Comparison of Two Human Skin Cell Isolation Protocols and Their Influence on Keratinocyte and Fibroblast Culture
Bibliographic record
Abstract
For the development of advanced therapies, the use of primary cells instead of cell lines is preferred. The manufacture of human tissue-engineered skin substitutes requires efficient isolation and culture protocols allowing a massive expansion of the cells in culture from an initial specimen of a minimal size. This study compared two skin cell isolation protocols, routinely applied in two clinical laboratories. Epithelial (keratinocytes) and dermal (fibroblasts) cells were isolated and cultured from three human skin biopsies (N = 3). The two-step digestion protocol (LOEX-Protocol) firstly used thermolysin to enzymatically disrupt the dermal–epidermal junction while, for the one-step digestion protocol (UPCIT-Protocol), mechanical detachment with scissors was applied. Then, the epidermal and dermal layers were digested, respectively, to achieve cell isolation. The cell size, viability, yield and growth were analyzed over five passages (P). The colony-forming efficiency (CFE) and Keratin 19 (K19) expression of epithelial cells were also assessed after P0 and P1. Regarding the dermal cells, no significant differences were observed in the tested parameters of isolation and culture. However, for the epithelial cells, viability was higher (93% vs. 85%) and the number of cells extracted per cm2 of skin was 3.4 times higher using the LOEX-Protocol compared to the UPCIT-Protocol. No significant difference was observed for any parameter once the keratinocytes were cultured from P1 to P4. The CFE and K19 expression decreased from P0 to P1 in both protocols, probably due to the culture process. This study shows that both protocols enable the efficient isolation of skin dermal and epithelial cells and subsequent culture to produce grafts destined for the treatment of patients.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".