Si Li, Xi Huang, Yuan Li, Rong Ding, Xuemei Wu, Ling Li, Canlin Li, Rui Gu
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引用次数: 0
Abstract
The quality of Chinese herbal medicine (CHM) directly impacts clinical efficacy and safety. Fingerprint technology is an internationally recognized method for evaluating the quality of CHM. However, the existing quality evaluation models based on fingerprint technology have blocked the ability to assess the internal quality of CHM and cannot comprehensively reflect the correlation between pharmacodynamic information and active constituents. Through mathematical methods, a connection between the "Spectrum" (fingerprint) and the "Effect" (pharmacodynamic data) was established to conduct a spectrum-effect relationship (SER) of CHM to unravel the active component information associated with the pharmacodynamic activity. Consequently, SER can efficiently address the limitations of the segmentation of chemical components and pharmacodynamic effect in CHM and further improve the quality evaluation of CHM. This review focuses on the recent research progress of SER in the field of CHM, including the establishment of fingerprint, the selection of data analysis methods, and their recent applications in the field of CHM. Various advanced fingerprint techniques are introduced, followed by the data analysis methods used in recent years are summarized. Finally, the applications of SER based on different research subjects are described in detail. In addition, the advantages of combining SER with other data are discussed through practical applications, and the research on SER is summarized and prospected. This review proves the validity and development potential of the SER and provides a reference for the development and application of quality evaluation methods for CHM.
中草药（CHM）的质量直接影响临床疗效和安全性。指纹图谱技术是国际公认的中药质量评价方法。然而，现有的基于指纹图谱技术的质量评价模型阻碍了对中药内在质量的评价能力，不能全面反映药效学信息与有效成分之间的相关性。通过数学方法，在 "谱"（指纹图谱）和 "效"（药效学数据）之间建立联系，对 CHM 进行谱效关系（SER）分析，从而揭示与药效学活性相关的活性成分信息。因此，SER 可以有效解决 CHM 中化学成分和药效学效应分割的局限性，进一步提高 CHM 的质量评价。本综述重点介绍了 SER 在化学合成药物领域的最新研究进展，包括指纹图谱的建立、数据分析方法的选择及其在化学合成药物领域的最新应用。首先介绍了各种先进的指纹技术，然后总结了近年来使用的数据分析方法。最后，详细介绍了基于不同研究课题的 SER 应用。此外，还通过实际应用讨论了将 SER 与其他数据相结合的优势，并对 SER 的研究进行了总结和展望。本综述证明了 SER 的有效性和发展潜力，为 CHM 质量评价方法的开发和应用提供了参考。
期刊介绍：
Critical Reviews in Analytical Chemistry continues to be a dependable resource for both the expert and the student by providing in-depth, scholarly, insightful reviews of important topics within the discipline of analytical chemistry and related measurement sciences. The journal exclusively publishes review articles that illuminate the underlying science, that evaluate the field''s status by putting recent developments into proper perspective and context, and that speculate on possible future developments. A limited number of articles are of a "tutorial" format written by experts for scientists seeking introduction or clarification in a new area.
This journal serves as a forum for linking various underlying components in broad and interdisciplinary means, while maintaining balance between applied and fundamental research. Topics we are interested in receiving reviews on are the following:
· chemical analysis;
· instrumentation;
· chemometrics;
· analytical biochemistry;
· medicinal analysis;
· forensics;
· environmental sciences;
· applied physics;
· and material science.
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