Harvesting the Potential of the Human Umbilical Cord: Isolation and Characterisation of Four Cell Types for Tissue Engineering Applications
Bibliographic record
Abstract
The human umbilical cord (UC) has attracted interest as a source of cells for many research applications. UC solid tissues contain four cell types: epithelial, stromal, smooth muscle and endothelial cells. We have developed a unique protocol for the sequential extraction of all four cell types from a single UC, allowing tissue reconstruction using multiple cell types from the same source. By combining perfusion, immersion and explant techniques, all four cell types have been successfully expanded in monolayer cultures. We have also characterised epithelial and Wharton's jelly cells (WJC) by immunolabelling of specific proteins. Epithelial cell yields averaged at 2.3 × 10(5) cells per centimetre UC, and the cells expressed an unusual combination of keratins typical of simple, mucous and stratified epithelia. Stromal cells in the Wharton's jelly expressed desmin, α-smooth muscle actin, elastin, keratins (K12, K16, K18 and K19), vimentin and collagens. Expression patterns in cultured cells resembled those found in situ except for basement membrane components and type III collagen. These stromal cells featured a sustained proliferation rate up to passage 12 after thawing. The mesenchymal stem cell (MSC) character of the WJC was confirmed by their expression of typical MSC surface markers and by adipogenic and osteogenic differentiation assays. To emphasise and demonstrate their potential for regenerative medicine, UC cell types were successfully used to produce human tissue-engineered constructs. Both bilayered stromal/epithelial and vascular substitutes were produced, establishing the versatility and importance of these cells for research and therapeutic applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".