Live pancreatic acinar imaging of exocytosis using syncollin-pHluorin
Bibliographic record
Abstract
In this report, a novel live acinar exocytosis imaging technique is described. An adenovirus was engineered, encoding for an endogenous zymogen granule (ZG) protein (syncollin) fused to pHluorin, a pH-dependent green fluorescent protein (GFP). Short-term culture of mouse acini infected with this virus permits exogenous adenoviral protein expression while retaining acinar secretory competence and cell polarity. The syncollin-pHluorin fusion protein was shown to be correctly localized to ZGs, and the pH-dependent fluorescence of pHluorin was retained. Coupled with the use of a spinning disk confocal microscope, the syncollin-pHluorin fusion protein exploits the ZG luminal pH changes that occur during exocytosis to visualize exocytic events of live acinar cells in real-time with high spatial resolution in three dimensions. Apical and basolateral exocytic events were observed on stimulation of acinar cells with maximal and supramaximal cholecystokinin concentrations, respectively. Sequential exocytic events were also observed. Coupled with the use of transgenic mice and/or adenovirus-mediated protein expression, this syncollin-pHluorin imaging method offers a superior approach to studying pancreatic acinar exocytosis. This assay can also be applied to acinar disease models to elucidate the mechanisms implicated in pancreatitis.
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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 | 0.001 |
| 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".