Electrical communication in branching arterial networks
Bibliographic record
Abstract
Electrical communication and its role in blood flow regulation are built on an examination of charge movement in single, isolated vessels. How this process behaves in broader arterial networks remains unclear. This study examined the nature of electrical communication in arterial structures where vessel length and branching were varied. Analysis began with the deployment of an existing computational model expanded to form a variable range of vessel structures. Initial simulations revealed that focal endothelial stimulation generated electrical responses that conducted robustly along short unbranched vessels and to a lesser degree lengthened arteries or branching structures retaining a single branch point. These predictions matched functional observations from hamster mesenteric arteries and support the idea that an increased number of vascular cells attenuate conduction by augmenting electrical load. Expanding the virtual network to 31 branches revealed that electrical responses increasingly ascended from fifth- to first-order arteries when the number of stimulated distal vessels rose. This property enabled the vascular network to grade vasodilation and network perfusion as revealed through blood flow modeling. An elevation in endothelial-endothelial coupling resistance, akin to those in sepsis models, compromised this ascension of vasomotor/perfusion responses. A comparable change was not observed when the endothelium was focally disrupted to mimic disease states including atherosclerosis. In closing, this study highlights that vessel length and branching play a role in setting the conduction of electrical phenomenon along resistance arteries and within networks. It also emphasizes that modest changes in endothelial function can, under certain scenarios, impinge on network responsiveness and blood flow control.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".