基于细胞力学的红细胞计算分类--应用于形态流变学标志物的机器智能
Cell Mechanics Based Computational Classification of Red Blood Cells Via Machine Intelligence Applied to Morpho-Rheological Markers
摘要：
尽管荧光细胞标记在生物医学研究中被广泛采用，但其一些缺点是不可避免的，其中不合适的荧光探针或诱导功能变化的探针是主要限制。因此，对细胞分类的无标记方法的需求和发展是强烈的，其对精准医学的影响是相关的。为此，已经提出了用于细胞机械表型分析的高通量技术，以获得单细胞的多维生物物理表征。出于这种动机，我们的目标是研究无监督的机器学习方法（专门应用于通过实时变形性和荧光细胞术（RT-FDC）获得的形态流变学标志物）可以在多大程度上解决提供网织红细胞与成熟红细胞的无标记区分的困难任务。我们专注于这个问题，因为血液中网织红细胞的特征（它们的百分比和细胞特征）在多种人类疾病中至关重要，特别是骨髓疾病，如贫血和白血病。我们的方法报告了有前途的无标记的结果，在网织红细胞从成熟的红细胞的分类，它代表了一个进步，在高通量的形态流变学为基础的方法的计算分类的单细胞的发展。此外，我们的方法可以是一种替代方法，但也是一种补充方法，与现有的细胞标记技术相结合。
英文摘要：
Despite fluorescent cell-labelling being widely employed in biomedical studies, some of its drawbacks are inevitable, with unsuitable fluorescent probes or probes inducing a functional change being the main limitations. Consequently, the demand for and development of label-free methodologies to classify cells is strong and its impact on precision medicine is relevant. Towards this end, high-throughput techniques for cell mechanical phenotyping have been proposed to get a multidimensional biophysical characterization of single cells. With this motivation, our goal here is to investigate the extent to which an unsupervised machine learning methodology, which is applied exclusively on morpho-rheological markers obtained by real-time deformability and fluorescence cytometry (RT-FDC), can address the difficult task of providing label-free discrimination of reticulocytes from mature red blood cells. We focused on this problem, since the characterization of reticulocytes (their percentage and cellular features) in the blood is vital in multiple human disease conditions, especially bone-marrow disorders such as anemia and leukemia. Our approach reports promising label-free results in the classification of reticulocytes from mature red blood cells, and it represents a step forward in the development of high-throughput morpho-rheological-based methodologies for the computational categorization of single cells. Besides, our methodology can be an alternative but also a complementary method to integrate with existing cell-labelling techniques.
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