纳米颗粒
计算机科学
鉴定(生物学)
分布(数学)
肿瘤细胞
纳米技术
肿瘤异质性
生物系统
材料科学
生物
数学
癌症
癌症研究
数学分析
植物
遗传学
作者
Presley MacMillan,Abdullah M. Syed,Benjamin R. Kingston,Jessica Ngai,Shrey Sindhwani,Zachary P. Lin,Luan N. Nguyen,Wayne Ngo,Stefan M. Mladjenovic,Qin Ji,Colin Blackadar,Warren C. W. Chan
出处
期刊:Nano Letters
[American Chemical Society]
日期:2023-07-28
卷期号:23 (15): 7197-7205
被引量:13
标识
DOI:10.1021/acs.nanolett.3c02186
摘要
Nanobio interaction studies have generated a significant amount of data. An important next step is to organize the data and design computational techniques to analyze the nanobio interactions. Here we developed a computational technique to correlate the nanoparticle spatial distribution within heterogeneous solid tumors. This approach led to greater than 88% predictive accuracy of nanoparticle location within a tumor tissue. This proof-of-concept study shows that tumor heterogeneity might be defined computationally by the patterns of biological structures within the tissue, enabling the identification of tumor patterns for nanoparticle accumulation.
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