细胞带电分析中显微细胞聚集度的数值表征方法
Numerical Characterization Algorithm for Microscopic Cell Aggregation Degree in Charging Cell Analysis

为表征细胞表面电荷的变化规律,依据细胞显微观测到的细胞团聚程度,通过数值分析,实现了对视野中细胞位置及密度的识别。以细胞中心距倒数的平均值定义了细胞聚集度,从而建立了表征细胞团聚程度的算法;采用MATLAB软件实现了对显微图像的分析与重构,并以此为基础,实现了使用细胞聚集度表征细胞表面电荷变化的实验分析。通过使用不同唾液酸酶添加量处理细胞表面电荷,比较了使用该方法计算的血细胞聚集度和ζ电位测量结果,实验表明,随着唾液酸酶用量增加,细胞表面电荷减少,ζ电位降低,团聚程度增大,验证了提出的通过细胞聚集度表征细胞表面电荷规律方法的有效性。该方法可以排除视野内细胞数量对于细胞团聚程度的影响,从而为进一步研究细胞表面电荷变化和细胞团聚程度的定量关系奠定了基础。
To research the variation of cell surface charges by microscopic observation of cell agglomeration degree, the cell position and density in the vision are distinguished by a numerical analysis for microscopic images. The cell aggregation degree is defined as the mean of the reciprocal of the distance between cells, thus an algorithm for characterizing the cell agglomeration is established. And the analysis and reconstruction of microscopic image are realized by MATLAB, and the variation of cell surface charges is experimentally characterized. Then the aggregation degree obtained with this method and the ζ potential of the blood cells whose surface charges are removed by different dosage of sialidase are compared, respectively. Experiments demonstrate that the charges of cell surface decrease with the increasing dosage of sialidase, and the aggregation degree increases with the decreasing ζ potential, which verifies the effectiveness of characterizing the surface charge by calculating the aggregation degree. This method can eliminate the influence of cell number in the vision on the agglomeration, and facilitates revealing the quantitative relationship between variation of cell surface charges and cell agglomeration degree