Theoretical evolution improves quality assessment of dao-di herbs, highlighting the need for multidisciplinary approaches.
Traditionally, Dao-di herbs refer to high-quality traditional Chinese medicine(TCM) produced in specific geographical regions. The development of their assessment theory holds profound significance for ensuring the stability of clinical efficacy and advancing the heritage and modernization of TCM. The concept of assessing Dao-di herbs originated in the Eastern Han Dynasty. Through millennia of inheritance and evolving cognitive frameworks, the assessment system has progressed from the traditional "appearance-based quality assessment" rooted in material phenomenology to the modern "excellent shape, high quality, and superior effect" theory guided by scientific quantification. This evolution epitomizes the innovative integration of traditional wisdom and modern technology. The formation of the "excellent shape and high quality" characteristics in Dao-di herbs involves intricate multi-level biological processes. Molecular biology techniques alone exhibit limitations in this complex system. A paradigm shift from reductionism to systems theory is required, and multidisciplinary approaches should be integrated, including molecular biology, cell biology, biophysics, and systems biology. Future research should prioritize exploring cellular-level features, deciphering relationships between microstructure and function, and investigating how environmental conditions regulate these traits to form the "excellent shape and high quality" attributes. This study systematically reviews the developmental trajectory of Dao-di herbs theory and proposes a biomechanics-driven research framework incorporating cellular developmental principles, aiming to refine the "excellent shape, high quality, and superior effect" theory. Moving forward, research should align with clinical precision medicine demands, leveraging artificial intelligence(AI) to synergize "wet" experiments(elucidation of molecular mechanisms) with "dry" experiments(AI modeling). Data-driven approaches will advance the standardization of Dao-di herbs.
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Yuan et al. (2025) studied this question.
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