Bayesian Cell Force Estimation Considering Force Directions
Bayesian Cell Force Estimation Considering Force Directions
复制标题
考虑力方向的贝叶斯单元力估计
DOI：
10.1007/s11063-013-9320-y
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Kazushi Ikeda
中科院分区：
文献类型：
--
作者：
Satoshi Kozawa;Yuichi Sakumura;Michinori Toriyama;Naoyuki Inagaki;Kazushi Ikeda
牵引力显微镜是测量细胞产生的机械力的一种有用的技术。在这种方法中，荧光纳米珠嵌入细胞培养的弹性底物中，细胞在其上培养。然后，从球头位移估计细胞力，这代表了细胞下基底的力引起的变形。当珠粒密度较低或细胞附着物的位置未知时，从珠粒位移中估计力是不容易的。在这项研究中，我们提出了一种贝叶斯算法，通过引入基于细胞形态学的先验力方向。我们将贝叶斯框架应用于合成数据集，在这种情况下，头密度低，细胞附着点未知。结果表明，贝叶斯算法在力估计方面比以往的算法具有更高的精度。
Traction force microscopy is a useful technique for measuring mechanical forces generated by cells. In this method, fluorescent nano beads are embedded in the elastic substrate of cell culture, on which cells are cultured. Then, cellular forces are estimated from bead displacements, which represent the force-induced deformation of the substrate under the cell. Estimating the forces from the bead displacements is not easy when the bead density is low or the locations of cellular attachments are unknown. In this study, we propose a Bayesian algorithm by introducing a prior force direction that is based on cellular morphology. We apply the Bayesian framework to synthetic datasets in conditions under which the bead density is low and cellular attachment points are unknown. We demonstrate that the Bayesian algorithm improves accuracy in force estimation compared with the previous algorithms.