A cationic near infrared fluorescent agent and ethyl-cinnamate tissue clearing protocol for vascular staining and imaging
Understanding vascular structures and dysfunction is a fundamental challenge. This task has been approached by using traditional methodologies such as microscopic computed tomography and magnetic resonance imaging. Both techniques are not only expensive but also time-consuming. Here, we present a ne...
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| Hauptverfasser: | , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
24 January 2019
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| In: |
Scientific reports
Year: 2019, Jahrgang: 9 |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/s41598-018-36741-1 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1038/s41598-018-36741-1 Verlag, Volltext: https://www.nature.com/articles/s41598-018-36741-1 
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| Verfasserangaben: | Jiaguo Huang, Cinzia Brenna, Arif ul Maula Khan, Cristina Daniele, Rüdiger Rudolf, Vincent Heuveline & Norbert Gretz |
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| 520 | |a Understanding vascular structures and dysfunction is a fundamental challenge. This task has been approached by using traditional methodologies such as microscopic computed tomography and magnetic resonance imaging. Both techniques are not only expensive but also time-consuming. Here, we present a new method for visualizing vascular structures in different organs in an efficient manner. A cationic near infrared (NIR) fluorescent dye was developed with attractive features to specifically stain blood vessels. Furthermore, we refined the process of organ staining and harvesting by retrograde perfusion and optimized the subsequent dehydration and clearing process by the use of an automatic tissue processor and a non-toxic substance, ethyl-cinnamate. Using this approach, the time interval between organ harvesting and microscopic analysis can be reduced from day(s) or weeks to 4 hours. Finally, we have demonstrated that the new NIR fluorescent agent in combination with confocal or light-sheet microscopy can be efficiently used for visualization of vascular structures, such as the blood vessels in different organs e.g. glomeruli in kidneys, with an extremely high resolution. Our approach facilitates the development of automatic image processing and the quantitative analysis to study vascular and kidney diseases. | ||
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