Recent Trends in Biofabrication Technologies for Studying Skeletal Muscle Tissue-Related Diseases.
Recent Trends in Biofabrication Technologies for Studying Skeletal Muscle Tissue-Related Diseases.
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DOI：
10.3389/fbioe.2021.782333
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发表时间：
2021
影响因子：
5.7
通讯作者：
Jang J
中科院分区：
文献类型：
--
作者：
Cho S;Jang J
在天然骨骼肌中，密集的肌纤维与周围的运动神经元和血管紧密接触，这些神经元和血管嵌入纤维结缔组织中。与传统的二维（2D）培养物相比，三维（3D）工程化骨骼肌模型通过向细胞提供几何限制和生理基质刚度而允许与天然骨骼肌组织的结构和机械相似性。此外，施加到这些模型的各种外部刺激增强肌肉成熟沿着细胞-细胞和细胞-细胞外基质相互作用。因此，3D体外肌肉模型可以充分再现天然骨骼肌内组织-组织界面（如神经肌肉接头）中发生的病理生理事件。此外，3D肌肉模型可以通过掺入患者来源的诱导多能干细胞和人原代细胞来诱导人肌肉营养不良症（例如杜氏肌营养不良症）的病理表型。在这篇综述中，我们讨论了目前用于模拟各种骨骼肌组织相关疾病（即，肌肉疾病），包括肌营养不良和炎性肌肉疾病。特别是，这些方法将能够发现新的表型标记物和人类肌肉疾病与基因突变的机制研究。
In native skeletal muscle, densely packed myofibers exist in close contact with surrounding motor neurons and blood vessels, which are embedded in the fibrous connective tissue. In comparison to conventional two-dimensional (2D) cultures, the three-dimensional (3D) engineered skeletal muscle models allow structural and mechanical resemblance with native skeletal muscle tissue by providing geometric confinement and physiological matrix stiffness to the cells. In addition, various external stimuli applied to these models enhance muscle maturation along with cell–cell and cell–extracellular matrix interaction. Therefore, 3D in vitro muscle models can adequately recapitulate the pathophysiologic events occurring in tissue–tissue interfaces inside the native skeletal muscle such as neuromuscular junction. Moreover, 3D muscle models can induce pathological phenotype of human muscle dystrophies such as Duchenne muscular dystrophy by incorporating patient-derived induced pluripotent stem cells and human primary cells. In this review, we discuss the current biofabrication technologies for modeling various skeletal muscle tissue-related diseases (i.e., muscle diseases) including muscular dystrophies and inflammatory muscle diseases. In particular, these approaches would enable the discovery of novel phenotypic markers and the mechanism study of human muscle diseases with genetic mutations.
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影响因子：
29.4
作者：
Compton, Brett G.;Lewis, Jennifer A.
通讯作者：
Lewis, Jennifer A.
影响因子：
1.6
作者：
Alfano, Lindsay N.;Charleston, Jay S.;Lowes, Linda P.
通讯作者：
Lowes, Linda P.
影响因子：
39.3
作者：
Buyse, Gunnar M.;Van der Mieren, Gerry;Meier, Thomas
通讯作者：
Meier, Thomas
DOI：
10.1083/jcb.200405004
发表时间：
2004-09-13
期刊：
The Journal of cell biology
影响因子：
--
作者：
Engler AJ;Griffin MA;Sen S;Bönnemann CG;Sweeney HL;Discher DE
通讯作者：
Discher DE
影响因子：
13.6
作者：
Bhattacharjee T;Zehnder SM;Rowe KG;Jain S;Nixon RM;Sawyer WG;Angelini TE
通讯作者：
Angelini TE