Function-specific calcium stores selectively regulate growth hormone secretion, storage, and mRNA level
Bibliographic record
Abstract
Ca(+) stores may regulate multiple components of the secretory pathway. We examined the roles of biochemically independent intracellular Ca(2+) stores on acute and long-term growth hormone (GH) release, storage, and mRNA levels in goldfish somatotropes. Thapsigargin-evoked intracellular Ca(2+) concentration ([Ca(2+)](i)) signal amplitude was similar to the Ca(2+)-mobilizing agonist gonadotropin-releasing hormone, but thapsigargin (2 microM) did not acutely increase GH release, suggesting uncoupling between [Ca(2+)](i) and exocytosis. However, 2 microM thapsigargin affected long-term secretory function. Thapsigargin-treated cells displayed a steady secretion of GH (2, 12, and 24 h), which decreased GH content (12 and 24 h), but not GH mRNA/production (24 h). In contrast to the results with thapsigargin, activating the ryanodine (Ry) receptor (RyR) with 1 nM Ry transiently increased GH release (2 h). Prolonged activation of RyR (24 h) reduced GH release, contents and apparent production, without changing GH mRNA levels. Inhibiting RyR with 10 microM Ry increased GH mRNA levels, production, and storage (2 h). Increasing [Ca(2+)](i) independently of Ca(2+) stores with the use of 30 mM KCl decreased GH mRNA. Collectively, these results suggest that parts of the secretory pathway can be controlled independently by function-specific Ca(2+) stores.
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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 | 0.001 | 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".