETB are primarily located on the nuclear membrane in adult cardiac ventricular myocytes (ACVMs). The present study was to determine the origin of these receptors. In ACVMs, which express ETA and ETB, fluorescently‐labeled ET‐1 was internalized and localized to lysosomes plus perinuclear structures. ET‐3 was transported soley to lysosomes. In rat aortic endothelial cells, which express ETB, endocytosed ET‐1 and ET‐3 were transported to lysosomes. To determine if the subcellular distribution of ETRs was altered during hypertrophy, mice were subjected to transverse aortic constriction (TAC) for 7 days and the distribution of ETRs examined by immunocytofluorescence. Whereas ETB immunofluorescence was associated with the nuclear membrane in sham animals, additional perinuclear staining was observed in TAC hearts. The distribution of ETA immunofluorescence was unaffected. Hence, localization of ETB to the nuclear membrane is not a result of post‐endocytotic ligand/receptor complex trafficking and the subcellular distribution, and possibly trafficking, of ETB is altered during hypertrophy. (Supported by the CIHR, FICM and HSFC)
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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) | 0.001 | 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".