Mitochondrial Regulation of Sarcoplasmic Reticulum Ca<sup>2+</sup>Content in Vascular Smooth Muscle Cells
Bibliographic record
Abstract
Subplasmalemmal ion fluxes have global effects on Ca(2+) signaling in vascular smooth muscle. Measuring cytoplasmic and mitochondrial [Ca(2+)]and [Na(+)], we previously showed that mitochondria buffer both subplasmalemmal cytosolic [Ca(2+)] and [Na(+)] in vascular smooth muscle cells. We have now directly measured sarcoplasmic reticulum [Ca(2+)] in aortic smooth muscle cells, revealing that mitochondrial Na(+)/Ca(2+) exchanger inhibition with CGP-37157 impairs sarcoplasmic reticulum Ca(2+) refilling during purinergic stimulation. By overexpressing hFis1 to remove mitochondria from the subplasmalemmal space, we show that the rate and extent of sarcoplasmic reticulum refilling is augmented by a subpopulation of peripheral mitochondria. In ATP-stimulated cells, hFis-1-mediated relocalization of mitochondria impaired the sarcoplasmic reticulum refilling process and reduced mitochondrial [Ca(2+)] elevations, despite increased cytosolic [Ca(2+)] elevations. Reversal of plasmalemmal Na(+)/Ca(2+) exchange was the primary Ca(2+) entry mechanism following ATP stimulation, based on the effects of KB-R7943. We propose that subplasmalemmal mitochondria ensure efficient sarcoplasmic reticulum refilling by cooperating with the plasmalemmal Na(+)/Ca(2+) exchanger to funnel Ca(2+) into the sarcoplasmic reticulum and minimize cytosolic [Ca(2+)] elevations that might otherwise contribute to hypertensive or proliferative vasculopathies.
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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 | 0.000 |
| 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".