Fluorescence excitation analysis by two-photon confocal laser scanning microscopy: a new method to identify fluorescent nanoparticles on histological tissue sections

利用双光子共聚焦激光扫描显微镜进行荧光激发分析:一种识别组织切片上荧光纳米颗粒的新方法

阅读:3
作者:Edmond Kahn ,Nicolas Tissot, Perrine Frere, Aurélien Dauphin, Mohamed Boumhras, Claude-Marie Bachelet, Frédérique Frouin, Gérard Lizard

Abstract

In the present study, we make use of the ability of two-photon confocal laser scanning microscopes (CLSMs) equipped with tunable lasers to produce spectral excitation image sequences. Furthermore, unmixing, which is usually performed on emission image sequences, is performed on these excitation image sequences. We use factor analysis of medical image sequences (FAMIS), which produces factor images, to unmix spectral image sequences of stained structures in tissue sections to provide images of characterized stained cellular structures. This new approach is applied to histological tissue sections of mouse aorta containing labeled iron nanoparticles stained with Texas Red and counterstained with SYTO13, to obtain visual information about the accumulation of these nanoparticles in the arterial wall. The possible presence of Texas Red is determined using a two-photon CLSM associated with FAMIS via the excitation spectra. Texas Red and SYTO13 are thus differentiated, and corresponding factor images specify their possible presence and cellular localization. In conclusion, the designed protocol shows that sequences of images obtained by excitation in a two-photon CLSM enables characterization of Texas Red-stained nanoparticles and other markers. This methodology offers an alternative and complementary solution to the conventional use of emission spectra unmixing to localize fluorescent nanoparticles in tissue samples. Keywords: FAMIS; Texas Red; spectral excitation sequences; tunable excitation; unmixing.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。