Aortic smooth muscle and endothelial plasma membrane Ca<sup>2+</sup> pump isoforms are inhibited differently by the extracellular inhibitor caloxin 1b1
Bibliographic record
Abstract
Plasma membrane Ca(2+) pumps (PMCA) that expel Ca(2+) from cells are encoded by four genes (PMCA1-4). In this study, we show that aortic endothelium and smooth muscle differ in their PMCA isoform mRNA expression: endothelium expressed predominantly PMCA1, and smooth muscle expressed PMCA4 and a lower level of PMCA1. In this study, we report a novel peptide (caloxin 1b1, obtained by screening for binding to extracellular domain 1 of PMCA4), which inhibited PMCA extracellularly, selectively, and had a higher affinity for PMCA4 than PMCA1. It inhibited the PMCA Ca(2+)-Mg(2+)-ATPase activity in leaky erythrocyte ghosts (mainly PMCA4) with a K(i) value of 46 +/- 5 microM, making it 10x more potent than the previously reported caloxin 2a1. It was isoform selective because it inhibited the PMCA1 Ca(2+)-Mg(2+)-ATPase in human embryonic kidney-293 cells with a higher K(i) value (105 +/- 11 microM) than for PMCA4. Caloxin 1b1 was selective in that it did not inhibit other ATPases. Because caloxin 1b1 had been selected to bind to an extracellular domain of PMCA, it could be added directly to cells and tissues to examine its effects on smooth muscle and endothelium. In de-endothelialized aortic rings, caloxin 1b1 (200 microM) produced a contraction. It also increased the force of contraction produced by a submaximum concentration of phenylephrine. In aortic rings with endothelium intact, precontracted with phenylephrine and relaxed partially with a submaximum concentration of carbachol, caloxin 1b1 increased the force of contraction rather than potentiating the endothelium-dependent relaxation. In cultured cells, caloxin 1b1 increased the cytosolic [Ca(2+)] more in arterial smooth muscle cells than in endothelial cells. Thus caloxin 1b1 is the first highly selective extracellular PMCA inhibitor that works better on vascular smooth muscle than on endothelium.
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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".