2D Is Better: Engineering Polydopamine into Cationic Nanosheets to Enhance Anti-Inflammatory Capability

ADVANCED HEALTHCARE MATERIALS(2024)

引用 0|浏览2
暂无评分
摘要
Polydopamine nanomaterials have emerged as one of the most popular organic materials for the management of oxidative stress-mediated inflammatory diseases. However, their current anti-inflammatory ability is still unsatisfactory because of limited phenolic hydroxyl groups, and oxidation reaction-medicated reactive oxygen and nitrogen species (RONS) scavenging. Herein, via fusing dimension engineering and surface charge engineering, 2D cationic polydopamine nanosheets (PDA NSs) capable of scavenging multiple danger signals to enhance anti-inflammatory capability are reported. Compared with conventional spherical polydopamine nanoparticles, 2D PDA NSs exhibit three- to fourfold enhancement in RONS scavenging capability, which should be attributed to high specific surface area and abundant phenol groups of 2D ultrathin structure. To further enhance the anti-inflammatory ability, polylysine molecules are absorbed on the surface of PDA NSs to endow the scavenging capability of cell-free DNA (cfDNA), another typical inflammatory factor to exacerbate the pathogenesis of inflammation. Molecular mechanisms reveal that cationic PDA NSs can concurrently activate Keap1-Nrf2 and block TLR9 signaling pathway, achieving synergistical inflammation inhibition. As a proof of concept, cationic PDA NSs with RONS and cfDNA dual-scavenging capability effectively alleviate the inflammatory bowel disease in both delayed and prophylactic models, much better than the clinical drug 5-aminosalicylic acid. It is reported that 2D cationic polydopamine nanosheets exhibit better anti-inflammatory effects than conventional spherical polydopamine nanoparticles for inflammatory bowel disease treatment, which should be attributed to dimension engineering and surface charge engineering. image
更多
查看译文
关键词
2D materials,cell-free DNA,inflammatory bowel disease,polydopamine nanosheets,ROS scavenging
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要