Jun Chu

Prof. Jun Chu

orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2020 in Toxicology in Vitro
Verified
Journal Article
Closed access
TJTing Jiang
Ting Jiang
HCHui Cheng
Hui Cheng
JSJingjing Su
Jingjing Su
XWXuncui Wang
Xuncui Wang
QWQiaoxue Wang
Qiaoxue Wang
QLQinglin Li
Qinglin Li

1 June 2007 in Genomics
Verified
Journal Article
Closed access
LDLiming Du
Liming Du
FJFangchan Jiao
Fangchan Jiao
JCJun Chu
Jun Chu
GJGulei Jin
Gulei Jin
Ming ChenMing Chen
Ming Chen
PWPing Wu
Ping Wu

17 May 2007 in Plant Molecular Biology
Verified
Journal Article
Closed access
PDF file
XQXiaopeng Qi
Xiaopeng Qi
ZWZhongchang Wu
Zhongchang Wu
JLJinhui Li
Jinhui Li
XMXiaorong Mo
Xiaorong Mo
Shihua WuShihua Wu
Shihua Wu
PWPing Wu
Ping Wu

19 March 2018 in Journal of Agricultural and Food Chemistry
Verified
Journal Article
Closed access
NXNa Xu
Na Xu
JCJun Chu
Jun Chu
MWMin Wang
Min Wang
LCLing Chen
Ling Chen
Liang ZhangLiang Zhang
Liang Zhang
XWXiaochun Wan
Xiaochun Wan

1 May 2015 in Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics
Verified
Journal Article
Closed access
JCJun Chu
Jun Chu
WLWei-Fang Li
Wei-Fang Li
CWCheng Wang
Cheng Wang
MLMo Lu
Mo Lu
KZKe-Hai Zhou
Ke-Hai Zhou
CZCong-Zhao Zhou
Cong-Zhao Zhou

1 November 2021 in Drug Design, Development and Therapy
Verified
Journal Article
Open access
PDF file
YYYunjia Yang
Yunjia Yang
HHHairong Huang
Hairong Huang
ZCZeying Cui
Zeying Cui
JCJun Chu
Jun Chu
GDGuankui Du
Guankui Du
Background: Betel nuts have long been used in traditional Chinese medicine. In our study, the bioactive components of betel nut were systematically investigated, and the main components and their target genes in the treatment of depression were predicted. Methods: The metabolites of the kernels and peels were analyzed with a UPLC–MS/MS system. Mass spectrometry outcomes were annotated by MULTIAQUANT. “Compound‐disease targets” were utilized to construct a pharmacology network. Results: A total of 873 metabolites were identified, with a high abundance of flavonoids, alkaloids, and phenols. Moreover, the abundance of flavonoids, alkaloids, and phenols in the kernel was significantly higher than that in the peel. A high abundance of catechin, arginine, and phenylalanine was detected in the kernel, while a high abundance of arginine, arecoline, and aminobutyric acid was detected in the peel. Catechins and cyanoside were the most abundant flavonoids in the kernel and peel, respectively. Arecoline was the most abundant alkaloid. A total of 111 metabolites showed a significant difference between the kernels and peels. The relative abundance of 40 differential metabolites was higher than 100,000, including 14 primary metabolites, 12 flavonoids, 4 phenols, and 4 alkaloids. Among the 40 high abundance metabolites, 20 were higher in the kernel and 20 in the peel. In addition, the enrichment of metabolic pathways found that the kernel and peel of the fruit adopted different metabolic pathways for the synthesis of flavonoids and alkaloids. Network pharmacology prediction showed that 93 metabolites could target 141 depression-related genes. The main components of betel nut intervention in depression were predicted to include L-phenylalanine, protocatechuic acid, okanin, nicotinic acid, L-tyrosine, benzocaine, syringic acid, benzocaine, phloretic acid, cynaroside, and 3,4-dihydroxybenzaldehyde. Conclusion: Betel nuts are rich in natural metabolites, and some of these metabolites can participate in the intervention of depression. In addition, the metabolites showed distinct characteristics between the kernel and peel. Therefore, it is necessary to comprehensively and rationally use betel nuts.