Purified Human Pancreatic Duct Cell Culture Conditions Defined by Serum-Free High-Content Growth Factor Screening
Bibliographic record
Abstract
The proliferation of pancreatic duct-like CK19+ cells has implications for multiple disease states including pancreatic cancer and diabetes mellitus. The in vitro study of this important cell type has been hampered by their limited expansion compared to fibroblast-like vimentin+ cells that overgrow primary cultures. We aimed to develop a screening platform for duct cell mitogens after depletion of the vimentin+ population. The CD90 cell surface marker was used to remove the vimentin+ cells from islet-depleted human pancreas cell cultures by magnetic-activated cell sorting. Cell sorting decreased CD90+ cell contamination of the cultures from 34±20% to 1.3±0.6%, yielding purified CK19+ cultures with epithelial morphology. A full-factorial experimental design was then applied to test the mitogenic effects of bFGF, EGF, HGF, KGF and VEGF. After 6 days in test conditions, the cells were labelled with BrdU, stained and analyzed by high-throughput imaging. This screening assay confirmed the expected mitogenic effects of bFGF, EGF, HGF and KGF on CK19+ cells and additionally revealed interactions between these factors and VEGF. A serum-free medium containing bFGF, EGF, HGF and KGF led to CK19+ cell expansion comparable to the addition of 10% serum. The methods developed in this work should advance pancreatic cancer and diabetes research by providing effective cell culture and high-throughput screening platforms to study purified primary pancreatic CK19+ 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".