<scp>ERK</scp> and p38<scp>MAPK</scp> pathways regulate myosin light chain phosphatase and contribute to Ca<sup>2+</sup> sensitization of intestinal smooth muscle contraction
Bibliographic record
Abstract
BACKGROUND: Mitogen-activated protein kinases (MAPKs), including extracellular signal-regulated protein kinase (ERK) and p38MAPK, are known regulators of smooth muscle contractility. The contraction of smooth muscle is mainly regulated by the phosphorylation of regulatory light chains of myosin II (LC20), which is driven by the balance between myosin light chain kinase (MLCK) and myosin light chain phosphatase (MLCP). We hypothesized that one possible mechanism for MAPK-dependent modulation of intestinal smooth muscle contractility is via the regulation of MLCP activity. METHODS: Contractile responses to carbachol (CCh) and effects of MAPK inhibitors on CCh-induced contractions were assessed with isolated rat ileal longitudinal smooth muscle strips. Biochemical assessments of MLCP activity and myosin phosphatse targeting subunit (MYPT1) and CPI-17 phosphorylations were completed. KEY RESULTS: Treatment of ileal smooth muscle with PD98059 (10 μM; MEK inhibitor) or SB203580 (10 μM; p38MAPK inhibitor) significantly inhibited CCh-induced contractile force. Decreased MLCP activity was observed during sustained contractions induced by CCh; the MLCP activity was recovered by treatment with PD98059 and SB203580. However, MYPT1 (Thr697 and Thr855) and CPI-17 (Thr38) phosphorylations were not affected. Application of ML-7 (MLCK inhibitor) during CCh-induced sustained contraction elicited an MLCP-dependent relaxation, the rate of which was accelerated by application of PD98059 and SB203580 with proportional changes in LC20 phosphorylation levels but not MYPT1 phosphorylation (Thr697 or Thr855). CONCLUSIONS & INFERENCES: ERK and p38MAPK contribute to CCh-induced sustained contraction in a LC20 phosphorylation dependent manner. Moreover, both kinases inhibit MLCP activity possibly by a novel mechanism.
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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) | 0.000 | 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) | 0.005 | 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".