Modification of sarcoplasmic reticulum (SR) Ca<sup>2+</sup>release by FK506 induces defective excitation-contraction coupling only when SR Ca<sup>2+</sup>recycling is disturbed
Bibliographic record
Abstract
This study examined whether the effects of FK506-binding protein dissociation from sarcoplasmic reticulum (SR) Ca(2+) release channels on excitation-contraction (EC) coupling changed when SR Ca(2+) reuptake and (or) the trans-sarcolemmal Ca(2+) extrusion were altered. The steady-state twitch Ca(2+) transient (CaT), cell shortening, post-rest caffeine-induced CaT, and Ca(2+) sparks were measured in rat ventricular myocytes using laser-scanning confocal microscopy. In the normal condition, 50 micromol FK506/L significantly increased steady-state CaT, cell shortening, and post-rest caffeine-induced CaT. When the cells were solely perfused with thapsigargin, FK506 did not reduce any of the states, but when low [Ca(2+)](0) (0.1 mmol/L) was perfused additionally, FK506 reduced CaT and cell shortening, and accelerated the reduction of post-rest caffeine-induced CaT. FK506 significantly increased Ca(2+) spark frequency in the normal condition, whereas it mainly prolonged duration of individual Ca(2+) sparks under the combination of thapsigargin and low [Ca(2+)](0) perfusion. Modification of SR Ca(2+) release by FK506 impaired EC coupling only when released Ca(2+) could not be taken back into the SR and was readily extruded to the extracellular space. Our findings could partly explain the controversy regarding the contribution of FK506-binding protein dissociation to defective EC coupling.
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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".