The Purinergic Agonists ATP and UTP Act Predominantly via P2Y Receptors in Human Vascular Endothelial Cells
Bibliographic record
Abstract
Purinergic agonists, such as ATP, can produce robust vasodilation, yet the specific receptor(s) (i.e. P2X or P2Y) responsible for these effects remain poorly characterized. In this study, we have examined the purinergic receptors mediating acute Ca 2+ mobilization, membrane hyperpolarization and nitric oxide (NO) synthesis in cultured HUVECs (EA.hy926 cell line). Brief application of either ATP or UTP (2 μM) to single HUVECs produced comparable elevations in cytosolic Ca 2+ , membrane hyperpolarizations and acute NO synthesis. These responses were largely unaffected in the presence of the non‐selective P2X receptor antagonists PPADS (10 μM) and TNP‐ATP (1 μM). In contrast to ATP and UTP, the selective P2X receptor agonist α,β‐methyl ATP (2 μM) had little effect on cytosolic Ca 2+ , membrane potential or NO production. Collectively, these data suggest that the observed stimulatory actions of ATP and UTP in this cell system occur primarily via P2Y, and not P2X, receptors. A plot of the concentration‐dependent rise in cytosolic Ca 2+ evoked by ATP and UTP revealed similar EC50 values for the two agonists (1–3 μM); this equipotent action of ATP and UTP further suggests that P2Y2 receptors are the predominant purinergic sub‐type. Finally, RT‐PCR analysis confirmed the presence of P2Y2 receptor mRNA in this human vascular endothelial cell model. Research support to AP Braun was provided by the CIHR and HSF Alberta
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".