Artificial Intelligence-Enabled Quantitative Assessment and Intervention for Heart Inflammation Model Organoids.

Journal: Angewandte Chemie (International ed. in English)
Published Date: Apr 21, 2025

Abstract

Inflammation plays a crucial role in progression of cardiovascular diseases (CVDs); thus, the discovery of rapid and precise analytical tools to assess inflammation related to CVDs is highly desirable for their diagnosis and therapeutic discovery. However, a straightforward and systematic method for quantitative assessment of inflammation levels in heart organoids has yet to be developed. Herein, we describe the construction of human heart inflammatory organoids with intricate structures and diverse cell lineages and the development of an artificial intelligence (AI)-enabled method for quantitative assessment of inflammation levels in this model. Furthermore, we devised a novel therapeutic strategy to boost endogenous energy molecule production in heart inflammatory organoids to address energy metabolic disorders. This research provides a convenient method for quantitative inflammation evaluation and offers a promising tool for drug discovery.

Authors

  • Hongrui Lin
    Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Shenzhen 518000, China.
  • Junjie Cheng
    Center of Basic Molecular Science, Department of Chemistry, Tsinghua University, 100084, Beijing, China.
  • Chuanwei Zhu
    Key Laboratory of Organic Solids, Beijing National Laboratory for Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, P.R. China.
  • Zhiwen Yang
    ShuKun Technology Co., Ltd., Jinhui Bd, Qiyang Rd, Beijing 100029, China.
  • Qi Shen
    Robotic Institute, School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, People's Republic of China. Mechanical Engineering Department, University of Nevada-Las Vegas, Las Vegas, NV 89154-4027, USA.
  • Yafeng Zou
    Key Laboratory of Organic Solids, Beijing National Laboratory for Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, P.R. China.
  • Yiming Huang
    Health Statistics Teaching and Research Office, School of Public Health, Shandong Second Medical University, Weifang Shandong 261053, China. hym033098@163.com.
  • Fengting Lv
    Key Laboratory of Organic Solids, Beijing National Laboratory for Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, P.R. China.
  • Haotian Bai
    Key Laboratory of Organic Solids, Beijing National Laboratory for Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, P.R. China.
  • Shu Wang
    Department of Radiology, Affiliated Hospital 6 of Nantong University, Yancheng Third People's Hospital, Yancheng, Jiangsu, China.

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