Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy

Background Adipose-derived stem cells (ADSCs) exhibit promising potential for the treatment of various diseases, including osteoarthritis. Spheroids derived from ADSCs are a viable treatment option with enhanced anti-inflammatory effects and tissue repair capabilities.Objective SphereRing® is a rota...

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Main Authors: Takuya Sakamoto, Hiroto Koma, Ayane Kuwano, Tetsuhiro Horie, Atsushi Fuku, Hironori Kitajima, Yuka Nakamura, Ikuhiro Tanida, Yujiro Nakade, Hiroaki Hirata, Yoshiyuki Tachi, Hiroshi Sunami, Daisuke Sakamoto, Sohsuke Yamada, Naoki Yamamoto, Yusuke Shimizu, Yasuhito Ishigaki, Toru Ichiseki, Ayumi Kaneuji, Satoshi Osawa, Norio Kawahara
Format: Article
Language:English
Published: Taylor & Francis Group 2025-03-01
Series:BioTechniques
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Online Access:https://www.tandfonline.com/doi/10.1080/07366205.2025.2493489
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author Takuya Sakamoto
Hiroto Koma
Ayane Kuwano
Tetsuhiro Horie
Atsushi Fuku
Hironori Kitajima
Yuka Nakamura
Ikuhiro Tanida
Yujiro Nakade
Hiroaki Hirata
Yoshiyuki Tachi
Hiroshi Sunami
Daisuke Sakamoto
Sohsuke Yamada
Naoki Yamamoto
Yusuke Shimizu
Yasuhito Ishigaki
Toru Ichiseki
Ayumi Kaneuji
Satoshi Osawa
Norio Kawahara
author_facet Takuya Sakamoto
Hiroto Koma
Ayane Kuwano
Tetsuhiro Horie
Atsushi Fuku
Hironori Kitajima
Yuka Nakamura
Ikuhiro Tanida
Yujiro Nakade
Hiroaki Hirata
Yoshiyuki Tachi
Hiroshi Sunami
Daisuke Sakamoto
Sohsuke Yamada
Naoki Yamamoto
Yusuke Shimizu
Yasuhito Ishigaki
Toru Ichiseki
Ayumi Kaneuji
Satoshi Osawa
Norio Kawahara
author_sort Takuya Sakamoto
collection DOAJ
description Background Adipose-derived stem cells (ADSCs) exhibit promising potential for the treatment of various diseases, including osteoarthritis. Spheroids derived from ADSCs are a viable treatment option with enhanced anti-inflammatory effects and tissue repair capabilities.Objective SphereRing® is a rotating donut-shaped tube that efficiently produces large quantities of spheroids. However, accurately measuring spheroid size for spheroid quality assessment is challenging. This study aimed to develop an automated method for measuring spheroid size using deep learning through the ChatGPT Data Analyst for image recognition and processing.Method The area, perimeter, and circularity of spheroids generated with the SphereRing system were analyzed using ChatGPT Data Analyst and ImageJ. Measurement accuracy was validated using Bland–Altman analysis and scatter plot correlation coefficients.Results ChatGPT Data Analyst was consistent with ImageJ for all parameters. Bland–Altman plots demonstrated strong agreement; most data points were within the 95% limits.Conclusion The ChatGPT Data Analyst provides a reliable and efficient alternative for assessing spheroid quality. This method reduces human error and improves reproducibility to enhance spheroid quality control. Thus, this method has potential applications in regenerative medicine.
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publishDate 2025-03-01
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spelling doaj-art-b495cf32f075439ab97f5b49db937d152025-08-20T03:53:52ZengTaylor & Francis GroupBioTechniques0736-62051940-98182025-03-0177313714910.1080/07366205.2025.2493489Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapyTakuya Sakamoto0Hiroto Koma1Ayane Kuwano2Tetsuhiro Horie3Atsushi Fuku4Hironori Kitajima5Yuka Nakamura6Ikuhiro Tanida7Yujiro Nakade8Hiroaki Hirata9Yoshiyuki Tachi10Hiroshi Sunami11Daisuke Sakamoto12Sohsuke Yamada13Naoki Yamamoto14Yusuke Shimizu15Yasuhito Ishigaki16Toru Ichiseki17Ayumi Kaneuji18Satoshi Osawa19Norio Kawahara20Medical Research Institute, Kanazawa Medical University, Kahoku, JapanGenome Biotechnology Laboratory, Kanazawa Institute of Technology, Hakusan, JapanGenome Biotechnology Laboratory, Kanazawa Institute of Technology, Hakusan, JapanMedical Research Institute, Kanazawa Medical University, Kahoku, JapanDepartment of Orthopedic Surgery, Kanazawa Medical University, Kahoku, JapanDepartment of Orthopedic Surgery, Kanazawa Medical University, Kahoku, JapanMedical Research Institute, Kanazawa Medical University, Kahoku, JapanGenome Biotechnology Laboratory, Kanazawa Institute of Technology, Hakusan, JapanDepartment of Orthopedic Surgery, Kanazawa Medical University, Kahoku, JapanDepartment of Orthopedic Surgery, Kanazawa Medical University, Kahoku, JapanDepartment of Orthopedic Surgery, Kanazawa Medical University, Kahoku, JapanFaculty of Medicine, Advanced Medical Research Center, University of the Ryukyus, Okinawa, JapanDepartment of Cardiovascular Surgery, Kanazawa Medical University, Kahoku, JapanCenter for Regenerative Medicine, Kanazawa Medical University Hospital, Kahoku, JapanResearch Promotion Headquarters, Fujita Health University, Toyoake, JapanDepartment of Plastic and Reconstructive Surgery, Graduate School of Medicine, University of the Ryukyus, Okinawa, JapanMedical Research Institute, Kanazawa Medical University, Kahoku, JapanMedical Research Institute, Kanazawa Medical University, Kahoku, JapanDepartment of Orthopedic Surgery, Kanazawa Medical University, Kahoku, JapanGenome Biotechnology Laboratory, Kanazawa Institute of Technology, Hakusan, JapanDepartment of Orthopedic Surgery, Kanazawa Medical University, Kahoku, JapanBackground Adipose-derived stem cells (ADSCs) exhibit promising potential for the treatment of various diseases, including osteoarthritis. Spheroids derived from ADSCs are a viable treatment option with enhanced anti-inflammatory effects and tissue repair capabilities.Objective SphereRing® is a rotating donut-shaped tube that efficiently produces large quantities of spheroids. However, accurately measuring spheroid size for spheroid quality assessment is challenging. This study aimed to develop an automated method for measuring spheroid size using deep learning through the ChatGPT Data Analyst for image recognition and processing.Method The area, perimeter, and circularity of spheroids generated with the SphereRing system were analyzed using ChatGPT Data Analyst and ImageJ. Measurement accuracy was validated using Bland–Altman analysis and scatter plot correlation coefficients.Results ChatGPT Data Analyst was consistent with ImageJ for all parameters. Bland–Altman plots demonstrated strong agreement; most data points were within the 95% limits.Conclusion The ChatGPT Data Analyst provides a reliable and efficient alternative for assessing spheroid quality. This method reduces human error and improves reproducibility to enhance spheroid quality control. Thus, this method has potential applications in regenerative medicine.https://www.tandfonline.com/doi/10.1080/07366205.2025.2493489Adipose-derived stem cellsChatGPT data analystSphereRingspheroidscell therapy
spellingShingle Takuya Sakamoto
Hiroto Koma
Ayane Kuwano
Tetsuhiro Horie
Atsushi Fuku
Hironori Kitajima
Yuka Nakamura
Ikuhiro Tanida
Yujiro Nakade
Hiroaki Hirata
Yoshiyuki Tachi
Hiroshi Sunami
Daisuke Sakamoto
Sohsuke Yamada
Naoki Yamamoto
Yusuke Shimizu
Yasuhito Ishigaki
Toru Ichiseki
Ayumi Kaneuji
Satoshi Osawa
Norio Kawahara
Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy
BioTechniques
Adipose-derived stem cells
ChatGPT data analyst
SphereRing
spheroids
cell therapy
title Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy
title_full Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy
title_fullStr Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy
title_full_unstemmed Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy
title_short Efficient spheroid morphology assessment with a ChatGPT data analyst: implications for cell therapy
title_sort efficient spheroid morphology assessment with a chatgpt data analyst implications for cell therapy
topic Adipose-derived stem cells
ChatGPT data analyst
SphereRing
spheroids
cell therapy
url https://www.tandfonline.com/doi/10.1080/07366205.2025.2493489
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