Use of Velocity Vectors for Cell Classification Under Acoustic Drifting Forces

Rahmetullah Varol, Sevde Omeroglu, Z. Karavelioglu, Ela Kumuk, Eda Nur Saruhan, Gizem Aydemir, M. E. Oruc, H. Uvet
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Abstract

This study reports a novel cell classification method based on the observation of trajectories that cells inside a fluidic chamber follow under an externally applied acoustic field. Proposed method is significant both as a cell classification method and as a method for characterizing the motion of various cell lines under different surface acoustic wave patterns. The difference is mainly due to the characteristic differences of cells such as mass, surface adhesiveness, cell stiffness and cellular volume. We discuss the mechanisms that affect the interaction between human colon carcinoma cell line (HCT116), human umbilical vein endothelial cells (HUVECs) and leukocyte cells and surface waves. Classification performance is tested using SVM, max-likelihood and MLP methods and accuracy, sensitivity and specificity values are reported for each. The results indicate that the method can be used as a powerful classifier particularly for cells that are hard to distinguish visually. It is observed that for a given frequency, the motion characteristics of different cell lines differ due to the difference between their mechanical properties for that particular line. This observation can be utilized for the development of a frequency based predictive cell manipulation method that is able to target specific cells using their characteristic frequencies. We discuss the potential of the proposed acoustic stimulation method as a cell manipulation technique.
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声波漂移力作用下速度矢量对细胞分类的应用
本研究报告了一种新的细胞分类方法,该方法基于观察在外部声场作用下流体腔内细胞的运动轨迹。该方法作为一种细胞分类方法和表征不同表面声波模式下各种细胞系运动的方法具有重要意义。这种差异主要是由于细胞的质量、表面粘附性、细胞刚度和细胞体积等特性的差异。我们讨论了影响人结肠癌细胞系(HCT116)、人脐静脉内皮细胞(HUVECs)和白细胞与表面波相互作用的机制。使用支持向量机、最大似然和MLP方法测试分类性能,并报告每种方法的准确性、灵敏度和特异性值。结果表明,该方法可以作为一种强大的分类器,特别是对于难以视觉区分的细胞。可以观察到,对于给定的频率,不同细胞系的运动特性不同,这是由于它们在该特定细胞系的机械特性之间的差异。这一观察结果可用于开发基于频率的预测细胞操作方法,该方法能够利用其特征频率靶向特定细胞。我们讨论了提出的声刺激方法作为细胞操作技术的潜力。
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Multiclass Classification of Brain Cancer with Machine Learning Algorithms Digital Filter Design Based on ARDUINO and Its Applications Use of Velocity Vectors for Cell Classification Under Acoustic Drifting Forces Development of a Full Face Mask during the COVID-19 Epidemic Spread Period TIPTEKNO 2020 Index
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