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基于气穴的光谱分析的多重超声成像。

Multiplexed Ultrasound Imaging Using Spectral Analysis on Gas Vesicles.

机构信息

Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.

Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA.

出版信息

Adv Healthc Mater. 2022 Sep;11(17):e2200568. doi: 10.1002/adhm.202200568. Epub 2022 Jul 12.

Abstract

Current advances in ultrasound imaging techniques combined with the next generation contrast agents such as gas vesicles (GV) revolutionize the visualization of biological tissues with spatiotemporal precision. In optics, fluorescent proteins enable understanding of molecular and cellular functions in biological systems due to their multiplexed imaging capability. Here, a panel of GVs is investigated using mid-band fit (MBF) spectral imaging to realize multiplexed ultrasound imaging to uniquely visualize locations of different types of stationary GVs. The MBF spectral imaging technique demonstrates that stationary clustered GVs are efficiently localized and distinguished from unclustered GVs in agarose gel phantom and 3D vessel structures are visualized in ex vivo mouse liver specimens. Mouse macrophages serve as carriers of clustered and unclustered GVs and multiplexing beacons to report cells' spatial locations by emitting distinct spectral signals. 2D MBF spectral images are reconstructed, and pixels in these images are classified depending on MBF values by comparing predetermined filters that predict the existence of cells with clustered and unclustered GVs. This pseudo-coloring scheme clearly distinguishes the locations of two classes of cells like pseudo-color images in fluorescence microscopy.

摘要

当前超声成像技术的进展与下一代造影剂(如气穴)相结合,以时空精度彻底改变了生物组织的可视化。在光学领域,由于荧光蛋白具有多重成像能力,因此能够理解生物系统中的分子和细胞功能。在这里,使用中带拟合(MBF)光谱成象来研究一组气穴,以实现多重超声成象,从而独特地可视化不同类型的固定气穴的位置。MBF 光谱成象技术表明,固定的聚集气穴可以有效地定位,并与琼脂糖凝胶模型中的非聚集气穴区分开,并且可以在离体小鼠肝标本中可视化 3D 血管结构。小鼠巨噬细胞作为聚集和气穴的载体以及多路复用信标,通过发出独特的光谱信号来报告细胞的空间位置。重建二维 MBF 光谱图像,并根据 MBF 值通过比较预测存在聚集和气穴的细胞的预定滤波器对这些图像中的像素进行分类。这种伪彩色方案可以像荧光显微镜中的伪彩色图像一样清楚地区分两类细胞的位置。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19b7/11468834/b630fa66a01b/ADHM-11-2200568-g002.jpg

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