Accumulation of Synaptosomal-Associated Protein of 25 kDa (SNAP-25) and Other Proteins Associated with the Secretory Pathway in GH4C1 Cells Upon Treatment with Estradiol, Insulin, and Epidermal Growth Factor*
Bibliographic record
Abstract
Treatment of rat pituitary GH4C1 cells with estradiol, insulin, and epidermal growth factor induces secretory granule accumulation, PRL storage, and stabilization of ICA512, a membrane protein associated with secretory granules. In these investigations we found that the same treatment induced accumulation over 2-fold of other proteins in the secretory pathway, including synaptosomal-associated protein of 25 kDa (SNAP-25), synaptotagmin III, synaptobrevin, synaptophysin, and cyclophilin B, and did not affect accumulation of others, including synaptotagmin I, calnexin, and glucose-regulated protein 94. The induction of proteins was not a coordinate event, because epidermal growth factor alone maximally stimulated SNAP-25 accumulation, but not that of synaptotagmin III. Induction of SNAP-25 accumulation occurred without an increase in its synthesis, and induction of cyclophilin B occurred without an increase in its messenger RNA accumulation, suggesting that accumulation may be caused by stabilization of the proteins. SNAP-25 immunofluorescence was located in the cytoplasm and on the plasma membrane and sometimes was heavily concentrated in protrusions from the cell surface, especially in hormone-treated cells. Frequenin immunofluorescence was also sometimes concentrated in intense patches, but did not colocalize with SNAP-25. Growth hormone and prolactin immunofluorescence was not found in the protrusions and sometimes did not colocalize with each other when they were present in the same cell. Hormone treatment of GH4C1 cells therefore induces accumulation of specific proteins in all parts of the secretory pathway and causes morphological changes in addition to accumulating secretory granules.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".