Sustained Contraction in Vascular Smooth Muscle by Activation of L-type Ca2+ Channels Does Not Involve Ca2+ Sensitization or Caldesmon
Bibliographic record
Abstract
channels (LTCC). This study used a pharmacological agonist of LTCC, Bay K8644, to elicit a sustained, sub-maximal contraction in VSM that mimics tone. Downstream signaling was investigated in order to determine what molecules are responsible for tone. Medial strips of swine carotid artery were stimulated with 100 nM Bay K8644 to induce a sustained level of force. Force and phosphorylation levels of myosin light chain (MLC), MAP kinase, MYPT1, CPI-17, and caldesmon were measured during Bay K8644 stimulation in the presence and absence of nifedipine, ML-7, U0126, bisindolylmaleimide (Bis), and H-1152. Nifedipine and ML-7 inhibited force and MLC phosphorylation in response to Bay K8644. Inhibition of Rho kinase (H-1152) but not PKC (Bis) inhibited Bay K8644 induced force. U0126 significantly increased Bay K8644-dependent force with no effect on MLC phosphorylation. Neither CPI-17 nor caldesmon phosphorylation were increased during the maintenance of sustained force. Our results suggest that force due to the influx of calcium through LTCCs is partially MLC phosphorylation-dependent but does not involve PKC or caldesmon. Interestingly, inhibition of MLC kinase (MLCK) and PKC significantly increased MAP kinase phosphorylation suggesting that MLCK and PKC may directly or indirectly inhibit MAP kinase activity during prolonged contractions induced by Bay K8544.
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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) | 0.001 | 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".