Guided neural stem cell differentiation by dynamic loading of 3D printed elastomeric scaffolds

IF 3.3 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Yi Yang , Abdullah Revaha Akdemir , Rafsan Ahmed Rashik , Omar Ahmad Shihadeh Khater , Zijian Weng , Long Wang , Ying Zhong , Nathan D. Gallant
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引用次数: 0

Abstract

The limited regenerative ability of “permanent” cells is a major barrier to treating conditions like spinal cord injury (SCI) and myocardial infarction (MI). The delivery of stem cells, which can generate various cell types, offer potential for personalized therapy with reduced immunoreaction and recovery time. However, restoring function to these tissues also requires new or replacement cells to align properly. Neurons, for example, must organize and extend parallel axons, mimicking their natural structure for directional signal propagation. Current stem cell differentiation methods lack guidance, resulting in randomly distributed axons and limited repair effectiveness. Advancing methods and materials to guide stem cell differentiation into functional, aligned nerve bundles is crucial for improving SCI treatment outcomes. This study aimed to develop an in vitro system to promote aligned neural differentiation by applying cyclic uniaxial tension to PC-12 stem cells adhered to 3D-printed elastic scaffolds. We created a simple loading device which can apply cyclic and controllable stretching force to a scaffold, which in turn transmits uniaxial tension to cells adhered to the scaffold during their differentiation. An elastomer ink for 3D printing scaffolds was formulated and surface treatment processes were investigated to enhance the cell-scaffold adhesion to support the dynamic loading. It was revealed that a corona discharge treatment while the scaffold is soaked with type I collagen can significantly enhance cell adhesion. A range of strain magnitudes and frequencies were revealed to enhance the differentiation of neural tissue derived PC-12 cells to neuron cells and increase the length of their neurites up to 76%. The combination of 3% maximum strain and 1 Hz loading frequency maximized differentiation and neurite extension. These findings demonstrate that dynamic mechanical stimulation enhances neural differentiation and organization, offering an alternative approach for regenerative therapies targeting SCI and similar conditions.
通过动态加载三维打印弹性支架引导神经干细胞分化
“永久性”细胞有限的再生能力是治疗脊髓损伤(SCI)和心肌梗死(MI)等疾病的主要障碍。干细胞的输送可以产生各种细胞类型,为减少免疫反应和恢复时间的个性化治疗提供了潜力。然而,恢复这些组织的功能也需要新的或替代细胞来正确排列。例如,神经元必须组织和扩展平行轴突,模仿它们的自然结构来进行定向信号传播。目前的干细胞分化方法缺乏引导,导致轴突随机分布,修复效果有限。改进方法和材料,引导干细胞分化成功能一致的神经束,对于改善脊髓损伤治疗效果至关重要。本研究旨在通过对3d打印弹性支架粘附的PC-12干细胞施加循环单轴张力,建立促进定向神经分化的体外系统。我们创造了一种简单的加载装置,它可以对支架施加循环和可控的拉伸力,从而在支架分化过程中将单轴拉力传递给粘附在支架上的细胞。制备了一种用于3D打印支架的弹性体墨水,并研究了表面处理工艺以增强细胞-支架的粘附力以支持动态载荷。结果表明,电晕放电处理同时浸泡I型胶原蛋白可显著增强细胞粘附。结果表明,在一定的应变强度和频率范围内,神经组织来源的PC-12细胞向神经元细胞分化,其神经突长度可增加76%。3%最大应变和1hz加载频率的组合使分化和神经突延伸最大化。这些发现表明,动态机械刺激可以增强神经分化和组织,为针对脊髓损伤和类似疾病的再生治疗提供了另一种方法。
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来源期刊
Journal of the Mechanical Behavior of Biomedical Materials
Journal of the Mechanical Behavior of Biomedical Materials 工程技术-材料科学:生物材料
CiteScore
7.20
自引率
7.70%
发文量
505
审稿时长
46 days
期刊介绍: The Journal of the Mechanical Behavior of Biomedical Materials is concerned with the mechanical deformation, damage and failure under applied forces, of biological material (at the tissue, cellular and molecular levels) and of biomaterials, i.e. those materials which are designed to mimic or replace biological materials. The primary focus of the journal is the synthesis of materials science, biology, and medical and dental science. Reports of fundamental scientific investigations are welcome, as are articles concerned with the practical application of materials in medical devices. Both experimental and theoretical work is of interest; theoretical papers will normally include comparison of predictions with experimental data, though we recognize that this may not always be appropriate. The journal also publishes technical notes concerned with emerging experimental or theoretical techniques, letters to the editor and, by invitation, review articles and papers describing existing techniques for the benefit of an interdisciplinary readership.
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