Effects of Serum-Free Culture at the Air–Liquid Interface in a Human Tissue-Engineered Skin Substitute
Bibliographic record
Abstract
Previous studies have reported that well-defined culture conditions can improve keratinocytes terminal differentiation and reproducibility. The aim of our study was to compare skin substitutes cultured in a complete medium with those cultured in a serum-free medium at the air-liquid interface to optimize the self-assembly method. Skin substitutes, cultured in a serum-free medium over 7, 14, and 21 days, were compared with others cultured in a complete medium (5% serum) over the complete culture period. Masson's Trichrome staining showed that the substitutes cultured in a serum-free medium generated a well-developed and differentiated epidermis. Immunolabeling analyses between the substitutes cultured without serum and those cultured in complete serum showed similar expression of epidermal differentiation markers, dermo-epidermal junction, and dermal extracellular matrix components. On the basis of our Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) results, the skin substitutes cultured in serum-free condition over 21 days of culture at the air-liquid interface showed lower frequencies of the CH(2) symmetric mode of vibrations, which means a better lipid organization of the stratum corneum. No significant difference in hydrocortisone penetration was observed between serum-free medium substitutes and the controls. Results demonstrate that the absence of serum does not compromise the characteristics of the skin substitutes observed in this study.
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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) | 0.000 | 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) | 0.001 | 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".