Suppr超能文献

有序、随机、单调和非单调数字纳米点梯度。

Ordered, random, monotonic and non-monotonic digital nanodot gradients.

作者信息

Ongo Grant, Ricoult Sébastien G, Kennedy Timothy E, Juncker David

机构信息

Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; McGill University and Génome Québec Innovation Centre, McGill University, Montréal, Québec, Canada.

McGill University and Génome Québec Innovation Centre, McGill University, Montréal, Québec, Canada; McGill Program in Neuroengineering, Department of Neurology and Neurosurgery, Montréal Neurological Institute, McGill University, Montréal, Québec, Canada.

出版信息

PLoS One. 2014 Sep 5;9(9):e106541. doi: 10.1371/journal.pone.0106541. eCollection 2014.

Abstract

Cell navigation is directed by inhomogeneous distributions of extracellular cues. It is well known that noise plays a key role in biology and is present in naturally occurring gradients at the micro- and nanoscale, yet it has not been studied with gradients in vitro. Here, we introduce novel algorithms to produce ordered and random gradients of discrete nanodots--called digital nanodot gradients (DNGs)--according to monotonic and non-monotonic density functions. The algorithms generate continuous DNGs, with dot spacing changing in two dimensions along the gradient direction according to arbitrary mathematical functions, with densities ranging from 0.02% to 44.44%. The random gradient algorithm compensates for random nanodot overlap, and the randomness and spatial homogeneity of the DNGs were confirmed with Ripley's K function. An array of 100 DNGs, each 400×400 µm2, comprising a total of 57 million 200×200 nm2 dots was designed and patterned into silicon using electron-beam lithography, then patterned as fluorescently labeled IgGs on glass using lift-off nanocontact printing. DNGs will facilitate the study of the effects of noise and randomness at the micro- and nanoscales on cell migration and growth.

摘要

细胞导航由细胞外信号的不均匀分布所引导。众所周知,噪声在生物学中起着关键作用,并且存在于微米和纳米尺度的自然发生的梯度中,但尚未在体外梯度条件下进行研究。在这里,我们引入了新算法,根据单调和非单调密度函数生成离散纳米点的有序和随机梯度——称为数字纳米点梯度(DNG)。这些算法生成连续的DNG,其点间距根据任意数学函数在沿梯度方向的二维空间中变化,密度范围从0.02%到44.44%。随机梯度算法补偿了随机纳米点的重叠,并且通过Ripley's K函数证实了DNG的随机性和空间均匀性。设计了一个由100个DNG组成的阵列,每个DNG面积为400×400 µm²,总共包含5700万个200×200 nm²的点,并使用电子束光刻技术将其图案化到硅片上,然后通过剥离纳米接触印刷技术在玻璃上图案化为荧光标记的免疫球蛋白。DNG将有助于研究微米和纳米尺度上的噪声和随机性对细胞迁移和生长的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72fe/4156346/386a3f55be4f/pone.0106541.g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验