Pan‐junctional sarcoplasmic reticulum in vascular smooth muscle: nanospace Ca<sup>2+</sup> transport for site‐ and function‐specific Ca<sup>2+</sup> signalling
Bibliographic record
Abstract
This review focuses on how smooth muscle sarcoplasmic reticulum (SR), the major releasable Ca(2+) store in these cells, performs its many functions by communicating with the plasma membrane (PM) and other organelles across cytoplasmic nanospaces, defined by membrane-membrane junctions less than 50 nm across. In spite of accumulating evidence in favour of the view that cytoplasmic nanospaces are a prerequisite for effective control of diverse cellular functions, our current understanding of how smooth muscle cells accomplish site- and function-specific Ca(2+) signalling remains in its infancy. We first present evidence in support of the view that effective Ca(2+) signalling depends on the restricted diffusion of Ca(2+) within cytoplasmic nanospaces. We then develop an evidence-based model of the smooth muscle SR - the 'pan-junctional SR' model - that incorporates a network of tubules and quilts that are capable of auto-regulating their Ca(2+) content and determining junctional [Ca(2+)]i through loading and unloading at membrane-membrane nanojunctions. Thereby, we provide a novel working hypothesis in order to inform future investigation into the control of a variety of cellular functions by local Ca(2+) signals at junctional nanospaces, from contraction and energy metabolism to nuclear transcription. Based on the current literature, we discuss the molecular mechanisms whereby the SR mediates these multiple functions through the interaction of ion channels and pumps embedded in apposing membranes within inter-organellar junctions. We finally highlight the fact that although most current hypotheses are qualitatively supported by experimental data, solid quantitative simulations are seriously lacking. Considering that at physiological concentrations the number of calcium ions in a typical junctional nanospace between the PM and SR is of the order of 1, ion concentration variability plays a major role as the currency of information transfer and stochastic quantitative modelling will be required to both test and develop working hypotheses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".