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使用图像分析方法对细胞/集落运动进行无创测量,以评估口腔角质形成细胞的增殖能力,作为再生医学质量控制的一种工具。

Noninvasive measurement of cell/colony motion using image analysis methods to evaluate the proliferative capacity of oral keratinocytes as a tool for quality control in regenerative medicine.

作者信息

Hoshikawa Emi, Sato Taisuke, Kimori Yoshitaka, Suzuki Ayako, Haga Kenta, Kato Hiroko, Tabeta Koichi, Nanba Daisuke, Izumi Kenji

机构信息

Division of Biomimetics, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan.

Division of Periodontology, Department of Oral Biological Science, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan.

出版信息

J Tissue Eng. 2019 Oct 15;10:2041731419881528. doi: 10.1177/2041731419881528. eCollection 2019 Jan-Dec.

Abstract

Image-based cell/colony analyses offer promising solutions to compensate for the lack of quality control (QC) tools for noninvasive monitoring of cultured cells, a regulatory challenge in regenerative medicine. Here, the feasibility of two image analysis algorithms, optical flow and normalised cross-correlation, to noninvasively measure cell/colony motion in human primary oral keratinocytes for screening the proliferative capacity of cells in the early phases of cell culture were examined. We applied our software to movies converted from 96 consecutive time-lapse phase-contrast images of an oral keratinocyte culture. After segmenting the growing colonies, two indices were calculated based on each algorithm. The correlation between each index of the colonies and their proliferative capacity was evaluated. The software was able to assess cell/colony motion noninvasively, and each index reflected the observed cell kinetics. A positive linear correlation was found between cell/colony motion and proliferative capacity, indicating that both algorithms are potential tools for QC.

摘要

基于图像的细胞/集落分析为弥补用于非侵入性监测培养细胞的质量控制(QC)工具的不足提供了有前景的解决方案,这是再生医学中的一个监管挑战。在此,研究了两种图像分析算法——光流法和归一化互相关法,用于非侵入性测量人原代口腔角质形成细胞中的细胞/集落运动以筛选细胞培养早期阶段细胞增殖能力的可行性。我们将我们的软件应用于从口腔角质形成细胞培养的96个连续延时相差图像转换而来的视频。在分割生长的集落后,基于每种算法计算两个指标。评估集落的每个指标与其增殖能力之间的相关性。该软件能够非侵入性地评估细胞/集落运动,并且每个指标都反映了观察到的细胞动力学。发现细胞/集落运动与增殖能力之间存在正线性相关,表明这两种算法都是用于质量控制的潜在工具。

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