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Tissue clearing

delete2021-12-16
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PRE
AI
D
Douglas S. Richardson *
W
Webster Guan
K
Katsuhiko Matsumoto
C
Chenchen Pan
K
Kwanghun Chung
A
Ali Ertürk
H
Hiroki R. Ueda
J
Jeff W. Lichtman
DOI:10.1038/s43586-021-00080-9delete
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摘要

摘要

En 中文
Tissue clearing of gross anatomical samples was first described more than a century ago and has only recently found widespread use in the field of microscopy. This renaissance has been driven by the application of modern knowledge of optical physics and chemical engineering to the development of robust and reproducible clearing techniques, the arrival of new microscopes that can image large samples at cellular resolution and computing infrastructure able to store and analyse large volumes of data. Many biological relationships between structure and function require investigation in three dimensions, and tissue clearing therefore has the potential to enable broad discoveries in the biological sciences. Unfortunately, the current literature is complex and could confuse researchers looking to begin a clearing project. The goal of this Primer is to outline a modular approach to tissue clearing that allows a novice researcher to develop a customized clearing pipeline tailored to their tissue of interest. Furthermore, the Primer outlines the required imaging and computational infrastructure needed to perform tissue clearing at scale, gives an overview of current applications, discusses limitations and provides an outlook on future advances in the field. Tissue clearing techniques render biological samples transparent to allow for the deep imaging of large tissue volumes. This Primer presents tissue clearing techniques in a modular way and underlines the main principles of each stage of clearing to help researchers to develop a custom tissue clearing workflow for their sample of choice. The authors also discuss the current applications and limitations of tissue clearing.

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Nature Reviews Methods Primers 封面图
Nature Reviews Methods Primers
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56
论文数:
235
被引数:
9.8K

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H
Helmholtz Zentrum Munchen
学者数:
149
论文数: 41
被引数: 25
M
massachusetts institute of technology
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5.0K
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T
the university of tokyo
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2.7K
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H
Harvard University
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5.7K
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