Endothelin A receptors contribute to senescence of brain microvascular endothelial cells
Bibliographic record
Abstract
Cellular senescence plays a pivotal role in the aging and progression of neurodegenerative diseases, including vascular cognitive impairment and dementia (VCID). In postmortem brains from individuals with VCID, endothelin-1 (ET-1) levels closely correlate with blood barrier breakdown and cerebral hypoperfusion. Brain microvascular endothelial cells (BMVECs), previously thought to have exclusively endothelin B receptors, also possess endothelin A (ETA) receptors; however, the functional significance of this receptor in BMVECs is not known. We hypothesize that ETA receptors mediate BMVEC senescence. Serum-starved human BMVECs (HBEC5i) were incubated with ET-1 (1 µmol/L) in the presence/absence of ETA receptor antagonist BQ-123 (20 µmol/L). Cells were collected for Western blot and quantitative real-time PCR analyses. Treatment of ET-1 increased protein expression of ETA receptor, while it was prevented by the ETA receptor antagonist. ET-1 increased p21, p16, p53, LIF1 and cyclin D1 protein levels, and β-galactosidase accumulation, which were prevented in the presence of ETA blockade. While there was no change in tight junction proteins, ET-1 decreased adherent junction protein vascular endothelial cadherin (VE-cadherin) levels. In conclusion, ET-1 upregulates ETA receptors in BMVECs in an autocrine manner and triggers the activation of senescence. These in vitro findings need to be further studied in vivo to establish the role of ETA receptors in the progression of endothelial senescence in VCID.
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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 | 0.000 |
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".