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In Nihon yakurigaku zasshi. Folia pharmacologica Japonica

Various artificial cells and artificial tissues can be generated from induced pluripotent stem cells (iPS cells). There is now an urgent need to standardize the quality evaluation and management of iPS cells. Recently, artificial intelligence (AI) technology such as machine learning is providing evaluation method for the quality of iPS cells and iPS cell-derived somatic cells based on optical microscopy. Light, which is the principle of optical microscopy, has an interesting and important feature. There are various kinds of interaction between light and molecule, and the scattered light includes internal information of the molecule. Raman scattering inheres all the vibration mode of molecular bonds composing a molecule, and second harmonic generation (SHG) light, which is one of second-order non-linear scattering light, is derived from electric polarizations in the molecule, in other words, carries structural information within the protein. While states of a cell are usually defined by protein/gene expression patterns, we have proposed to apply Raman spectra for cellular fingerprinting as an alternative for identifying the cell state, and now succeeded in predicting gene-expression of antibiotic resistant bacteria in combination with machine learning technology. Meanwhile, SHG microscopy has been used to visualize fiber structures in living specimens, such as collagen, and microtubules as a label-free modality. By utilizing the feature that SHG senses protein structure change, we developed a new method to measure actomyosin activity in cardiac cells. The most important advantage of the use of the scattering light is their non-labeling and non-invasive capability.

Watanabe Tomonobu M, Fujita Hideaki, Kaneshiro Junichi