Effects of Selective Endocrine or Exocrine Induction of AR42J on SNARE and Munc18 Protein Expression
Bibliographic record
Abstract
INTRODUCTION AND AIM: We used the amphicrine AR42J as an excellent model to study the differentiation of the secretory machinery of pancreatic endocrine and exocrine cells. Dexamethasone treatment induced the AR42J to differentiate towards the exocrine phenotype capable of secreting amylase in response to cholecystokinin. In contrast, activin A plus hepatocyte growth factor treatment of a subclone of AR42J, AR42J-B13, induced this cell to differentiate morphologically and functionally toward an insulin-containing and insulin-secreting endocrine phenotype. We took advantage of these unique properties of selective exocrine and endocrine induction of the AR42J to reveal which distinct combinations of exocytic SNARE complex proteins (syntaxin, SNAP-25 and VAMP) and associated Munc18 proteins were preferentially expressed to play a role in enzyme and insulin secretion. RESULTS AND CONCLUSION: To our surprise, both endocrine and exocrine induction of AR42J and AR42J-B13 caused very similar upregulation in the expression of the exocytic member isoforms of the syntaxin, SNAP-25, VAMP, and Munc18 families. We conclude that whereas the differentiation of the proximal components of the secretory machinery of the exocrine acinar and endocrine islet beta-cells is distinct, the differentiation of the distal components of exocytosis between these two cell types is very similar.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".