Evidence map›Paper›PMID 41276812›Full record

ArticleChinese medicine2025

A novel algorithm- specific loci screening accelerates the establishment of molecular quantification of Glycyrrhiza glabra, G. uralensis, and G. inflata.

Yifei Pei, Ziyi Liu, Wenjun Jiang, Mingyu Zhang, Haitao Liu, Xue Feng, Xiwen Li

Abstract read
In one paragraph

Article in Chinese medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yifei PeiState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-Di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.ORCID http://orcid.org/0000-0002-3638-9017
Ziyi LiuState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-Di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.ORCID http://orcid.org/0009-0003-2566-2203
Wenjun JiangState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-Di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.ORCID http://orcid.org/0000-0001-6490-9449
Mingyu ZhangState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-Di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.ORCID http://orcid.org/0009-0007-9361-4392
Haitao LiuInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100193, China.ORCID http://orcid.org/0009-0002-4342-3938
Xue FengState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-Di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China. xfeng0413@icmm.ac.cn.ORCID http://orcid.org/0000-0003-0334-1225
Xiwen LiState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-Di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China. xwli@implad.ac.cn.ORCID http://orcid.org/0000-0002-5092-854X

Funding

Beijing Natural Science Foundation 7244492Central Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences CI2024C003YNNational Key Research and Development Program of China No.2019YFC1710601the Fundamental Research Funds for the Central public welfare research institutes of China ZXKT23004the Fundamental Research Funds for the Central public welfare research institutes of China ZZ18-XRZ-064
6 · The paper itself

Abstract

objectiveThis study aims to establish a specialized molecular method for distinguishing different licorice and quantifying target species accurately from mixtures.

methodsA rapid specific loci screening (SLS) algorithm was developed in this study, and used the chloroplast genome sequences were used to screen for variable loci in the Glycyrrhiza glabra (GG), G. uralensis (GU), and G. inflata (GI). Each locus has been validated by polymerase chain reaction and pyrosequencing. The selected loci were analyzed by Herb molecular quantification (Herb-Q) assay to complete the quantitative methodology verification and establish a quantitative detection system for homemade licorice mixtures and one of the patent medicines-Liuyi San.

resultsOutstanding performance was observed in quantitative validation, which evaluated linearity (0.9989), limit of detection (2%) and quantification (2%), and repeatability; additionally, a quantitative detection system was established for homemade licorice mixtures and Liuyi San (one of the patent medicines), with the lowest bias being 3.48%. When both GG and GU were present in the mixed powder, the average biases for GG and GU quantification were 8.25% and 8.01%, respectively. When only GG was present in Liuyi San, the bias was 6.43%; when both GG and GU were present, the biases for GG and GU were 5.61% and 3.48%, respectively.

conclusionThis study successfully established an accurate detection system for quantifying the botanical origin of edible-medicinal licorice, which represents a significant milestone in enhancing the safety, efficacy, and quality control in licorice products.

Indexed as

Chloroplast genomePyrosequencingSingle nucleotide polymorphism; GlycyrrhizaSpecies quantification

Identifiers

PMID41276812
PMCPMC12642167

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