Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation
Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers...
Ausführliche Beschreibung
Autor*in: |
Jingnan Hu [verfasserIn] Yu Feng [verfasserIn] Baolin Li [verfasserIn] Fengxia Wang [verfasserIn] Qi Qian [verfasserIn] Wei Tian [verfasserIn] Liying Niu [verfasserIn] Xinguo Wang [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2023 |
---|
Schlagwörter: |
---|
Übergeordnetes Werk: |
In: PeerJ - PeerJ Inc., 2013, 11, p e15948(2023) |
---|---|
Übergeordnetes Werk: |
volume:11, p e15948 ; year:2023 |
Links: |
Link aufrufen |
---|
DOI / URN: |
10.7717/peerj.15948 |
---|
Katalog-ID: |
DOAJ100193900 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ100193900 | ||
003 | DE-627 | ||
005 | 20240414080433.0 | ||
007 | cr uuu---uuuuu | ||
008 | 240414s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.7717/peerj.15948 |2 doi | |
035 | |a (DE-627)DOAJ100193900 | ||
035 | |a (DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
050 | 0 | |a QH301-705.5 | |
100 | 0 | |a Jingnan Hu |e verfasserin |4 aut | |
245 | 1 | 0 | |a Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). | ||
650 | 4 | |a Cyanotis arachnoidea | |
650 | 4 | |a Quality markers | |
650 | 4 | |a UHPLC | |
650 | 4 | |a Chemical pattern recognition | |
650 | 4 | |a Network pharmacology | |
650 | 4 | |a Hypoglycemic | |
653 | 0 | |a Medicine | |
653 | 0 | |a R | |
653 | 0 | |a Biology (General) | |
700 | 0 | |a Yu Feng |e verfasserin |4 aut | |
700 | 0 | |a Baolin Li |e verfasserin |4 aut | |
700 | 0 | |a Fengxia Wang |e verfasserin |4 aut | |
700 | 0 | |a Qi Qian |e verfasserin |4 aut | |
700 | 0 | |a Wei Tian |e verfasserin |4 aut | |
700 | 0 | |a Liying Niu |e verfasserin |4 aut | |
700 | 0 | |a Xinguo Wang |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t PeerJ |d PeerJ Inc., 2013 |g 11, p e15948(2023) |w (DE-627)736558624 |w (DE-600)2703241-3 |x 21678359 |7 nnns |
773 | 1 | 8 | |g volume:11, p e15948 |g year:2023 |
856 | 4 | 0 | |u https://doi.org/10.7717/peerj.15948 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a |z kostenfrei |
856 | 4 | 0 | |u https://peerj.com/articles/15948.pdf |z kostenfrei |
856 | 4 | 0 | |u https://peerj.com/articles/15948/ |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/2167-8359 |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_206 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 11, p e15948 |j 2023 |
author_variant |
j h jh y f yf b l bl f w fw q q qq w t wt l n ln x w xw |
---|---|
matchkey_str |
article:21678359:2023----::dniiainfultmresocaoiaahodanaayioishsooiamcaimaeoceiapteneonto |
hierarchy_sort_str |
2023 |
callnumber-subject-code |
QH |
publishDate |
2023 |
allfields |
10.7717/peerj.15948 doi (DE-627)DOAJ100193900 (DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a DE-627 ger DE-627 rakwb eng QH301-705.5 Jingnan Hu verfasserin aut Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). Cyanotis arachnoidea Quality markers UHPLC Chemical pattern recognition Network pharmacology Hypoglycemic Medicine R Biology (General) Yu Feng verfasserin aut Baolin Li verfasserin aut Fengxia Wang verfasserin aut Qi Qian verfasserin aut Wei Tian verfasserin aut Liying Niu verfasserin aut Xinguo Wang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e15948(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e15948 year:2023 https://doi.org/10.7717/peerj.15948 kostenfrei https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a kostenfrei https://peerj.com/articles/15948.pdf kostenfrei https://peerj.com/articles/15948/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e15948 2023 |
spelling |
10.7717/peerj.15948 doi (DE-627)DOAJ100193900 (DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a DE-627 ger DE-627 rakwb eng QH301-705.5 Jingnan Hu verfasserin aut Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). Cyanotis arachnoidea Quality markers UHPLC Chemical pattern recognition Network pharmacology Hypoglycemic Medicine R Biology (General) Yu Feng verfasserin aut Baolin Li verfasserin aut Fengxia Wang verfasserin aut Qi Qian verfasserin aut Wei Tian verfasserin aut Liying Niu verfasserin aut Xinguo Wang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e15948(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e15948 year:2023 https://doi.org/10.7717/peerj.15948 kostenfrei https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a kostenfrei https://peerj.com/articles/15948.pdf kostenfrei https://peerj.com/articles/15948/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e15948 2023 |
allfields_unstemmed |
10.7717/peerj.15948 doi (DE-627)DOAJ100193900 (DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a DE-627 ger DE-627 rakwb eng QH301-705.5 Jingnan Hu verfasserin aut Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). Cyanotis arachnoidea Quality markers UHPLC Chemical pattern recognition Network pharmacology Hypoglycemic Medicine R Biology (General) Yu Feng verfasserin aut Baolin Li verfasserin aut Fengxia Wang verfasserin aut Qi Qian verfasserin aut Wei Tian verfasserin aut Liying Niu verfasserin aut Xinguo Wang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e15948(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e15948 year:2023 https://doi.org/10.7717/peerj.15948 kostenfrei https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a kostenfrei https://peerj.com/articles/15948.pdf kostenfrei https://peerj.com/articles/15948/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e15948 2023 |
allfieldsGer |
10.7717/peerj.15948 doi (DE-627)DOAJ100193900 (DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a DE-627 ger DE-627 rakwb eng QH301-705.5 Jingnan Hu verfasserin aut Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). Cyanotis arachnoidea Quality markers UHPLC Chemical pattern recognition Network pharmacology Hypoglycemic Medicine R Biology (General) Yu Feng verfasserin aut Baolin Li verfasserin aut Fengxia Wang verfasserin aut Qi Qian verfasserin aut Wei Tian verfasserin aut Liying Niu verfasserin aut Xinguo Wang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e15948(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e15948 year:2023 https://doi.org/10.7717/peerj.15948 kostenfrei https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a kostenfrei https://peerj.com/articles/15948.pdf kostenfrei https://peerj.com/articles/15948/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e15948 2023 |
allfieldsSound |
10.7717/peerj.15948 doi (DE-627)DOAJ100193900 (DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a DE-627 ger DE-627 rakwb eng QH301-705.5 Jingnan Hu verfasserin aut Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). Cyanotis arachnoidea Quality markers UHPLC Chemical pattern recognition Network pharmacology Hypoglycemic Medicine R Biology (General) Yu Feng verfasserin aut Baolin Li verfasserin aut Fengxia Wang verfasserin aut Qi Qian verfasserin aut Wei Tian verfasserin aut Liying Niu verfasserin aut Xinguo Wang verfasserin aut In PeerJ PeerJ Inc., 2013 11, p e15948(2023) (DE-627)736558624 (DE-600)2703241-3 21678359 nnns volume:11, p e15948 year:2023 https://doi.org/10.7717/peerj.15948 kostenfrei https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a kostenfrei https://peerj.com/articles/15948.pdf kostenfrei https://peerj.com/articles/15948/ kostenfrei https://doaj.org/toc/2167-8359 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11, p e15948 2023 |
language |
English |
source |
In PeerJ 11, p e15948(2023) volume:11, p e15948 year:2023 |
sourceStr |
In PeerJ 11, p e15948(2023) volume:11, p e15948 year:2023 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Cyanotis arachnoidea Quality markers UHPLC Chemical pattern recognition Network pharmacology Hypoglycemic Medicine R Biology (General) |
isfreeaccess_bool |
true |
container_title |
PeerJ |
authorswithroles_txt_mv |
Jingnan Hu @@aut@@ Yu Feng @@aut@@ Baolin Li @@aut@@ Fengxia Wang @@aut@@ Qi Qian @@aut@@ Wei Tian @@aut@@ Liying Niu @@aut@@ Xinguo Wang @@aut@@ |
publishDateDaySort_date |
2023-01-01T00:00:00Z |
hierarchy_top_id |
736558624 |
id |
DOAJ100193900 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ100193900</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414080433.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.7717/peerj.15948</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ100193900</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QH301-705.5</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Jingnan Hu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM).</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cyanotis arachnoidea</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quality markers</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">UHPLC</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Chemical pattern recognition</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Network pharmacology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Hypoglycemic</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Biology (General)</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yu Feng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Baolin Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Fengxia Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qi Qian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wei Tian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Liying Niu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xinguo Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">PeerJ</subfield><subfield code="d">PeerJ Inc., 2013</subfield><subfield code="g">11, p e15948(2023)</subfield><subfield code="w">(DE-627)736558624</subfield><subfield code="w">(DE-600)2703241-3</subfield><subfield code="x">21678359</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11, p e15948</subfield><subfield code="g">year:2023</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.7717/peerj.15948</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://peerj.com/articles/15948.pdf</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://peerj.com/articles/15948/</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2167-8359</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11, p e15948</subfield><subfield code="j">2023</subfield></datafield></record></collection>
|
callnumber-first |
Q - Science |
author |
Jingnan Hu |
spellingShingle |
Jingnan Hu misc QH301-705.5 misc Cyanotis arachnoidea misc Quality markers misc UHPLC misc Chemical pattern recognition misc Network pharmacology misc Hypoglycemic misc Medicine misc R misc Biology (General) Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation |
authorStr |
Jingnan Hu |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)736558624 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut aut aut aut aut aut |
collection |
DOAJ |
remote_str |
true |
callnumber-label |
QH301-705 |
illustrated |
Not Illustrated |
issn |
21678359 |
topic_title |
QH301-705.5 Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation Cyanotis arachnoidea Quality markers UHPLC Chemical pattern recognition Network pharmacology Hypoglycemic |
topic |
misc QH301-705.5 misc Cyanotis arachnoidea misc Quality markers misc UHPLC misc Chemical pattern recognition misc Network pharmacology misc Hypoglycemic misc Medicine misc R misc Biology (General) |
topic_unstemmed |
misc QH301-705.5 misc Cyanotis arachnoidea misc Quality markers misc UHPLC misc Chemical pattern recognition misc Network pharmacology misc Hypoglycemic misc Medicine misc R misc Biology (General) |
topic_browse |
misc QH301-705.5 misc Cyanotis arachnoidea misc Quality markers misc UHPLC misc Chemical pattern recognition misc Network pharmacology misc Hypoglycemic misc Medicine misc R misc Biology (General) |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
PeerJ |
hierarchy_parent_id |
736558624 |
hierarchy_top_title |
PeerJ |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)736558624 (DE-600)2703241-3 |
title |
Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation |
ctrlnum |
(DE-627)DOAJ100193900 (DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a |
title_full |
Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation |
author_sort |
Jingnan Hu |
journal |
PeerJ |
journalStr |
PeerJ |
callnumber-first-code |
Q |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2023 |
contenttype_str_mv |
txt |
author_browse |
Jingnan Hu Yu Feng Baolin Li Fengxia Wang Qi Qian Wei Tian Liying Niu Xinguo Wang |
container_volume |
11, p e15948 |
class |
QH301-705.5 |
format_se |
Elektronische Aufsätze |
author-letter |
Jingnan Hu |
doi_str_mv |
10.7717/peerj.15948 |
author2-role |
verfasserin |
title_sort |
identification of quality markers for cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation |
callnumber |
QH301-705.5 |
title_auth |
Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation |
abstract |
Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). |
abstractGer |
Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). |
abstract_unstemmed |
Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM). |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 |
title_short |
Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation |
url |
https://doi.org/10.7717/peerj.15948 https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a https://peerj.com/articles/15948.pdf https://peerj.com/articles/15948/ https://doaj.org/toc/2167-8359 |
remote_bool |
true |
author2 |
Yu Feng Baolin Li Fengxia Wang Qi Qian Wei Tian Liying Niu Xinguo Wang |
author2Str |
Yu Feng Baolin Li Fengxia Wang Qi Qian Wei Tian Liying Niu Xinguo Wang |
ppnlink |
736558624 |
callnumber-subject |
QH - Natural History and Biology |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.7717/peerj.15948 |
callnumber-a |
QH301-705.5 |
up_date |
2024-07-04T01:54:27.142Z |
_version_ |
1803611607813586944 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ100193900</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414080433.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.7717/peerj.15948</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ100193900</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ6033e34a0e4b4d898622c1620b970d6a</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QH301-705.5</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Jingnan Hu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Identification of quality markers for Cyanotis arachnoidea and analysis of its physiological mechanism based on chemical pattern recognition, network pharmacology, and experimental validation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Cyanotis arachnoidea C. B. Clarke is a traditional Chinese medicinal herb that has a limited clinical use in the treatment of diabetes mellitus (DM) in minority areas of Guizhou in China. However, few prior reports are available on the quality control of Cyanotis arachnoidea, and its quality markers and hypoglycemic mechanism are still unclear. The purpose of this study is to explore the quality markers (Q-markers) of Cyanotis arachnoidea and predict its hypoglycemic mechanism. In this study, ultra-high-performance liquid chromatography (UHPLC) fingerprint combined with chemical pattern recognition were performed, and four differential components were screened out as quality markers, including 20-Hydroxyecdysone, 3-O-acetyl-20-hydroxyecdysone, Ajugasterone C, and 2-O-acetyl-20-hydroxyecdysone. Network pharmacology analysis revealed 107 therapeutic target genes of Cyanotis arachnoidea in DM treatment, and the key targets were Akt1, TNF, IL-6, MAPK3, and JUN. The hypoglycemic mode of action of Cyanotis arachnoidea may be mediated by tumor necrosis factor (TNF) signaling, cancer, insulin resistance, and JAK-STAT pathways. Molecular docking analysis disclosed that the foregoing quality markers effectively bound their key target genes. An in vitro experiment conducted on pancreatic islet β-cells indicated that the forenamed active components of Cyanotis arachnoidea had hypoglycemic efficacy by promoting PI3K/Akt and inhibiting MAPK signaling. UHPLC also accurately quantified the quality markers. The identification and analysis of quality markers for Cyanotis arachnoidea is expected to provide references for the establishment of a quality control evaluation system and clarify the material basis and hypoglycemic mechanisms of this traditional Chinese medicine (TCM).</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cyanotis arachnoidea</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quality markers</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">UHPLC</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Chemical pattern recognition</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Network pharmacology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Hypoglycemic</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Biology (General)</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yu Feng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Baolin Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Fengxia Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qi Qian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Wei Tian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Liying Niu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xinguo Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">PeerJ</subfield><subfield code="d">PeerJ Inc., 2013</subfield><subfield code="g">11, p e15948(2023)</subfield><subfield code="w">(DE-627)736558624</subfield><subfield code="w">(DE-600)2703241-3</subfield><subfield code="x">21678359</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11, p e15948</subfield><subfield code="g">year:2023</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.7717/peerj.15948</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/6033e34a0e4b4d898622c1620b970d6a</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://peerj.com/articles/15948.pdf</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://peerj.com/articles/15948/</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2167-8359</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11, p e15948</subfield><subfield code="j">2023</subfield></datafield></record></collection>
|
score |
7.399768 |