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j.reth.2022.01.002.pdf | 5.24 MB | Adobe PDF | 見る/開く |
タイトル: | Automated measurement of fluorescence signals reveals a significant increase of the graft-derived neurite extension in neonates compared to aged rats |
著者: | Grinand, Luc Takahashi, Jun |
著者名の別形: | 髙橋, 淳 |
キーワード: | Neural graft Parkinson's disease Aging Quantification Automation |
発行日: | Mar-2022 |
出版者: | Elsevier BV The Japanese Society for Regenerative Medicine |
誌名: | Regenerative Therapy |
巻: | 19 |
開始ページ: | 97 |
終了ページ: | 106 |
抄録: | [Background] --Neural tissue grafting is an acceptable form of cell therapy for brain injury and diseases. However, methods that can evaluate the graft integration and measure axonal extensions in a 3D environment are limited in scale, inconvenient, and operator intensive. [Method] --We stained grafts with a fluorescent antibody and then quantified the amount of fluorescence through the entire brain. To achieve this, we created an automated computer program designed to sort out authentic staining from background noise without any user input, enabling the analysis of thousands of images. [Results] --Our program could compensate for variations in the background brightness between images in all animals. Using this program, we show that human induced pluripotent stem cell (iPSC)-derived dopaminergic (DA) progenitor cells integrate better into the striatum of neonates than older rats. [Conclusion] --Our program can quantify quickly and conveniently the integration of neural grafts in a 3D environment without depending on a blinded human operator. We expect this method to be a useful tool to assess the efficiency of graft-enhancing treatments for neurodegenerative diseases or other neural reconstruction attempts. |
著作権等: | © 2022 The Japanese Society for Regenerative Medicine. Production and hosting by Elsevier B.V. This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license. |
URI: | http://hdl.handle.net/2433/275964 |
DOI(出版社版): | 10.1016/j.reth.2022.01.002 |
PubMed ID: | 35155722 |
出現コレクション: | 学術雑誌掲載論文等 |
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