Emulsion template fabricated gelatin-based scaffold functionalized by dialdehyde starch complex with antibacterial antioxidant properties for accelerated wound healing

明胶 淀粉 乳状液 微观结构 材料科学 抗菌活性 抗氧化剂 化学工程 脚手架 多孔性 化学 生物医学工程 复合材料 有机化学 细菌 工程类 生物 医学 遗传学
作者
Tao Long,Ting Xu,Rui Li,Zhilang Xu,Defu Li,Changdao Mu,Lun Yuan,Yandong Mu
出处
期刊:International Journal of Biological Macromolecules [Elsevier BV]
卷期号:254: 127918-127918 被引量:3
标识
DOI:10.1016/j.ijbiomac.2023.127918
摘要

Gelatin and starch are considered as promising sustainable materials for their abundant production and good biodegradability. Efforts have been made to explore their medical application. Herein, scaffolds based on gelatin and starch with a preferred microstructure and antibacterial antioxidant property were fabricated by the emulsion template method. The dialdehyde starch was firstly combined with silver nanoparticles and curcumin to carry out the efficient hybrid antibacterial agent. Then, the gelatin microsphere of appropriate size was prepared by emulsification and gathered by the above agent to obtain gelatin-based scaffolds. The prepared scaffolds showed porous microstructures with high porosity of over 74 % and the preferred pore sizes of ∼65 μm, which is conducive to skin regeneration. Moreover, the scaffolds possessed a good swelling ability of over 640 %, good degradability of over 18 days, excellent blood compatibility, and cell compatibility. The promising antibacterial and antioxidant properties came from the hybrid antibacterial agent were affirmed. As expected, the gelatin-based scaffolds fabricated by the emulsion template method with a preferred microstructure can facilitate more adhered fibroblasts. In summary, gelatin-based scaffolds functionalized by starch-based complex expanded the application of abundant sustainable materials in the biomedical field, especially as antibacterial antioxidant wound dressings.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
REBACK发布了新的文献求助10
刚刚
科研通AI5应助ni采纳,获得10
刚刚
1秒前
rora完成签到 ,获得积分10
1秒前
lllll完成签到,获得积分10
2秒前
2秒前
充电宝应助金雪采纳,获得10
3秒前
上官若男应助小酒窝采纳,获得10
3秒前
3秒前
吃猫的鱼发布了新的文献求助10
4秒前
4秒前
1111完成签到,获得积分10
4秒前
Little发布了新的文献求助10
5秒前
5秒前
李健应助儒雅新波采纳,获得10
5秒前
迷路诗蕊发布了新的文献求助10
5秒前
tomato039完成签到,获得积分10
6秒前
徐先生1106完成签到,获得积分10
6秒前
科研通AI5应助DK采纳,获得10
7秒前
7秒前
洪对对发布了新的文献求助10
7秒前
hahah发布了新的文献求助10
7秒前
unite 小丘完成签到,获得积分10
8秒前
高婧红关注了科研通微信公众号
8秒前
勤劳的曼易完成签到,获得积分10
8秒前
胖虎啊发布了新的文献求助10
8秒前
yy完成签到,获得积分10
8秒前
李健应助诺笙采纳,获得10
9秒前
桐桐应助科研通管家采纳,获得10
9秒前
9秒前
良辰应助科研通管家采纳,获得10
9秒前
9秒前
脑洞疼应助科研通管家采纳,获得10
9秒前
MX应助科研通管家采纳,获得20
9秒前
无花果应助科研通管家采纳,获得10
9秒前
SciGPT应助科研通管家采纳,获得10
9秒前
Akim应助科研通管家采纳,获得10
9秒前
星辰大海应助科研通管家采纳,获得10
10秒前
烟花应助科研通管家采纳,获得10
10秒前
久伴久爱完成签到 ,获得积分10
10秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
English language teaching materials : theory and practice 200
Parallel Optimization 200
Deciphering Earth's History: the Practice of Stratigraphy 200
New Syntheses with Carbon Monoxide 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3835595
求助须知:如何正确求助?哪些是违规求助? 3377959
关于积分的说明 10501323
捐赠科研通 3097529
什么是DOI,文献DOI怎么找? 1705876
邀请新用户注册赠送积分活动 820756
科研通“疑难数据库(出版商)”最低求助积分说明 772226