Characterization of Ca<sup>2+</sup>release from heterogeneous Ca<sup>2+</sup>stores in sarcoplasmic reticulum isolated from arterial and gastric smooth muscle
Bibliographic record
Abstract
Ca2+ transport was investigated in vesicles of sarcoplasmic reticulum subfractionated from bovine main pulmonary artery and porcine gastric antrum using digitonin binding and zonal density gradient centrifugation. Gradient fractions recovered at 15-33% sucrose were studied as the sarcoplasmic reticulum component using Fluo-3 fluorescence or 45Ca2+ Millipore filtration. Thapsigargin blocked active Ca2+ uptake and induced a slow Ca2+ release from actively loaded vesicles. Unidirectional 45Ca2+ efflux from passively loaded vesicles showed multicompartmental kinetics. The time course of an initial fast component could not be quantitatively measured with the sampling method. The slow release had a half-time of several minutes. Both components were inhibited by 20 microM ruthenium red and 10 mM Mg2+. Caffeine, inositol 1,4,5-trisphosphate, ATP, and diltiazem accelerated the slow component. A Ca2+ release component activated by ryanodine or cyclic adenosine diphosphate ribose was resolved with Fluo-3. Comparison of tissue responses showed that the fast Ca2+ release was significantly smaller and more sensitive to inhibition by Mg2+ and ruthenium red in arterial vesicles. They released more Ca2+ in response to inositol 1,4,5-trisphosphate and were more sensitive to activation by cyclic adenosine diphosphate ribose. Ryanodine and caffeine, in contrast, were more effective in gastric antrum. In each tissue, the fraction of the Ca2+ store released by sequential application of caffeine and inositol 1,4,5-trisphosphate depended on the order applied and was additive. The results indicate that sarcoplasmic reticulum purified from arterial and gastric smooth muscle represents vesicle subpopulations that retain functional Ca2+ channels that reflect tissue-specific pharmacological modulation. The relationship of these differences to physiological responses has not been determined.
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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) | 0.000 | 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".