Role of sarcoplasmic reticulum in regulation of tonic contraction of rabbit basilar artery
Bibliographic record
Abstract
Superficial sarcoplasmic reticulum (SR) regulates smooth muscle force development directly by Ca(2+) release and removal to and from the cytoplasm (Somlyo and Somlyo. J Cardiovasc Pharmacol 8, Suppl 8: S42-S47, 1986) by buffering Ca(2+) influx and contributing to Ca(2+) extrusion (Mueller and van Breemen. Nature 281: 682-683, 1979) and indirectly by releasing Ca(2+) near Ca(2+)-activated K(+) channels (K(Ca)) to hyperpolarize the plasma membrane (Bolton and Imaizumi. Cell Calcium 20: 141-152, 1996 and Nelson et al. Science 270: 633-637, 1995). In the rabbit basilar artery, relative contributions of direct effects and those mediated through activation of K(Ca) were evaluated by measuring force and intracellular Ca(2+) concentration ([Ca(2+)](i)) in response to the SR-depleting agents thapsigargin and ryanodine and the large conductance K(Ca) (BK(Ca)) blockers iberiotoxin (IbTX) and tetraethylammonium ion (TEA). A large contraction was observed in response to K(Ca) blockade with either 3 mM TEA or 100 nM IbTX and also after addition of 10 microM ryanodine or 2 microM thapsigargin. When K(Ca) was blocked first with TEA or IbTX, subsequent addition of thapsigargin or ryanodine also increased force. Measurements of fura 2 fluorescence showed parallel increases in [Ca(2+)](i) in response to sequential blockade of sarco(endo)plasmic reticulum Ca(2+)-ATPase and K(Ca) regardless of the order of application. It appears that a significant fraction of K(Ca) remains activated in the absence of SR function and that SR contributes to relaxation after blockade of K(Ca). We found that depletion of SR before stimulating Ca(2+) influx through voltage-gated Ca(2+) channels markedly reduced force development rate and that thapsigargin abolished this effect. We conclude that the SR of rabbit cerebral arteries modulates constriction by direct and indirect mechanisms.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".