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Potential quality evaluation method for Radix Astragali based on sweetness indicators.

ABSTRACT: Sweetness is a traditional sensory indicator used to evaluate the quality of the popular Chinese herb Radix Astragali (RA). RA roots with strong sweetness are considered to be of good quality. However, neither a thorough analysis of the component(s) contributing to RA sweetness, nor a scientific investigation of the reliability of this indicator has been conducted to date. In this study, seven kinds of sweetness components were identified in RA and a quality evaluation method based on these components was established and used to characterize the quality of 48 RA samples. The sweetness evaluation method of RA was first built based on the sweetness components, and a comprehensive evaluation index commonly used in quality control of RA was also derived, which was based on the contents of four indicators (astragaloside IV, calycosin glucoside, polysaccharides and extracts). After evaluating the correlation of these indexes the results showed that the level of sweetness exhibited a strong positive correlation with the proposed comprehensive index. Our results indicate that sweetness is one of the most important quality attributes of RA and thus provide a scientific basis for the utility of the sweetness indicator in quality assessment of this Chinese herb.

SUBMITTER: Li K

PROVIDER: S-EPMC6272557 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Potential quality evaluation method for Radix Astragali based on sweetness indicators.

Li Ke K Gao Fanrong F Li Zhenyu Z Qin Xuemei X Sun Haifeng H Xing Jie J Zhang Lizeng L Du Guanhua G

Molecules (Basel, Switzerland) 20150213 2

Sweetness is a traditional sensory indicator used to evaluate the quality of the popular Chinese herb Radix Astragali (RA). RA roots with strong sweetness are considered to be of good quality. However, neither a thorough analysis of the component(s) contributing to RA sweetness, nor a scientific investigation of the reliability of this indicator has been conducted to date. In this study, seven kinds of sweetness components were identified in RA and a quality evaluation method based on these comp ...[more]

PMID: 25689640

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Project description:Background The molecular mechanism of Astragali Radix in the treatment of children with nephrotic syndrome (NS) is unclear. This study aimed to use network pharmacology to explore this potential mechanism. Methods The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to identify the main active ingredients of Astragali Radix. The PharmMapper, Online Mendelian Inheritance in Man (OMIM), and GeneCards databases were then used to identify the active ingredients of Astragali Radix. The String database and Cytoscape software were used to construct the protein-protein network. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using DAVID Database. Results In the TCMSP Database, a total of 20 chemical constituents of Astragali Radix were screened. After removing the duplicates and false positive genes, 394 targets of these active ingredients were obtained from PharmMapper. By comparing the NS-related genes in the GeneCards and OMIM Databases, a total of 39 potential NS-related targets were ultimately identified. The protein-protein-interaction network included 39 nodes and 366 edges. The top 5 proteins were albumin (ALB), serine/threonine kinase (AKT1), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase (MAPK), and matrix metallopeptidase 9 (MMP9). The GO analysis showed that the target genes were mainly involved in biological processes (e.g., signal transduction, the positive regulation of cell proliferation, and the positive regulation of migration). The cellular components included a plasma membrane, extracellular exosome, and extracellular space. The molecular functions included protein binding, zinc-ion binding, protein tyrosine kinase activity, and enzyme binding. The KEGG analysis showed that the treatment of NS by Astragali Radix mainly involved pathways in cancer, proteoglycans in cancer, the phosphatidylinositol 3-kinase and protein kinase B (PI3K-Akt) signaling pathway, the rennin-angiotensin-system (Ras) signaling pathways, and Forkhead box protein O1 (FoxO) signaling pathways. Conclusions In the present study, the network pharmacology method was used to explore the potential targets and pathways of Astragali Radix in the treatment of NS. We also provided future research directions for the treatment of NS with a complex pathogenesis.

Project description:ObjectiveCritical process parameters (CPPs) identification is an important step of the implementation of quality by design (QbD) concept. There are many CPP identification methods, such as risk analysis method, sensitivity analysis method, multiple linear regression method, standard partial regression coefficient (SPRC) method, and so on. The SPRC method can consider multiple process critical quality attributes (CQAs) simultaneously, but the determination of CPP number is subjective. Therefore, new CPP identification method is still required.MethodsThe manufacturing process of Astragali Radix extract, which contained water reflux extraction, concentration, and ethanol precipitation, was used as an example. First, the multiple process CQAs were determined to be the yield of pigment, dry matter, sugars, and active ingredients. Second, the potential CPPs were determined by a knowledge organization method. Plackett-Burman designed experiments were then performed. A weighted determination coefficient ( Rw2 ) method was presented to identify CPPs. In this method, the importance of different CQAs was considered. Process parameters were removed one-by-one according to their importance index. The decrease in Rw2 was used to characterize the importance of the removed parameter. If the decrease of Rw2 was less than a preset threshold, the removed parameter was not a CPP.ResultsDuring the manufacturing process of Astragali Radix extract, the potential CPPs determined by the knowledge organization method were water consumption, reflux extraction time, extraction frequency, ethanol content, ethanol consumption, and concentration endpoint. Reflux extraction time, the first ethanol consumption, the second ethanol consumption, and the second ethanol precipitation refrigeration temperature were found to be CPPs using the weighted determination coefficient method with the threshold of 10%.ConclusionUsing the weighted determination coefficient method, CPPs can be determined with all the CQAs considered based on their importance. The determination of CPP number is more objective compared with the SPRC method.

Project description:Astragali Radix (AR) has been widely used in traditional Chinese medicine prescriptions for acute and chronic liver injury. However, little is known about the effects of AR on acetaminophen (APAP)-induced liver injury (ALI). In the current study, a network pharmacology–based approach was applied to characterize the action mechanism of AR on ALI. All compounds of AR were obtained from the corresponding databases, and active compounds were selected according to its oral bioavailability and drug-likeness index. The potential genes of AR were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and PubChem, whereas the potential genes related to ALI were obtained from Online databases (GeneCards and Online Mendelian Inheritance in Man) and Gene Expression Omnibus profiles. The enriched processes, pathways, and target genes of the diseases were analyzed by referring to the Search Tool for the Retrieval of Interacting Genes/Proteins database. A network constructed through Cytoscape software was used to identify the target proteins that connected the compounds in AR with the differential genes of ALI. Subsequently, the potential underlying action mechanisms of AR on ALI predicted by the network pharmacology analyses were experimentally validated in APAP-induced liver injury in mice and HL7702 cells incubated with APAP. The compound-target network included 181 targets, whereas the potential genes related to ALI were 4,621. A total of 49 AR–ALI crossover proteins, corresponding to 49 genes, were filtered into a protein–protein interaction network complex and designated as the potential targets of AR on ALI. Among the genes, the three highest-scoring genes, MYC, MAPK8, and CXCL8 were highly associated with apoptosis in ALI. Then in vitro and in vivo experiments confirmed that AR exhibited its prominent therapeutic effects on ALI mainly via regulating hepatocyte apoptosis related to inhibiting the expressions of MYC (c-Myc), MAPK8 (JNK1), and CXCL8 (IL-8). In conclusion, our study suggested that the combination of network pharmacology prediction with experimental validation might offer a useful tool to characterize the molecular mechanism of AR on ALI.

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Potential quality evaluation method for Radix Astragali based on sweetness indicators.

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Potential quality evaluation method for Radix Astragali based on sweetness indicators.

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