Myogenic constriction occurs in the absence of a detectable increase in pLC20 in the presence of agonist‐induced tone
Bibliographic record
Abstract
Force generation in resistance arteries in response to increased transmural pressure, the myogenic response, is thought to involve increased cytosolic [Ca2+], activation of myosin light chain kinase, phosphorylation of myosin regulatory light chain subunits (LC20), actomyosin ATPase activation and cross‐bridge cycling, as well as Ca2+ sensitization owing to Rho‐associated kinase‐mediated inhibition of myosin light chain phosphatase activity (Johnson RP et al., J Physiol. 2009, 587:2537). Here, we studied the interplay between pressure‐ and agonist‐induced mechanisms of vasoconstriction in rat cererbal arteries. Elevating pressure from 10 to 60 mmHg caused myogenic constriction and an increase in LC20 phosphorylation. Subsequent exposure to serotonin (1 μM) at 60 mmHg evoked a further increase in pLC20 content and constriction. In contrast, a further increase in pLC20 was not detected when pressure was elevated after serotonin pretreatment despite the presence of a clear myogenic response. These results suggest that: 1) altered wall tension owing to agonist pretreatment affects the mechanism underlying pressure‐induced force generation, and 2) myogenic force generation may involve LC20‐independent mechanisms or require minimal additional (undetectable) LC20 phosphorylation when activated in the presence of agonist. (Funded by CIHR MOP‐97988, CIHR & AHFMR Fellowships)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".