| 项目编号: | 1605971
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| 项目名称: | (NANO)^2: gold nanoclusters in lipid nanodiscoidal bicelles as a potential nanodiagnostic platform: experiment and computer modeling |
| 作者: | Mu-Ping Nieh
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| 承担单位: | University of Connecticut
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| 批准年: | 2016
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| 开始日期: | 2016-06-15
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| 结束日期: | 2019-05-31
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| 资助金额: | 369482
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | nanoparticle
; solid nanoparticle
; lipid nanocarrier
; bicelle
; lipid
; nanoparticle-complex
; experiment
; nanoparticle encapsulation
; gold cluster
; lipid/nanoparticle composition
; nanoparticle self-assembly
; promising platform
; lipid structure
; friendly platform
; computer simulation
; well-defined lipid nanodisc
; x-ray computerized tomography
; nanoparticle cluster
; nanoparticle aggregation
; nanoparticle size
; aggregated gold nanoparticle
; discoidal bicelle
; lipid composition
; nanodisc formulation
; lipid molecule
; computer modeling effort
; local nanoparticle concentration
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| 英文摘要: | CBET - 1605971
PI: Nieh, Mu-Ping
Lipid nanocarriers containing solid nanoparticles are a promising platform for drug delivery and imaging in biomedical applications. The entrapped solid nanoparticles can be imaging contrast agents, which enhance the signal obtained in various medical imaging techniques such as magnetic resonance imaging, X-ray computerized tomography, and photoacoustic tomography. Placing the nanoparticles inside the lipid nanocarriers increases their solubility and stability, and provides a significant enhancement in luminescence due to nanoparticle aggregation. The nanoparticle-complex can also be used to enhance local heating in photothermal therapy, which uses infrared electromagnetic radiation to treat tumors and other disorders. Aggregated gold nanoparticles can enhance signals by several orders of magnitude, which is promising for high-sensitivity imaging and sensing. The goal of this project is to develop well-defined lipid nanodiscs (bicelles) that can serve as carriers for nanoparticles and investigate their performance in imaging applications. A combination of experiments and computer simulation will be used to determine the key parameters that affect arrangements of nanoparticles in bicelles and then optimize lipid composition and nanodisc formulation to achieve encapsulated clusters of nanoparticles with strong fluorescence properties. The project will provide opportunities for students at various academic levels to participate in research. Grade 5-12 STEM teachers who participate in UCONN's da Vinci Project will be introduced to research projects related to nanoparticle self-assembly.
The combination of experiments and molecular dynamics simulations will provide fundamental understanding of the interactions between lipid molecules and hydrophobically-modified solid nanoparticles such as monolayer protected gold clusters and hydrophobic quantum dots. Factors that affect solid nanoparticle solubilization and clustering inside discoidal bicelles, including lipid and hydrophobic tether chain lengths, nanoparticle size, and charge density of the lipids or nanoparticle, will be examined. In addition, the relationships between local nanoparticle concentration inside the bicelles, the distance between nanoparticles, and the size of nanoparticle clusters trapped in the lipid structure and their photo-physical properties will be investigated. The joint experimental and computer modeling effort will help predict the range of desired lipid/nanoparticle composition to optimize nanoparticle encapsulation, clustering and retention. This new strategy of nanoparticle encapsulation by lipid nanocarriers will provide a fast, robust, size-controllable and environmentally friendly platform that can be easily adapted for manufacturing. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/92034
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
Mu-Ping Nieh. (NANO)^2: gold nanoclusters in lipid nanodiscoidal bicelles as a potential nanodiagnostic platform: experiment and computer modeling. 2016-01-01.
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