戊二醛
纳米纤维
材料科学
明胶
静电纺丝
生物相容性
脚手架
膜
真皮
复合材料
复合数
壳聚糖
生物医学工程
化学工程
化学
聚合物
色谱法
冶金
工程类
解剖
医学
生物化学
作者
Ziyu Song,Jiajun Wang,Shaojie Tan,Jing Gao,Lu Wang
标识
DOI:10.1016/j.colsurfa.2022.130211
摘要
The treatment of severely damaged wounds is a serious challenge as these wounds have poor self-healing capacity, take longer to heal, and are prone to becoming chronic wounds. To solve this problem, PCL/gelatin electrospinning nanofiber membranes were combined with rGO-loaded chitosan non-woven fabrics to prepare biomimetic bilayer skin scaffolds. Among them, the PCL/gelatin nanofiber membrane was used to simulate the epidermis layer with a dense structure, and the chitosan non-woven fabric was used to simulate the dermis layer with a loose structure. When the concentration of the spinning solution was 7 %, and the average fiber diameter was 241 nm, HaCaTs had the best cell proliferation and adhesion, and the re-epithelialization process was fast. To enhance the induction effect of scaffolds on dermal cells, the electroactive substance rGO was used to give the scaffold electrical conductivity. Considering the biocompatibility, the concentration of GO dispersion was controlled at 1 mg/mL, and the obtained CHI@ 1rGO scaffolds had high conductivity, as well as the improved mitochondrial membrane potential of HFF-1 s which increased cell viability. So the induction of HFF-1 s migration was obvious. After cross-linking composite scaffolds with glutaraldehyde, the scaffolds still showed good cytocompatibility, at the same time, the peel strength was increased from 7.21 cN to 350 cN, and the structural stability of the nanofiber membrane layer in the liquid environment was also enhanced. Both the moisture absorption and moisture permeability of composite scaffolds were improved, which could maintain the moist environment of the wound to a certain extent. Altogether, results showed that electroactive biomimetic bilayer fibrous scaffolds have great application potential in promoting skin tissue regeneration.
科研通智能强力驱动
Strongly Powered by AbleSci AI