Multimodality Microscopy of Cell Dynamics in Three-Dimensional Engineered and Natural Tissues

被引:0
|
作者
Boppart, Stephen A. [1 ]
机构
[1] Univ Illinois, Beckman Inst Adv Sci & Technol, Urbana, IL 61801 USA
关键词
OPTICAL COHERENCE TOMOGRAPHY; GREEN FLUORESCENT PROTEIN; IN-VIVO; SPECTROSCOPY; CONSTRUCTS;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Our understanding of human disease is dependent on our ability to visualize and track the dynamic molecular and cellular changes that occur in tissue. Optical microscopy techniques provided the appropriate spatiotemporal scales for the non-destructive investigation into the complex three-dimensional (3-D) microenvironment of tissue. In tissue engineering, it has been recognized that 3-D scaffolds more closely recapitulate the natural microenvironment compared to standard planar substrates. Similarly, we are recognizing the importance that mechanical stimuli have on the dynamic behavior of cells and the formation of complex tissues. While 3-D scaffolds are favored, our microscopic imaging technologies to visualize these 3-D structures have been limited. Recent advances in microscopy, however, including optical coherence and multi-photon microscopy, have made high-resolution, deep-tissue imaging possible, even in highly-scattering engineered and natural tissues. Using a novel multimodal microscopy platform, we have imaged the dynamics of single cells and small populations of cells in a range of engineered tissues, as well as demonstrated in vivo imaging in human skin. Effects from mechanical stimulation are also observed, enabling future developments to track populations of cells through the growth of engineered tissues, under the application of mechanical stimuli, and following the grafting into living hosts. With advances in stem cell biology, labeling and tracking are also possible, helping to elucidate the migration and homing of stem cells to and from their niches. It is expected that these advanced microscopy techniques will reveal new insight and contribute experimental data to work in stem cell biology, complex systems biology, disease pathogenesis, and the optimization of engineered tissues for in vivo applications.
引用
收藏
页码:379 / 385
页数:7
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