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新方法实现低信噪比荧光纵向体内成像的混合解混
作者:小柯机器人 发布时间:2023/1/29 12:13:45


美国南加州大学Francesco Cutrale研究小组开发出新方法,实现低信噪比荧光纵向体内成像的混合解混。这一研究成果于2023年1月19日在线发表在国际学术期刊《自然—方法学》上。

据研究人员介绍,荧光生物成像向更复杂的系统和几何图形的扩展需要能够跨越广泛不同的时间尺度和长度尺度的分析工具,清晰地分离多个荧光标签,并将这些标签与背景自发荧光区分开来。

研究人员满足了这些具有挑战性的多光谱荧光显微镜目标,其结合高光谱相量和线性解混来创建混合解混(HyU)。HyU是高效和稳健的,能够定量信号分离,即使在低照明水平。在发育中的斑马鱼胚胎和小鼠组织的动态成像中,HyU能够干净有效地分解多个荧光标签,即使在要求的体积时间间隔成像设置中也是如此。HyU允许高动态范围成像,并允许同时成像明亮的外源基因标记和昏暗的内源基因标记。这使得在同一样本内对标记成分、细胞行为和细胞代谢进行同步研究成为可能,从而为生物系统的复杂性提供了更准确的见解。

附:英文原文

Title: HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence

Author: Chiang, Hsiao Ju, Koo, Daniel E. S., Kitano, Masahiro, Burkitt, Sean, Unruh, Jay R., Zavaleta, Cristina, Trinh, Le A., Fraser, Scott E., Cutrale, Francesco

Issue&Volume: 2023-01-19

Abstract: The expansion of fluorescence bioimaging toward more complex systems and geometries requires analytical tools capable of spanning widely varying timescales and length scales, cleanly separating multiple fluorescent labels and distinguishing these labels from background autofluorescence. Here we meet these challenging objectives for multispectral fluorescence microscopy, combining hyperspectral phasors and linear unmixing to create Hybrid Unmixing (HyU). HyU is efficient and robust, capable of quantitative signal separation even at low illumination levels. In dynamic imaging of developing zebrafish embryos and in mouse tissue, HyU was able to cleanly and efficiently unmix multiple fluorescent labels, even in demanding volumetric timelapse imaging settings. HyU permits high dynamic range imaging, allowing simultaneous imaging of bright exogenous labels and dim endogenous labels. This enables coincident studies of tagged components, cellular behaviors and cellular metabolism within the same specimen, providing more accurate insights into the orchestrated complexity of biological systems.

DOI: 10.1038/s41592-022-01751-5

Source: https://www.nature.com/articles/s41592-022-01751-5

期刊信息

Nature Methods:《自然—方法学》,创刊于2004年。隶属于施普林格·自然出版集团,最新IF:47.99
官方网址:https://www.nature.com/nmeth/
投稿链接:https://mts-nmeth.nature.com/cgi-bin/main.plex

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