Nano-silver-decorated microfibrous eggshell membrane: processing, cytotoxicity assessment and optimization, antibacterial activity and wound healing
Bibliographic record
Abstract
An ideal wound dressing can both promote wound healing and prevent bacterial infection. Here, we report a potential dressing prepared by incorporating an optimized concentration of silver nanoparticles (AgNPs) into the microfibers of a natural eggshell membrane (EM) using environmentally friendly and mussel-inspired dopamine. Briefly, acid-treated EM was used as a porous membrane for polydopamine-reduced AgNPs synthesis. To obtain the optimal cytocompatible silver concentration, cellular attachment and MTT assay were performed with different concentrations of AgNPs. The morphology of the EM and AgNPs was confirmed by scanning electronic microscopy, scanning transmission electronic microscopy and Fourier transform infrared spectroscopy. The synthesized EM/AgNPs exhibited steady and safe AgNPs release, which was further tested for antibacterial activity against Escherichia coli and Staphylococcus aureus by disc diffusion method and bacterial suspension assay. Finally, in a murine full-thickness skin wound model, we found that EM/AgNPs could promote re-epithelialization, granulation tissue formation and wound healing via enhancing cell proliferation, as demonstrated by the expression of proliferating cell nuclear antigen (PCNA), and controlling inflammation response, as demonstrated by the expression of interleukin-1β (IL-1β). These findings suggest that EM/AgNPs may have a promising application in wound management.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".