Jiang Xijuan

Jiang Xijuan


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

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

Representative Publications

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29 September 2021 in Scientific Reports
Verified
Journal Article
Open access
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WZWenyun Zeng
Wenyun Zeng
DWDanbin Wu
Danbin Wu
YSYingxin Sun
Yingxin Sun
YSYanrong Suo
Yanrong Suo
QYQun Yu
Qun Yu
JXJiang Xijuan
Jiang Xijuan
NLRP3 inflammasome is a vital player in macrophages pyroptosis, which is a type of proinflammatory cell-death and takes part in the pathogenesis of atherosclerosis. In this study, we used apoE−/− mice and ox-LDL induced THP-1 derived macrophages to explore the mechanisms of MCC950, a selective NLRP3 inhibitor in treating atherosclerosis. For the in vivo study, MCC950 was intraperitoneal injected to 8-week-old apoE−/− mice fed with high-fat diet for 12 weeks. For the in vitro study, THP-1 derived macrophages were treated with ox-LDL and MCC950 for 48 h. MCC950 administration reduced plaque areas and macrophages contents, but did not improve the serum lipid profiles in aortic root of apoE−/− mice. MCC950 inhibited the activation of NLRP3/ASC/Caspase-1/GSDMD-N axis, and alleviated macrophages pyroptosis and the production of IL-1β and IL-18 both in aorta and in cell lysates. However, MCC950 did not affect the expression of TLR4 or the mRNA levels of NLRP3 inflammasome and its downstream proteins, suggesting that MCC950 had no effects on the priming of NLRP3 inflammasome activation in macrophages. The anti-atherosclerotic mechanisms of MCC950 on attenuating macrophages inflammation and pyroptosis involved in inhibiting the assembly and activation of NLRP3 inflammasome, rather than interrupting its priming.

9 February 2026 in Acupuncture and Herbal Medicine
Verified
Journal Article
Open access
TXTong Xia
Tong Xia
FHFa-Yin Huang
Fa-Yin Huang
SLShi-Qi Li
Shi-Qi Li
YYYi-Jing Yan
Yi-Jing Yan
LGLin Guo
Lin Guo
WZWen-Yun Zeng
Wen-Yun Zeng
Objective: To explore the effects of astragalus injection (AI) in patients with diabetic cognitive impairment (DCI). Methods: First, to screen for effective chemical components of astragalus, we searched Traditional Chinese Medicines Systems Pharmacology (TCMSP) and Analysis Platform databases. We then predicted the corresponding potential target genes using Swiss Target Prediction, searched and filtered three disease databases to identify DCI targets, and constructed a drug-component-target-disease interaction network and protein–protein interaction (PPI) network. The core targets and pathways of AI against DCI were predicted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. In vivo experiments demonstrated the efficacy of AI in alleviating diabetes-associated cognitive impairment, whereas in vitro studies verified its anti-inflammatory and antioxidant stress mechanisms. Finally, western blot analysis identified key regulatory proteins involved in inflammation and oxidative stress, proposing a potential mechanism by which AI mitigates DCI through modulation of these proteins. Results: We screened 25 active components of astragalus and 251 drug targets and obtained 220 common targets after intersecting 8,036 DCI targets. GO enrichment analysis showed that astragalus mainly treats DCI by regulating the response to external stimuli, lipopolysaccharide, hypoxia, and oxygen levels. KEGG pathway enrichment analysis revealed that it was mainly involved in cancer, calcium signaling, p53 signaling, vascular endothelial growth factor (VEGF) signaling pathway, and Toll-like receptor (TLR) signaling pathways. Experimental results demonstrated that AI alleviates diabetes-associated cognitive impairment through dual mechanisms: activating the Kelch-like ECH-associated protein (Keap1)/nuclear factor-erythroid-derived related factor 2 (Nrf2) signaling pathway to exert antioxidant effects, and inhibiting the TLR-4/nuclear factor-kappa B (NF-κB) signaling pathway to mitigate neuroinflammation, thereby improving cognitive dysfunction and hyperglycemia. Conclusions: Network pharmacology identified potential AI interventions for DCI, and experiments were conducted to confirm some of the major targets in the predictive signaling pathway. Our study offers new insights into the mechanisms of AI treatment for DCI.