Incorporation of cell-adhesion peptides into collagen scaffolds promotes corneal epithelial stratification
Bibliographic record
Abstract
The objective of this study was to examine the effects of cell-adhesion peptides incorporated into collagen scaffolds on corneal epithelial cell stratification. Peptides (YIGSR, YIGSRIKVAV, IKVAVYIGSR and negative control YISGR) were first chemically attached to dendrimers. The peptide-modified dendrimers were then used as collagen cross-linkers. This permitted the incorporation of the peptides into the bulk structure of the collagen gels. The amount of peptide incorporated into the collagen gels was determined by 125I radiolabelling to be between 0.064 and 6.4 microg/mg collagen for YIGSR, and between 0.1187 to 11.87 microg/mg collagen for YIGSRIKVAV and IKVAVYIGSR. Corneal epithelial cell monolayers were grown on the surface of the collagen scaffolds and then exposed to conditions that promoted stratification as a stratified epithelial layer is desired in a tissue-engineered cornea. It was found that all of the incorporated peptides promoted stratification of the cells with the exception of the negative control YISGR. A synergistic effect of the combined sequences from laminin was observed, with the orientation of the peptide sequences having a great impact on the ability of the materials to promote cell stratification.
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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 | 0.000 | 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 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".