Predicting patient outcome using machine learning technique
Predicting patient outcome using machine learning technique
批准号:
549560-2020
负责人:
Chan, WarrenWCW
金额:
$11.76万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Health Research Projects
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
中文摘要
化学探针是生物成像工具箱的关键组成部分,因为它们标记细胞和组织中的生物分子。生物成像的新挑战是设计用于三维组织成像的化学探针。在这项工作中,我们发现金属纳米颗粒的光散射可以在完整和透明的组织中提供3D成像对比。纳米颗粒可以作为金属层化学生长的模板,进一步增强散射信号。在整个组织中使用化学培养的纳米颗粒可以放大散射,产生比使用普通荧光团高140万倍的光子产量。这些探针是非光漂白的,可以与?无干扰的荧光团。我们展示了三种不同的生物医学应用:(a)血管的分子成像,(b)肿瘤中纳米药物载体的跟踪,以及(c)多发性硬化症小鼠模型中病变和免疫细胞的定位。我们的策略建立了一套独特而又互补的成像探针,用于从三维角度理解疾病机制。
英文摘要
Chemical probes are key components of thebioimaging toolbox, as they label biomolecules in cells andtissues. The new challenge in bioimaging is to design chemicalprobes for three-dimensional (3D) tissue imaging. In thiswork, we discovered that light scattering of metal nanoparticlescan provide 3D imaging contrast in intact and transparenttissues. The nanoparticles can act as a template for thechemical growth of a metal layer to further enhance thescattering signal. The use of chemically grown nanoparticles inwhole tissues can amplify the scattering to produce a 1.4million-fold greater photon yield than obtained using common?uorophores. These probes are non-photobleaching and canbe used alongside ?uorophores without interference. Wedemonstrated three distinct biomedical applications: (a) molecular imaging of blood vessels, (b) tracking of nanodrug carriers intumors, and (c) mapping of lesions and immune cells in a multiple sclerosis mouse model. Our strategy establishes a distinct yetcomplementary set of imaging probes for understanding disease mechanisms in three dimensions.
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