| 摘要: |
| 病理学从微观角度展现了生物组织发育、分化、成熟和凋亡的复杂变化状态，单细胞分析技术为病理学复杂系统的研究提供了更多的信息。肿瘤是由肿瘤细胞和周围微环境组成的复杂生态系统。在病理学上，肿瘤中细胞各异、分布和生理功能千差万别，并且受自身、周围环境和治疗方法的调节，自成复杂系统。利用复杂系统中的因果判定方法，可以揭示单细胞复杂的调节作用，以及不同类型的肿瘤细胞与患者治疗方案、治疗效果、疾病复发和生存时间之间的因果关系。本文以肿瘤为例，阐述基于复杂系统中因果关系的单细胞病理学的意义和研究方法。 |
| 关键词: 复杂系统 因果关系 单细胞病理学 肿瘤病理学 人工智能 |
| DOI：10.16781/j.CN31-2187/R.20230700 |
| 投稿时间：2023-12-05修订日期：2024-01-10 |
| 基金项目:国家自然科学基金面上项目（81972721）. |
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| Single-cell pathology based on causality in complex systems |
| YU Guanzhen1*,SU Jinzhu1,CHEN Ying2 |
(1. Laboratory of Digital Health and Artificial Intelligence, Zhejiang Digital Content Research Institute, Shaoxing 312366, Zhejiang, China;
2. Department of Gastroenterology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University), Shanghai 200433, China
*Corresponding author) |
| Abstract: |
| Pathology reveals the complex changes of biological tissue development, differentiation, maturation, and apoptosis from a micro perspective. Single-cell analysis technology provides more information for the study of complex system of pathology. Tumor is a complex ecosystem composed of tumor cells and their surrounding microenvironment. In pathology, the cells in tumors are different, with different distribution and physiological functions, and are regulated by themselves, their surrounding environment and treatment methods, forming a complex system. Using the causal determination method in complex systems, we can reveal the complex regulatory role of a single cell, and the causal relationships between different types of tumor cells and patient treatment regimens, treatment effects, recurrence, and survival time. Taking tumor as an example, in this article we expound the significance and research methods of single-cell pathology based on causality in complex systems. |
| Key words: complex systems causality single-cell pathology tumor pathology artificial intelligence |
