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形态迁移描述作为一种将细胞迁移与其形态联系起来的新方法。

Morphomigrational description as a new approach connecting cell's migration with its morphology.

机构信息

Department of Pharmaceutical Biophysics, Faculty of Pharmacy, Jagiellonian University Medical College, ul. Medyczna 9, 30-688, Kraków, Poland.

Department of Molecular and Interfacial Biophysics, Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. Lojasiewicza 11, 30-348, Kraków, Poland.

出版信息

Sci Rep. 2023 Jul 7;13(1):11006. doi: 10.1038/s41598-023-35827-9.

DOI:10.1038/s41598-023-35827-9
PMID:37419901
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10328925/
Abstract

The examination of morphology and migration of cells plays substantial role in understanding the cellular behaviour, being described by plethora of quantitative parameters and models. These descriptions, however, treat cell migration and morphology as independent properties of temporal cell state, while not taking into account their strong interdependence in adherent cells. Here we present the new and simple mathematical parameter called signed morphomigrational angle (sMM angle) that links cell geometry with translocation of cell centroid, considering them as one morphomigrational behaviour. The sMM angle combined with pre-existing quantitative parameters enabled us to build a new tool called morphomigrational description, used to assign the numerical values to several cellular behaviours. Thus, the cellular activities that until now were characterized using verbal description or by complex mathematical models, are described here by a set of numbers. Our tool can be further used in automatic analysis of cell populations as well as in studies focused on cellular response to environmental directional signals.

摘要

细胞形态和迁移的研究在理解细胞行为方面具有重要作用,其中涉及大量的定量参数和模型。然而,这些描述将细胞迁移和形态视为时间细胞状态的独立属性,而没有考虑到它们在贴壁细胞中的强相关性。在这里,我们提出了一个新的简单数学参数,称为有向形态迁移角(sMM 角),它将细胞几何形状与细胞质心的迁移联系起来,将它们视为一种形态迁移行为。sMM 角与现有的定量参数相结合,使我们能够构建一个新的工具,称为形态迁移描述,用于为几种细胞行为分配数值。因此,直到现在使用描述性语言或复杂数学模型来描述的细胞活动,现在可以通过一组数字来描述。我们的工具可以进一步用于细胞群体的自动分析,以及研究细胞对环境定向信号的反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/6aaea97edd69/41598_2023_35827_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/471e5243d4cc/41598_2023_35827_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/535a757d458b/41598_2023_35827_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/cb8c3a5ec028/41598_2023_35827_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/6aaea97edd69/41598_2023_35827_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/471e5243d4cc/41598_2023_35827_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/535a757d458b/41598_2023_35827_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/cb8c3a5ec028/41598_2023_35827_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e961/10328925/6aaea97edd69/41598_2023_35827_Fig4_HTML.jpg

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