<i>In vitro</i> comparison of human plasma-based and self-assembled tissue-engineered skin substitutes: two different manufacturing processes for the treatment of deep and difficult to heal injuries
Bibliographic record
Abstract
Abstract Background The aim of this in vitro study was to compare side-by-side two models of human bilayered tissue-engineered skin substitutes (hbTESSs) designed for the treatment of severely burned patients. These are the scaffold-free self-assembled skin substitute (SASS) and the human plasma-based skin substitute (HPSS). Methods Fibroblasts and keratinocytes from three humans were extracted from skin biopsies (N = 3) and cells from the same donor were used to produce both hbTESS models. For SASS manufacture, keratinocytes were seeded over three self-assembled dermal sheets comprising fibroblasts and the extracellular matrix they produced (n = 12), while for HPSS production, keratinocytes were cultured over hydrogels composed of fibroblasts embedded in either plasma as unique biomaterial (Fibrin), plasma combined with hyaluronic acid (Fibrin-HA) or plasma combined with collagen (Fibrin-Col) (n/biomaterial = 9). The production time was 46–55 days for SASSs and 32–39 days for HPSSs. Substitutes were characterized by histology, mechanical testing, PrestoBlue™-assay, immunofluorescence (Ki67, Keratin (K) 10, K15, K19, Loricrin, type IV collagen) and Western blot (type I and IV collagens). Results The SASSs were more resistant to tensile forces (p-value &lt; 0.01) but less elastic (p-value &lt; 0.001) compared to HPSSs. A higher number of proliferative Ki67+ cells were found in SASSs although their metabolic activity was lower. After epidermal differentiation, no significant difference was observed in the expression of K10, K15, K19 and Loricrin. Overall, the production of type I and type IV collagens and the adhesive strength of the dermal-epidermal junction was higher in SASSs. Conclusions This study demonstrates, for the first time, that both hbTESS models present similar in vitro biological characteristics. However, mechanical properties differ and future in vivo experiments will aim to compare their wound healing potential.
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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) | 0.001 | 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".