Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning
Mesenchymal stem cells (MSCs) play a crucial role in tissue engineering, as their differentiation status directly affects the quality of the final cultured tissue, which is critical to the success of transplantation therapy. Furthermore, the precise control of MSC differentiation is essential for st...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Cells |
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| Online Access: | https://www.mdpi.com/2073-4409/12/11/1524 |
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| author | Yawei Kong Jianpeng Ao Qiushu Chen Wenhua Su Yinping Zhao Yiyan Fei Jiong Ma Minbiao Ji Lan Mi |
| author_facet | Yawei Kong Jianpeng Ao Qiushu Chen Wenhua Su Yinping Zhao Yiyan Fei Jiong Ma Minbiao Ji Lan Mi |
| author_sort | Yawei Kong |
| collection | DOAJ |
| description | Mesenchymal stem cells (MSCs) play a crucial role in tissue engineering, as their differentiation status directly affects the quality of the final cultured tissue, which is critical to the success of transplantation therapy. Furthermore, the precise control of MSC differentiation is essential for stem cell therapy in clinical settings, as low-purity stem cells can lead to tumorigenic problems. Therefore, to address the heterogeneity of MSCs during their differentiation into adipogenic or osteogenic lineages, numerous label-free microscopic images were acquired using fluorescence lifetime imaging microscopy (FLIM) and stimulated Raman scattering (SRS), and an automated evaluation model for the differentiation status of MSCs was built based on the K-means machine learning algorithm. The model is capable of highly sensitive analysis of individual cell differentiation status, so it has great potential for stem cell differentiation research. |
| first_indexed | 2024-03-11T03:09:43Z |
| format | Article |
| id | doaj.art-9676e3cb99d54472b8d7241730c6856f |
| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-11T03:09:43Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj.art-9676e3cb99d54472b8d7241730c6856f2023-11-18T07:41:14ZengMDPI AGCells2073-44092023-05-011211152410.3390/cells12111524Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine LearningYawei Kong0Jianpeng Ao1Qiushu Chen2Wenhua Su3Yinping Zhao4Yiyan Fei5Jiong Ma6Minbiao Ji7Lan Mi8Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Department of Optical Science and Engineering, Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai 200433, ChinaDepartment of Physics, Fudan University, Shanghai 200433, ChinaKey Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Department of Optical Science and Engineering, Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai 200433, ChinaKey Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Department of Optical Science and Engineering, Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai 200433, ChinaHuman Phenome Institute, Fudan University, Shanghai 200433, ChinaKey Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Department of Optical Science and Engineering, Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai 200433, ChinaKey Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Department of Optical Science and Engineering, Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai 200433, ChinaDepartment of Physics, Fudan University, Shanghai 200433, ChinaKey Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Department of Optical Science and Engineering, Shanghai Engineering Research Center of Ultra-Precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai 200433, ChinaMesenchymal stem cells (MSCs) play a crucial role in tissue engineering, as their differentiation status directly affects the quality of the final cultured tissue, which is critical to the success of transplantation therapy. Furthermore, the precise control of MSC differentiation is essential for stem cell therapy in clinical settings, as low-purity stem cells can lead to tumorigenic problems. Therefore, to address the heterogeneity of MSCs during their differentiation into adipogenic or osteogenic lineages, numerous label-free microscopic images were acquired using fluorescence lifetime imaging microscopy (FLIM) and stimulated Raman scattering (SRS), and an automated evaluation model for the differentiation status of MSCs was built based on the K-means machine learning algorithm. The model is capable of highly sensitive analysis of individual cell differentiation status, so it has great potential for stem cell differentiation research.https://www.mdpi.com/2073-4409/12/11/1524MSCslabel-freeFLIMSRSmachine learning |
| spellingShingle | Yawei Kong Jianpeng Ao Qiushu Chen Wenhua Su Yinping Zhao Yiyan Fei Jiong Ma Minbiao Ji Lan Mi Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning Cells MSCs label-free FLIM SRS machine learning |
| title | Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning |
| title_full | Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning |
| title_fullStr | Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning |
| title_full_unstemmed | Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning |
| title_short | Evaluating Differentiation Status of Mesenchymal Stem Cells by Label-Free Microscopy System and Machine Learning |
| title_sort | evaluating differentiation status of mesenchymal stem cells by label free microscopy system and machine learning |
| topic | MSCs label-free FLIM SRS machine learning |
| url | https://www.mdpi.com/2073-4409/12/11/1524 |
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