Development and In Vitro Analysis of Layer-by-Layer Assembled Membranes for Potential Wound Dressing: Electrospun Curcumin/Gelatin as Middle Layer and Gentamicin/Polyvinyl Alcohol as Outer Layers.
Ssu-Meng HuangShih-Ming LiuHua-Yi TsengWen-Cheng ChenPublished in: Membranes (2023)
Nanofibrous membranes made of hydrogels have high specific surface areas and are suitable as drug carriers. Multilayer membranes fabricated by continuous electrospinning could delay drug release by increasing diffusion pathways, which is beneficial for long-term wound care. In this experiment, polyvinyl alcohol (PVA) and gelatin were used as membrane substrates, and a sandwich PVA/gelatin/PVA structure of layer-by-layer membranes was prepared by electrospinning under different drug loading concentrations and spinning times. The outer layers on both sides were citric-acid-crosslinked PVA membranes loaded with gentamicin as an electrospinning solution, and the middle layer was a curcumin-loaded gelatin membrane for the study of release behavior, antibacterial activity, and biocompatibility. According to the in vitro release results, the multilayer membrane could release curcumin slowly; the release amount was about 55% less than that of the single layer within 4 days. Most of the prepared membranes showed no significant degradation during immersion, and the phosphonate-buffered saline absorption rate of the multilayer membrane was about five to six times its weight. The results of the antibacterial test showed that the multilayer membrane loaded with gentamicin had a good inhibitory effect on Staphylococcus aureus and Escherichia coli . In addition, the layer-by-layer assembled membrane was non-cytotoxic but detrimental to cell attachment at all gentamicin-carrying concentrations. This feature could be used as a wound dressing to reduce secondary damage to the wound when changing the dressing. This multilayer wound dressing could be applied to wounds in the future to reduce the risk of bacterial infection and help wounds heal.
Keyphrases
- wound healing
- tissue engineering
- drug delivery
- escherichia coli
- staphylococcus aureus
- hyaluronic acid
- healthcare
- machine learning
- cancer therapy
- oxidative stress
- pseudomonas aeruginosa
- stem cells
- deep learning
- weight loss
- single cell
- body mass index
- climate change
- silver nanoparticles
- weight gain
- alcohol consumption
- chronic pain
- klebsiella pneumoniae