Rho‐kinase mediates diphosphorylation of myosin regulatory light chain in cultured uterine, but not vascular smooth muscle cells
Bibliographic record
Abstract
Phosphorylation of myosin regulatory light chain (RLC) triggers contraction in smooth muscle myocytes. Dephosphorylation of phosphorylated RLC (pRLC) is mediated by myosin RLC phosphatase (MLCP), which is negatively regulated by rho-associated kinase (ROK). We have compared basal and stimulated concentrations of pRLC in myocytes from human coronary artery (hVM), which has a tonic contractile pattern to myocytes from human uterus (hUM), which has a phasic contractile pattern. Our studies reveal fundamental differences between hVM and hUM regarding the mechanisms regulating phosphorylation RLC. Whereas hVM responded to stimulation by phosphorylation of RLC at S19, hUM responded by forming diphosphorylated RLC (at T18 and S19; ppRLC), which, compared to pRLC, causes two to threefold greater activation of myosin ATPase that provides energy to power the contraction. Importantly, the conversion of pRLC to ppRLC is mediated by ROK. In hUM, MLCP has high activity for ppRLC and this is inhibited by ROK through phosphorylation of the substrate targeting subunit (MYPT1) at T853. Inhibitors of ROK significantly reduce contractility in both hVM and hUM. We demonstrated that inhibition of ppRLC in phasic myocytes (hUM) is 100-fold more sensitive to ROK inhibitors than is pRLC in tonic myocytes (hVM). We speculate that these differences in phosphorylation of RLC might reflect evolution of different contractile patterns to perform distinct physiological functions. Furthermore, our data suggest that low concentrations of ROK inhibitors might inhibit uterine contractions with minimal effects on vascular tone, thus posing a novel strategy for prevention or treatment of conditions such as preterm birth.
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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 | 0.000 |
| 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".