微重力下关节软骨退变检测技术的研究进展
Research Progress of Detection Techniques for Microgravity-induced Articular Cartilage Degeneration
摘要
Abstract
With the rapid development of space program,research on joint degeneration under microgravity has become a critical focus in aerospace medicine,particularly due to the unique mechanical loading alterations that predispose articular cartilage to degenerative changes.This paper reviewed the latest progress in the study on microgravity-induced articular cartilage degeneration using biochemical analysis,magnetic resonance imaging(MRI),biomechanical testing,microscopic imaging,and infrared spectroscopy techniques.It elucidated that the first four methodologies could respectively decode molecular metabolism and reveal morphological/mechanical characteristics of cartilage under microgravity,yet which were constrained by sample destructiveness and insufficient dynamic monitoring.In contrast,mid and near infrared spectroscopy technologies,leveraging their non-destructive detection capabilities and molecular fingerprint recognition advantages,demonstrated significant potential not only in dynamic cartilage composition analysis and early degeneration identification under normal conditions when integrated with machine learning algorithms,but also showed preliminary feasibility for in-situ non-invasive detection in simulated microgravity experiments.Although infrared spectroscopy research in this field remains exploratory,its demonstrated strengths and prospects suggest that future integration with machine learning and multimodal technologies can enable practical in-situ non-invasive monitoring in space stations.These developments are anticipated to provide innovative strategies for safeguarding astronaut health and advancing clinical diagnosis and treatment of joint diseases.关键词
微重力/关节软骨/红外光谱/机器学习/评述Key words
Microgravity/Articular cartilage/Infrared spectroscopy/Machine learning/Review引用本文复制引用
李博展,吴青霞,李运宏,孙文惠,尚林伟,王慧捷,尹建华..微重力下关节软骨退变检测技术的研究进展[J].分析化学,2025,53(12):2001-2008,8.基金项目
国家自然科学基金项目(Nos.62375127,62105147)、江苏省重点研发计划项目(No.BE2023812)、南京航空航天大学前瞻布局专项基金项目(No.ILA-22022)、南京航空航天大学研究生科研与实践创新计划项目(Nos.xcxjh20230330,xcxjh20240331)、江苏省研究生科研与实践创新计划项目(No.KYCX24_0567)和中央高校基本科研业务费项目(No.NZ2025032)资助. Supported by the National Natural Science Foundation of China(Nos.62375127,62105147),the Jiangsu Province Key Research and Development Program(No.BE2023812),the Prospective Layout Special Fund of Nanjing University of Aeronautics and Astronautics(No.ILA-22022),the Graduate Research and Innovation Program of Nanjing University of Aeronautics and Astronautics(Nos.xcxjh20230330,xcxjh20240331),the Jiangsu Province Research and Practice Innovation Program(No.KYCX24_0567)and the Fundamental Research Funds for the Central Universities(No.NZ2025032). （Nos.62375127,62105147）
