肿瘤靶向MRI/NIR双模态自组装探针的构建及基于新型粗粒化分子模型的理论探索(四）

项目名称： 肿瘤靶向MRI/NIR双模态自组装探针的构建及基于新型粗粒化分子模型的理论探索(四）

项目编号： No.91227126

项目类型： 重大研究计划

立项/批准年度： 2013

项目学科： 影像医学与生物医学工程

项目作者： 谭明乾

作者单位： 大连工业大学

项目金额： 75万元

中文摘要： 肿瘤靶向MRI/NIR多模态探针可以有效地兼顾MRI高空间分辨率以及NIR成像灵敏、快速等优势，在医学基础研究和肿瘤临床诊断中具有重要的应用价值。为解决MRI成像对比度差、近红外光学成像穿透能力低以及肿瘤识别缺乏特异性等核心问题，利用自组装技术发展肿瘤靶向性的MRI/NIR多模态探针是关键所在。本研究采用自组装技术，设计和合成具有良好生物相容性的MRI、NIR及肿瘤靶向基元，构建具有肿瘤靶向作用的MRI/NIR多模态探针，并发展新型粗粒化分子模型对自组装过程进行理论模拟，从分子层面上阐明各种自组装体的结构与提高自组装探针的磁共振和近红外荧光信号的关系，为构建自组装多模态探针基元以及建立多模态分子探针可控自组装新方法提供理论依据。同时以荷瘤动物为研究对象，采用MRI和NIR成像方法，对所合成的多模态探针进行成像评价，为多模态肿瘤非侵入可视化技术提供新的思路和技术手段。

中文关键词： 核磁共振成像；荧光成像；纳米载体；分子自组装；粗粒化模型

英文摘要： Tumor-targeted magnetic resonance imaging (MRI)-near infrared (NIR) multimodal probes are combinations of MRI and optical imaging modalities with the advantages of high spatial resolution of MRI and high sensitivity and rapid screening of NIR imaging, which have important application value for basic medical research and tumor clinical diagnosis. In order to overcome the key problems of poor contrast of MRI, lower penetration ability of NIR and non-specific tumor diagnosis, the key importance is the development of tumor-targeted MRI/NIR multimodal probes with self-assembly technology. In this proposal, biocompatible MRI, NIR and tumor-targeted structure motifs will be designed and synthesized. Tumor-targeted MRI/NIR multimodal probes will be prepared with self-assembly technology. A novel coarse-grained molecular model will be developed for theoretical modeling of the self-assembly process and clarifying the relationship between self-assembly structures and improvement of MRI-NIR intensity from the molecular level. The theoretical exploration of coarse-grained model will provide a theory for the development of self-assembly multimodal probes’ motifs as well as the new controllable self-assembly methods for multimodal molecular probes. The obtained multimodal molecular probes will be evaluated with MRI/NIR imaging

英文关键词： magnetic resonance imaging；fluorescent imaging；nanocarrier；molecular self-assembly；Coarse-Grained Model