Correlation Engine 2.0
Clear Search sequence regions


Sizes of these terms reflect their relevance to your search.

The extraction intermediate of traditional Chinese medicine is the key intermediate in the preparation process, and its stability has an important impact on the effectiveness and quality of the final product. However, existing stability evaluation methods are often time-consuming and labor-intensive, requiring long-term observation and the operation of complex equipment (such as high-performance liquid chromatography), and it is difficult to obtain more physical information about the instability of the system. Therefore, there is an urgent need to establish a fast and accurate stability analysis technology for traditional Chinese medicine. Multiple light scattering is a cutting-edge analytical method that can accurately and rapidly evaluate the stability of traditional Chinese medicines in an environment-friendly manner without changing the nature or state of the sample or using organic reagents. In this work, using the precise scanning data of multiple light scattering, the present protocol rapidly acquired the variation curves for layer thickness, particle migration speed, and average particle size over time. This enabled the precise identification of the mechanism and crucial characteristics causing the system's instability in its early stages. Of note, the research period for the extraction process can be considerably shortened by the detailed quantification of the system stability, which also allows for a quick, accurate, and in-depth analysis of the effects of various extraction processes on the stability of Phyllanthus emblica L.

Citation

Haozhou Huang, Mengqi Li, Chuanhong Luo, Sanhu Fan, Taigang Mo, Li Han, Dingkun Zhang, Junzhi Lin. Using Multiple Light Scattering to Examine the Stability of Phyllanthus emblica L. Extracts Obtained with Different Extraction Methods. Journal of visualized experiments : JoVE. 2023 Apr 14(194)

Expand section icon Mesh Tags

Expand section icon Substances


PMID: 37125797

View Full Text