Production and <i>In Vitro</i> Evaluation of Soy Protein–Based Biofilms as a Support for Human Keratinocyte and Fibroblast Culture
Bibliographic record
Abstract
This study presents results on soy protein isolate (SPI) biofilm production and the corresponding effect on the stability and toxicity of the derived films. SPI biofilms were prepared from SPI chemically treated with formaldehyde at various concentrations (0%, 1%, 2%, and 3%) as cross-linking agents. In vitro SPI biofilm degradation was evaluated as a function of water absorption leading to weight and size modifications. SPI biofilm toxicity was determined as a function of human keratinocyte and fibroblast adhesion, viability, and proliferation. Cytokine gene expression supported this using reverse transcriptase polymerase chain reaction techniques. Our results confirm that SPI can be used to produce biofilms. The resulting SPI biofilms without formaldehyde swell significantly, which leads to their physical instability. Formaldehyde treatment enhanced the mechanical properties of these biofilms by covalently cross-linking polypeptide chains. The decreased water absorption was dependent on the amount of formaldehyde present. SPI biofilms with 2% and 3% formaldehyde were highly stable and easier to manipulate than those with 0% and 1% formaldehyde. Tissue culture analyses revealed that the SPI biofilms without formaldehyde were non-toxic to human cells (keratinocytes and fibroblasts). The presence of formaldehyde in biofilms did not have any effects on cell viability, adhesion, or proliferation. This was supported by the high level of messenger RNA expression of interleukin-1 beta (IL-1beta) and tumor necrosis factor alpha by the keratinocytes and of IL-6 and IL-8 by the fibroblasts. Overall, we produced a stable, non-toxic soy protein support, which may be of potential interest in medical applications such as cell culture matrices and damaged tissue replacement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".