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Exploiting spectral information in Opto-Electronic Tweezers for cell classification and drug response evaluation
Sensors and Actuators B: Chemical ( IF 8.0 ) Pub Date : 2022-06-16 , DOI: 10.1016/j.snb.2022.132200
J. Filippi , D. Di Giuseppe , P. Casti , A. Mencattini , G. Antonelli , M. D’Orazio , F. Corsi , D. Della-Morte Canosci , L. Ghibelli , C. Witte , C. Di Natale , S.L. Neale , E. Martinelli

Cell responses to varying electric fields can reveal insights on cell biology with important implications for pharmaceutical and basic research. In this work, we exploit spectral information content in Opto-Electronic Tweezers (OET) systems through machine learning for label-free characterization of cell dielectric properties aimed at cell classification and drug response evaluation. A customized Polymethyl-methacrylate (PMMA) chip with ITO substrates and an a-Si layer was designed for OET-based manipulation of cells and integrated with an inverted microscope. We obtained OET cell signatures as spectra responses of kinematic and dynamic descriptors, which are the result of time-lapse measurements at increasing frequencies of the OET. Machine learning algorithms enable automatic selection and characterization of the information content present in the OET signature so derived. Experiments are performed on three biological case studies, involving 1) the discrimination of cell types among U937 human leukemia cells, PC-3 human prostate cancer cells and HaCaT human immortalized keratinocytes; 2) the evaluation of the effects of the chemotherapeutic agent etoposide on U937 cells at different concentrations; and 3) the evaluation of the effects of different exposure times of etoposide on U937 cells. The obtained results demonstrate that multiple levels of dielectric information can be extracted via OET cell signatures and clearly pose OET as a promising tool for cell discrimination and drug response evaluation.



中文翻译:

利用光电镊子中的光谱信息进行细胞分类和药物反应评估

细胞对不同电场的反应可以揭示细胞生物学的见解,对药物和基础研究具有重要意义。在这项工作中,我们通过机器学习利用光电镊子 (OET) 系统中的光谱信息内容,对细胞介电特性进行无标记表征,以用于细胞分类和药物反应评估。具有 ITO 基板和 a-Si 层的定制聚甲基丙烯酸甲酯 (PMMA) 芯片设计用于基于 OET 的细胞操作,并与倒置显微镜集成。我们获得了 OET 细胞特征作为运动学和动态描述符的光谱响应,这是在 OET 频率增加时延时测量的结果。机器学习算法能够自动选择和表征存在于如此导出的 OET 签名中的信息内容。对三个生物学案例研究进行了实验,涉及1)U937人白血病细胞、PC-3人前列腺癌细胞和HaCaT人永生化角质形成细胞之间的细胞类型区分;2)不同浓度化疗药物依托泊苷对U937细胞的影响评价;3) 不同曝光时间依托泊苷对U937细胞影响的评价。所获得的结果表明,可以通过 OET 细胞特征提取多层次的介电信息,并清楚地将 OET 作为细胞识别和药物反应评估的有前途的工具。对三个生物学案例研究进行了实验,涉及1)U937人白血病细胞、PC-3人前列腺癌细胞和HaCaT人永生化角质形成细胞之间的细胞类型区分;2)不同浓度化疗药物依托泊苷对U937细胞的影响评价;3) 不同曝光时间依托泊苷对U937细胞影响的评价。所获得的结果表明,可以通过 OET 细胞特征提取多层次的介电信息,并清楚地将 OET 作为细胞识别和药物反应评估的有前途的工具。对三个生物学案例研究进行了实验,涉及1)U937人白血病细胞、PC-3人前列腺癌细胞和HaCaT人永生化角质形成细胞之间的细胞类型区分;2)不同浓度化疗药物依托泊苷对U937细胞的影响评价;3) 不同曝光时间依托泊苷对U937细胞影响的评价。所获得的结果表明,可以通过 OET 细胞特征提取多层次的介电信息,并清楚地将 OET 作为细胞识别和药物反应评估的有前途的工具。2)不同浓度化疗药物依托泊苷对U937细胞的影响评价;3) 不同曝光时间依托泊苷对U937细胞影响的评价。所获得的结果表明,可以通过 OET 细胞特征提取多层次的介电信息,并清楚地将 OET 作为细胞识别和药物反应评估的有前途的工具。2)不同浓度化疗药物依托泊苷对U937细胞的影响评价;3) 不同曝光时间依托泊苷对U937细胞影响的评价。所获得的结果表明,可以通过 OET 细胞特征提取多层次的介电信息,并清楚地将 OET 作为细胞识别和药物反应评估的有前途的工具。

更新日期:2022-06-16
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