IEEE Trans Biomed Eng. 2019 Nov;66(11):3185-3191. doi: 10.1109/TBME.2019.2901763. Epub 2019 Feb 26.
Cellular physical properties have been identified to reflect cell states. Existing techniques are able to characterize either mechanical or electrical properties of a cell. This paper presents a micropipette aspiration technique that enables the characterization of both mechanical (instantaneous elastic modulus, equilibrium elastic modulus, and viscosity), and electrical (specific membrane capacitance) properties of the same single cell. Two bladder cancer cell lines (RT4 and T24) with different metastatic potential were used to evaluate the technique. The results showed that high-grade bladder cancer cells (T24, grade III) possess lower viscosity, lower elastic modulus, and larger SMC than the low-grade cancer cells (RT4, grade I). The Naive Bayes classifier was utilized to assess the classification accuracy using single-physical and multi-physical parameters. The classification results confirmed that the use of multi-biophysical parameters resulted in higher accuracy (97.5%), sensitivity (100%), and specificity (95.2%) than the use of a single-physical parameter for distinguishing T24 and RT4 cells.
细胞的物理特性被认为可以反映细胞状态。现有的技术能够描述细胞的机械或电学特性。本文提出了一种微管吸吮技术，能够同时表征同一单个细胞的机械（瞬时弹性模量、平衡弹性模量和粘度）和电学（特定膜电容）特性。使用两种具有不同转移潜能的膀胱癌细胞系（RT4 和 T24）来评估该技术。结果表明，高级别膀胱癌细胞（T24，III 级）比低级别癌细胞（RT4，I 级）具有更低的粘度、更低的弹性模量和更大的 SMC。使用朴素贝叶斯分类器评估使用单物理和多物理参数的分类准确性。分类结果证实，使用多生物物理参数比使用单一物理参数来区分 T24 和 RT4 细胞具有更高的准确性（97.5%）、灵敏度（100%）和特异性（95.2%）。
