Nuclear membrane R-type calcium channels mediate cytosolic ET-1-induced increase of nuclear calcium in human vascular smooth muscle cells
Bibliographic record
Abstract
The objective of this work was to verify whether, as in the case of the plasma membrane of human vascular smooth muscle cells (hVSMCs), cytosolic ET-1-induced increase of nuclear calcium is mediated via the activation of calcium influx through the steady-state R-type calcium channel. Pharmacological tools to identify the R-type calcium channels, as well as real 3-D confocal microscopy imaging techniques coupled to calcium fluorescent probes, were used to study the effect of cytosolic ET-1 on nuclear calcium in isolated nuclei of human hepatocytes and plasma membrane perforated hVSMCs. Our results showed that pre-treatment with pertussis toxin (PTX) or cholera toxin (CTX) prevented cytosolic ET-1 (10(-9) mol/L) from inducing a sustained increase in nuclear calcium. Furthermore, the L-type calcium channel blocker nifedipine did not prevent cytosolic ET-1 from inducing an increase in nuclear calcium, as opposed to the dual L- and R-type calcium channel blocker isradipine (PN200-110) (in the presence of nifedipine). In conclusion, the preventative effect with PTX and CTX, and the absence of an effect with nifedipine, as well as the blockade by isradipine on cytosolic ET-1-induced increase in nuclear calcium, suggest that this nuclear calcium influx in hVSMCs is due to activation of the steady-state R-type calcium channel. The sarcolemmal and nuclear membrane R-type calcium channels in hVSMCs are involved in ET-1 modulation of vascular tone in physiology and pathology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".