論文 - 詳細
| RRC ID | 64400 |
|---|---|
| 著者 | Akagi Y, Mori N, Kawamura T, Takayama Y, Kida YS. |
| タイトル | Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS). |
| ジャーナル | Sci Rep |
| Abstract |
Raman scattering represents the distribution and abundance of intracellular molecules, including proteins and lipids, facilitating distinction between cellular states non-invasively and without staining. However, the scattered light obtained from cells is faint and cells have complex structures, making it difficult to obtain a Raman spectrum covering the entire cell in a short time using conventional methods. This also prevents efficient label-free cell classification. In the present study, we developed the Paint Raman Express Spectroscopy System, which uses two fast-rotating galvano mirrors to obtain spectra from a wide area of a cell. By using this system and applying machine learning, we were able to acquire broad spectra of a variety of human and mouse cell types, including pluripotent stem cells and confirmed that each cell type can be classified with high accuracy. Moreover, we classified different activation states of human T cells, despite their similar morphology. This system could be used for rapid and low-cost drug evaluation and quality management for drug screening in cell-based assays. |
| 巻・号 | 11(1) |
| ページ | 8818 |
| 公開日 | 2021-4-23 |
| DOI | 10.1038/s41598-021-88056-3 |
| PII | 10.1038/s41598-021-88056-3 |
| PMID | 33893362 |
| PMC | PMC8065115 |
| MeSH | Animals Cells / classification* Humans Machine Learning Mice Single-Cell Analysis / methods Spectrum Analysis, Raman / methods* |
| IF | 3.998 |
| オルトメトリクス指標 |
オルトメトリクス指標項目
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| 最多言及媒体 | News |
| 各媒体での言及数の合計 | 11 |
| 過去6か月間でのオルトメトリクス指標の変動値 | 0.0 |
| リソース情報 | |
| ヒト・動物細胞 | 201B7(HPS0063) |