A rapid method for quantitative analysis of traditional Chinese medicine activity: A case study on antioxidant...

Gastrodia elata (GE) is a precious Traditional Chinese Medicine (TCM) with an extensive history of medicinal and dietary use in China. GE is renowned for its abilities to calm internal wind to relieve convulsions, pacify liver yang, expel wind to unblock collaterals, and promote longevity. It remains widely used as a dietary supplement for anti-aging purposes. Modern pharmacological studies have demonstrated that GE possesses significant anti-inflammatory, antioxidant, anti-aging, anticonvulsant, sedative, and neuroprotective properties.

To establish an accurate, rapid, and high-throughput method for detecting the biological activity of TCM, with a specific focus on optimizing the quality control approach for GE, thereby significantly reducing the cost and testing cycle associated with conventional bioactivity assessments.

First, six primary active components were identified in GE through fingerprint analysis and serum pharmacochemistry. Principal component analysis (PCA) was then employed to evaluate the correlation between these six components and ABTS· scavenging capacity. Subsequently, the contribution of each component to the antioxidant activity of GE was quantified and validated from two dimensions-in vitro antioxidant activity and in vivo antioxidant activity-using a matrix addition method. By integrating tripartite data encompassing chemical content, in vitro antioxidant activity, and in vivo antioxidant activity, an activity scoring system for GE was established. Finally, based on activity scoring system, a quality grading system for GE was implemented, and a rapid detection method for GE activity was developed by incorporating Near-infrared spectroscopy (NIRS) technology.

Six primary active components were identified in GE: Gastrodin (Gas), p-hydroxybenzyl alcohol (HBA), Parishin A (PA), Parishin B (PB), Parishin C (PC), and Parishin E (PE). Through multidimensional data integration, we determined that Gas exhibited a significant positive correlation with the antioxidant activity of GE, while HBA showed a negative correlation. PA, PB, PC, and PE were all positively correlated with the antioxidant activity. Our activity scoring system accurately predicted the antioxidant activity of GE (R² = 0.8062), and established the quality grading threshold for superior-grade GE at a Score > 8.79. Furthermore, utilizing NIRS technology combined with MLP regression analysis, we developed a rapid detection method for assessing the antioxidant activity of GE (R² = 0.95).

This work successfully integrates chemical composition with biological activity, establishing an accurate, rapid, and high-throughput quantitative activity detection method using NIRS. It provides a practical and efficient paradigm for quality control in TCM. The developed approach significantly reduces detection time and cost while maintaining precision, demonstrating broad applicability and reference value for quality assessment studies of other TCMs.