Traditional Chinese Herbal Medicine (TCHM) contain multiple botanicals, each of which contains many compounds that may be relevant to the medicine's putative activity. Therefore, analytical techniques that look at a suite of compounds, including their respective ratios, provide a more rational approach to the authentication and quality assessment of TCHM. In this paper we present several examples of applying chromatographic fingerprint analysis for determining the identity, stability, and consistency of TCHM as well as the identification of adulterants as follows: (1) species authentication of various species of ginseng (Panax ginseng, Panax quinquefolium, Panax noto-ginseng) and stability of ginseng preparations using high performance thin-layer chromatography (HPTLC) fingerprint analysis; (2) batch-to-batch consistency of extracts of Total Glycosides of Peony (TGP), to be used as a raw material and in finished products (TGP powdered extract products), using high performance liquid chromatography (HPLC) fingerprint analysis with a pattern recognition software interface (CASE); (3) documenting the representative HPLC fingerprints of Immature Fruits of Terminalia chebula (IFTC) through the assessment of raw material, in-process assay of the extracts, and the analysis of the finished product (tablets); (4) HPLC fingerprint study demonstrating the consistent quality of total flavonoids of commercial extracts of ginkgo (Ginkgo biloba) leaves (EGb) along with detection of adulterations. The experimental conditions as well as general comments on the application of chromatographic fingerprint analysis are discussed.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.chroma.2005.12.091 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Analysis of stomatal characteristics of maize hybrids and their parental inbred lines during critical reproductive periods.
Front Plant Sci
January 2025
Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.
The stomatal phenotype is a crucial microscopic characteristic of the leaf surface, and modulating the stomata of maize leaves can enhance photosynthetic carbon assimilation and water use efficiency, thereby playing a vital role in maize yield formation. The evolving imaging and image processing technologies offer effective tools for precise analysis of stomatal phenotypes. This study employed Jingnongke 728 and its parental inbred to capture stomatal images from various leaf positions and abaxial surfaces during key reproductive stages using rapid scanning electron microscopy.
View Article and Find Full Text PDFTransformer-generated atomic embeddings to enhance prediction accuracy of crystal properties with machine learning.
Nat Commun
January 2025
School of Information Science and Technology, Fudan University, Shanghai, China.
Accelerating the discovery of novel crystal materials by machine learning is crucial for advancing various technologies from clean energy to information processing. The machine-learning models for prediction of materials properties require embedding atomic information, while traditional methods have limited effectiveness in enhancing prediction accuracy. Here, we proposed an atomic embedding strategy called universal atomic embeddings (UAEs) for their broad applicability as atomic fingerprints, and generated the UAE tensors based on the proposed CrystalTransformer model.
View Article and Find Full Text PDFStandardized HPTLC for Reproducible Chemical Fingerprinting.
Methods Mol Biol
January 2025
HPTLC Association, Rheinfelden, Switzerland.
High-performance thin-layer chromatography (HPTLC) plays a crucial role in establishing the chemical fingerprint of natural products (NPs) during analysis. This technique involves standardized procedures for each step, ensuring the reproducibility of results. In this context, we present a comprehensive standard operating procedure (SOP) encompassing both manual instruments and suitable devices.
View Article and Find Full Text PDFComprehensive analysis strategy of quality for traditional Chinese medicine compound based on fingerprint technology and quantitative prediction of spectra.
Talanta
January 2025
School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China. Electronic address:
Traditional Chinese medicine compound (TCMC) comes from a wide range of sources, and the complexity of chemical composition leads to differences in quality. Improving quality evaluation standards is the focus as well as the difficulty in its development and application. The traditional fingerprint analysis method has certain limitations for the quality evaluation of TCMC and the judgment of superior and inferior products.
View Article and Find Full Text PDFQuantum chemical studies of carbon-based graphene-like nanostructures: from benzene to coronene.
J Mol Model
January 2025
Department of Chemistry, Federal Institute of Education, Science and Technology of Espírito Santo, Av. Min. Salgado Filho, Vila Velha, 29106-010, Espírito Santo, Brazil.
Context: This study presents quantum chemical analysis of 14 distinct carbon-based nanostructures (CBN), ranging from simple molecules, like benzene, to more complex structures, such as coronene, which serves as an exemplary graphene-like model. The investigation focuses on elucidating the relationships between molecular orbital (MO) energies, the energy band gaps, electron occupation numbers (eON), electronic conduction, and the compound topologies, seeking to find the one that approaches most of a graphene-like structure for in silico studies. Through detailed examination of molecular properties including chemical hardness and chemical potential, we demonstrate that the electronic exchange between orbitals is directly influenced by the structural topology of the carbon-based nanostructures, as the electron occupation numbers and the molecular orbital energies.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!