The conducted vasomotor response and the principles of electrical communication in resistance arteries
Bibliographic record
Abstract
Biological tissues are fed by arterial networks whose task is to set blood flow delivery in accordance with energetic demand. Coordinating vasomotor activity among hundreds of neighboring segments is an essential process, one dependent upon electrical information spreading among smooth muscle and endothelial cells. The "conducted vasomotor response" is a functional expression of electrical spread, and it is this process that lies at the heart of this critical review. Written in a narrative format, this review first highlights historical manuscripts and then characterizes the conducted response across a range of preparations. Trends are highlighted and used to guide subsequent sections, focused on cellular foundations, biophysical underpinnings, and regulation in health and disease. Key information has been tabulated; figures reinforce grounding concepts and reveal a framework within which theoretical and experimental work can be rationalized. This summative review highlights that despite 30 years of concerted experimentation, key aspects of the conducted response remain ill defined. Of note is the need to rationalize the regulation and deterioration of conduction in pathobiological settings. New quantitative tools, along with transgenic technology, are discussed as a means of propelling this investigative field forward.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".