The Role of Actin Filament Dynamics in the Myogenic Response of Cerebral Resistance Arteries
Bibliographic record
Abstract
The myogenic response has a critical role in regulation of blood flow to the brain. Increased intraluminal pressure elicits vasoconstriction, whereas decreased intraluminal pressure induces vasodilatation, thereby maintaining flow constant over the normal physiologic blood pressure range. Improved understanding of the molecular mechanisms underlying the myogenic response is crucial to identify deficiencies with pathologic consequences, such as cerebral vasospasm, hypertension, and stroke, and to identify potential therapeutic targets. Three mechanisms have been suggested to be involved in the myogenic response: (1) membrane depolarization, which induces Ca(2+) entry, activation of myosin light chain kinase, phosphorylation of the myosin regulatory light chains (LC(20)), increased actomyosin MgATPase activity, cross-bridge cycling, and vasoconstriction; (2) activation of the RhoA/Rho-associated kinase (ROCK) pathway, leading to inhibition of myosin light chain phosphatase by phosphorylation of MYPT1, the myosin targeting regulatory subunit of the phosphatase, and increased LC(20) phosphorylation; and (3) activation of the ROCK and protein kinase C pathways, leading to actin polymerization and the formation of enhanced connections between the actin cytoskeleton, plasma membrane, and extracellular matrix to augment force transmission. This review describes these three mechanisms, emphasizing recent developments regarding the importance of dynamic actin polymerization in the myogenic response of the cerebral vasculature.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".