巨噬细胞
化学
炎症
脂多糖
一氧化氮
己内酯
体外
脚手架
细胞培养
药理学
细胞生物学
生物医学工程
生物化学
免疫学
生物
医学
有机化学
聚合物
共聚物
遗传学
作者
Xiang Wang,Yujia Cao,Linzhi Jing,Siyu Chen,Bin Leng,Xin Yang,Zhiyuan Wu,Jun Bian,Ratana Banjerdpongchai,Juthathip Poofery,Dejian Huang
出处
期刊:ACS applied bio materials
[American Chemical Society]
日期:2021-10-12
卷期号:4 (11): 7967-7978
被引量:2
标识
DOI:10.1021/acsabm.1c00889
摘要
Inflammation plays an essential role in the human immune system, and anti-inflammatory compounds are important to promote health. However, the in vitro screening of these compounds is largely dependent on flat biology. Herein, we report our efforts in establishing a 3D inflammation murine macrophage model. Murine macrophage RAW 264.7 cells were cultured on poly(ε-caprolactone) (PCL) scaffolds fabricated through an electrohydrodynamic jetting 3D printer and their behavior were examined. Cells on PCL scaffolds showed a 3D shape and morphology with multilayers and a lower proliferation rate. Moreover, macrophages were not activated by scaffold material PCL and 3D microenvironment. The 3D cells showed greater sensitivity to lipopolysaccharide stimulation with higher production activity of nitric oxide (NO), nitric oxide synthases (iNOS), and cyclooxygenase-2 (COX-2). Additionally, the 3D macrophage model showed lower drug sensitivity to commercial anti-inflammatory drugs including aspirin, ibuprofen, and dexamethasone, and natural flavones apigenin and luteolin with higher IC50 for NO production and lower iNOS and COX-2 inhibition efficacy. Overall, the 3D macrophage model showed promise for higher accurate screening of anti-inflammatory compounds. We developed, for the first time, a 3D macrophage model based on a 3D-printed PCL scaffold that provides an extracellular matrix environment for cells to grow in the 3D dimension. 3D-grown RAW 264.7 cells showed different sensitivities and responses to anti-inflammatory compounds from its 2D model. The 3D cells have lower sensitivity to both commercial and natural anti-inflammatory compounds. Consequently, our 3D macrophage model could be applied to screen anti-inflammatory compounds more accurately and thus holds great potential in next-generation drug screening applications.
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