| Project/Area Number |
18K17193
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 57060:Surgical dentistry-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Igarashi Masaki 東京大学, 医学部附属病院, 登録研究員 (40769577)
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| Project Period (FY) |
2018-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 幹細胞 / フローサイトメーター / セルソーター / 脂肪組織由来間葉系幹細胞 / AI / 脂肪幹細胞 / 記憶学習型セルソーター / 再生医療 |
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| Outline of Final Research Achievements |
Initially, excess auricular cartilage tissue from patients with microtia was harvested, cells were isolated and cultured and chondrocytes derived from human ototid tissue were reconstituted prior to evaluation by ASC. Next, to investigate whether adipose tissue-derived mesenchymal stem cells (ASCs) can also be isolated, ASCs were isolated from mouse adipose tissue, and the expression of representative ASC markers such as CD44, CD73, CD90, and CD105 positive and CD14, CD31, and CD45 negative were confirmed. Human auricular chondrocytes were able to isolate populations with different cartilage properties based on cell morphology alone, and the algorithm data were used to isolate ASCs and compared them with other stem cells.
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| Academic Significance and Societal Importance of the Research Achievements |
顎顔面領域における骨欠損に対して、自己細胞や組織を用いた移植医療などの再生医療が臨床応用されつつある。しかし、外科的侵襲や感染などのリスク、培養による細胞脱分化による品質の低下、移植後の免疫応答などの問題がある。最近開発された無染色で光学的な分析により目的細胞を分離可能とする機械学習駆動型フローサイトメーターに着眼し、多分化能が高い間葉系間質細胞（ASC）を分離することや軟骨特性の高い培養軟骨細胞の分離など、分離操作が複雑な細胞を簡便に分離が可能となる。この技術が実現すれば、今後、従来装置では検出不可能とされてきた特異細胞などが検出、分取可能にり、さらなる再生医療研究の発展が見込まれる。
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