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On-line Access: 2023-01-19

Received: 2022-08-15

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Bio-Design and Manufacturing  2023 Vol.6 No.3 P.319-339

http://doi.org/10.1007/s42242-022-00226-y


Organoids revealed: morphological analysis of the profound next generation in-vitro model with artificial intelligence


Author(s):  Xuan Du, Zaozao Chen, Qiwei Li, Sheng Yang, Lincao Jiang, Yi Yang, Yanhui Li & Zhongze Gu

Affiliation(s):  State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China; more

Corresponding email(s):   101012282@seu.edu.cn, liyanhuili@nju.edu.cn, Gu@seu.edu.cn

Key Words:  Artificial intelligence, Organoids, Morphology, Growth characteristics, Growth characteristics, Convolutional neural network


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Xuan Du, Zaozao Chen, Qiwei Li, Sheng Yang, Lincao Jiang, Yi Yang, Yanhui Li & Zhongze Gu. Organoids revealed: morphological analysis of the profound next generation in-vitro model with artificial intelligence[J]. Journal of Zhejiang University Science D, 2023, 6(3): 319-339.

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Abstract: 
The human gut microbiota is widely considered to be a metabolic organ hidden within our bodies, playing a crucial role in the host’s physiology. Several factors affect its composition, so a wide variety of microbes residing in the gut are present in the world population. Individual excessive imbalances in microbial composition are often associated with human disorders and pathologies, and new investigative strategies to gain insight into these pathologies and define pharmaceutical therapies for their treatment are needed. In vitro models of the human gut microbiota are commonly used to study microbial fermentation patterns, community composition, and host-microbe interactions. Bioreactors and microfluidic devices have been designed to culture microorganisms from the human gut microbiota in a dynamic environment in the presence or absence of eukaryotic cells to interact with. In this review, we will describe the overall elements required to create a functioning, reproducible, and accurate in vitro culture of the human gut microbiota. In addition, we will analyze some of the devices currently used to study fermentation processes and relationships between the human gut microbiota and host eukaryotic cells.

东南大学杜轩等 | 揭示类器官:使用人工智能对影响深远的下一代体外模型进行形态分析

本综述论文聚焦利用人工智能对影响深远的下一代体外模型进行形态分析。在现代术语中,类器官是指在体外特定三维(3D)环境中生长的细胞,与它们的源器官或组织具有相似的结构。通过显微镜观察类器官的形态和生长特征是类器官分析的常用观察方式。然而,仅依靠劳动力来筛选和分析类器官是困难、耗时和不准确的,而传统技术无法很好地解决这一问题。人工智能(AI)技术的应用已经在许多生物学和医学研究领域证明了其有效性,特别是在单细胞或H/E染色组织切片的分析中。扩展到分析类器官,人工智能还应提供更高效、定量、准确和快速的解决方案。在这篇综述中,首先简要概述类器官的应用领域,然后讨论传统类器官测量和分析方法的缺点。其次,概述了从机器学习到深度学习的发展以及后者的优势,接着描述如何利用卷积神经网络来解决类器官观察和分析中的挑战。最后,讨论目前人工智能在类器官研究中的局限性,并探究机遇和未来的研究方向。

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