Less is more: minimal expression of myoendothelial gap junctions optimizes cell–cell communication in virtual arterioles
Bibliographic record
Abstract
Key points Electrical signalling in blood vessels is important in acute and long‐term flow regulation. As myoendothelial gap junctions (MEGJs) provide electrical contacts between endothelial cells and smooth muscle cells (SMCs), a high MEGJ expression is thought to be important for intercellular communication despite observations of heterogeneous MEGJ expression. Using a computational approach, we find that a minimal but sufficient number of heterogeneously distributed MEGJs optimize electrical cell–cell communication. Tailoring SMC–SMC coupling to the MEGJ distribution and permeability ensures a smooth electrical response while retaining the ability to display local responses. As heterogeneous MEGJ distributions allow for different conduction profiles along the SMC and endothelial cell layers, it is possible to observe an apparently non‐decaying conduction profile in the SMC layer of a vessel with passive electrical properties. These findings expand our understanding of how heterogeneity in MEGJ distribution affects local and global flow. Abstract Dysfunctional electrical signalling within the arteriolar wall is a major cause of cardiovascular disease. The endothelial cell layer constitutes the primary electrical pathway, co‐ordinating contraction of the overlying smooth muscle cell (SMC) layer. As myoendothelial gap junctions (MEGJs) provide direct contact between the cell layers, proper vasomotor responses are thought to depend on a high, uniform MEGJ density. However, MEGJs are observed to be expressed heterogeneously within and among vascular beds. This discrepancy is addressed in the present study. As no direct measures of MEGJ conductance exist, we employed a computational modelling approach to vary the number, conductance and distribution of MEGJs. Our simulations demonstrate that a minimal number of randomly distributed MEGJs augment arteriolar cell–cell communication by increasing conduction efficiency and ensuring appropriate membrane potential responses in SMCs. We show that electrical coupling between SMCs must be tailored to the particular MEGJ distribution. Finally, observation of non‐decaying mechanical conduction in arterioles without regeneration has been a long‐standing controversy in the microvascular field. As heterogeneous MEGJ distributions provide for different conduction profiles along the cell layers, we demonstrate that a non‐decaying conduction profile is possible in the SMC layer of a vessel with passive electrical properties. These intriguing findings redefine the concept of efficient electrical communication in the microcirculation, illustrating how heterogeneous properties, ubiquitous in biological systems, may have a profound impact on system behaviour and how acute local and global flow control is explained from the biophysical foundations.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".