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首页> 外文期刊>Microscopy and microanalysis: The official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada >Quantification of Cardiomyocyte Alignment from Three-Dimensional (3D) Confocal Microscopy of Engineered Tissue
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Quantification of Cardiomyocyte Alignment from Three-Dimensional (3D) Confocal Microscopy of Engineered Tissue

机译:从工程组织三维(3D)共聚焦显微镜的心肌细胞对齐量化

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摘要

Biological tissues have complex, three-dimensional (3D) organizations of cells and matrix factors that provide the architecture necessary to meet morphogenic and functional demands. Disordered cell alignment is associated with congenital heart disease, cardiomyopathy, and neurodegenerative diseases and repairing or replacing these tissues using engineered constructs may improve regenerative capacity. However, optimizing cell alignment within engineered tissues requires quantitative 3D data on cell orientations and both efficient and validated processing algorithms. We developed an automated method to measure local 3D orientations based on structure tensor analysis and incorporated an adaptive subregion size to account for multiple scales. Our method calculates the statistical concentration parameter, kappa, to quantify alignment, as well as the traditional orientational order parameter. We validated our method using synthetic images and accurately measured principal axis and concentration. We then applied our method to confocal stacks of cleared, whole-mount engineered cardiac tissues generated from human-induced pluripotent stem cells or embryonic chick cardiac cells and quantified cardiomyocyte alignment. We found significant differences in alignment based on cellular composition and tissue geometry. These results from our synthetic images and confocal data demonstrate the efficiency and accuracy of our method to measure alignment in 3D tissues.
机译:生物组织具有复杂的三维(3D)组织的细胞和矩阵因子,其提供满足形态发生和功能性需求所必需的结构。无序的细胞对齐与先天性心脏病,心肌病和神经变性疾病和修复或更换这些组织的使用工程化构建能力可以提高再生能力。然而,优化工程组织内的细胞对准需要关于单元方向的定量3D数据以及有效和验证的处理算法。我们开发了一种自动化方法,用于基于结构张量分析来测量局部3D方向,并结合了自适应子区域大小以考虑多个尺度。我们的方法计算统计浓度参数Kappa,以量化对准,以及传统的方向顺序参数。我们使用合成图像和精确测量主轴和浓度验证了我们的方法。然后,我们将我们的方法应用于从人诱导的多能干细胞或胚胎嵌入式心脏细胞和定量的心肌细胞取向产生的清除叠层的分组堆叠的叠加。我们发现基于细胞组成和组织几何形状的对齐方面的显着差异。这些来自我们的合成图像和共聚焦数据的结果证明了我们测量3D组织中的对准的方法的效率和准确性。

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