Adhesion Characteristics of Human Pancreatic Islets, Duct Epithelial Cells, and Acinar Cells to a Polymer Scaffold
Bibliographic record
Abstract
We reported in 2018 that among several extracellular matrices, fibronectin, type I collagen, type IV collagen, laminin I, fibrinogen, and bovine serum albumin, fibronectin is particularly useful for adhesion of porcine pancreatic tissue. Subsequently, we developed a technology that enables the chemical coating of the constituent motifs of fibronectin onto cell culture dishes. In this experiment, we used islets (purity ≥ 90%), duct epithelial cells (purity ≥ 60%), and acinar cells (purity ≥ 99%) isolated from human pancreas according to the Edmonton protocol published in 2000 and achieved adhesion to the constituent motifs of fibronectin. A solution including cGMP Prodo Islet Media was used as the assay solution. In islets, adhesion was enhanced with the constitutive motifs of fibronectin compared with uncoated islets. In the functional evaluation of islets, insulin mRNA expression and insulin secretion were enhanced by the constitutive motif of fibronectin compared with non-coated islets. The stimulation index was comparable between non-coated islets and fibronectin motifs. In duct epithelial cells, adhesion was mildly promoted by the fibronectin component compared with non-coated component, while in acinar cells, adhesion was inhibited by the fibronectin component compared with the non-coated component. These data suggest that the constitutive motifs of fibronectin are useful for the adhesion of islets and duct epithelial cells.
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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".