Clusterin Expression in the Early Process of Pancreas Regeneration in the Pancreatectomized Rat
Bibliographic record
Abstract
We have previously reported upregulation of clusterin at the time of islet cell regeneration after beta-cell injury. This led us to speculate that clusterin might be involved in the neogenic regeneration of the pancreas. Clusterin expression was examined throughout the process of pancreatic neogenesis in pancreatectomized rats. For in vitro analysis, duct cells were isolated from the rat pancreas and clusterin cDNA was transfected for its overexpression. Clusterin and its mRNA increased significantly in the early phase of regeneration, particularly at 1-3 days after pancreatectomy. Clusterin was transiently expressed in the differentiating acinar cells but faded afterwards. Interestingly, these clusterin cells were negative for PCNA (proliferating cell nuclear antigen), whereas most epithelial cells in ductules in the regenerating tissue showed extensive proliferative activity. Clusterin expression was also detected in some endocrine cells of the regenerating tissue. Transfection of clusterin cDNA into primary cultured duct cells resulted in a 2.5-fold increase in cell proliferation and induced transformation of non-differentiated duct cells into differentiated cells displaying cytokeratin immunoreactivity. Taken together, these results suggest that clusterin may play essential roles in the neogenic regeneration of pancreatic tissue by stimulating proliferation and differentiation of duct cells.
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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 | 0.001 | 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 | 0.001 |
| 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".