Suppr超能文献

使用光点击性明胶生物墨水挤出式 3D 生物打印功能性自支撑神经构建体。

Extrusion 3D bioprinting of functional self-supporting neural constructs using a photoclickable gelatin bioink.

机构信息

Department of Materials Science and Engineering, Monash Institute of Medical Engineering, Monash University, Clayton, Victoria 3800, Australia.

RMIT Centre for Additive Manufacturing, School of Engineering, RMIT University, Melbourne, Victoria 3000, Australia.

出版信息

Biofabrication. 2022 Jun 1;14(3). doi: 10.1088/1758-5090/ac6e87.

Abstract

Manymodels of neural physiology utilize neuronal networks established on two-dimensional substrates. Despite the simplicity of these 2D neuronal networks, substrate stiffness may influence cell morphology, network interactions and how neurons communicate and function. With this perspective, three-dimensional (3D) gel encapsulation is a powerful to recapitulating aspects offeatures, yet such an approach is often limited in terms of the level of resolution and feature size relevant for modelling aspects of brain architecture. Here, we report 3D bioplotting of rat primary cortical neural cells using a hydrogel system comprising gelatin norbornene (GelNB) and poly (ethylene glycol) dithiol (PEGdiSH). This bioink benefits from a rapid photo-click chemistry, yielding eight-layer crosshatch neural scaffolds and a filament width of 350m. The printability of this system depends on hydrogel concentration, printing temperature, extrusion pressure and speed. These parameters were studied via quantitative comparison between rheology and filament dimensions to determine the optimal printing conditions. Under optimal conditions, cell viability of bioprinted primary cortical neurons at day 1 (68 ± 2%) and at day 7 (68 ± 1%) were comparable to the 2D control group (72 ± 7%). The present study relates material rheology and filament dimensions to generate compliant free-standing neural constructs through bioplotting of low-concentration GelNB-PEGdiSH, which may provide a step forward to study 3D neuronal function and network formation.

摘要

许多神经生理学模型利用建立在二维基质上的神经元网络。尽管这些 2D 神经元网络很简单,但基质的硬度可能会影响细胞形态、网络相互作用以及神经元如何进行通信和发挥功能。从这个角度来看,三维(3D)凝胶包封是再现特征的有力方法,但这种方法通常在建模脑结构方面的分辨率和特征尺寸方面受到限制。在这里,我们使用包含明胶降冰片烯(GelNB)和聚乙二醇二巯基(PEGdiSH)的水凝胶系统报告大鼠原代皮质神经元的 3D 生物打印。这种生物墨水得益于快速的光点击化学,产生了 8 层交错的神经支架和 350m 的细丝宽度。该系统的可打印性取决于水凝胶浓度、打印温度、挤出压力和速度。通过流变学和细丝尺寸之间的定量比较研究了这些参数,以确定最佳打印条件。在最佳条件下,生物打印的原代皮质神经元在第 1 天(68 ± 2%)和第 7 天(68 ± 1%)的细胞活力与 2D 对照组(72 ± 7%)相当。本研究将材料流变学和细丝尺寸联系起来,通过低浓度 GelNB-PEGdiSH 的生物打印生成顺应性独立的神经结构,这可能是研究 3D 神经元功能和网络形成的一个进步。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验