Baopeng Tang

Dr. Baopeng Tang

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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13 December 2022 in Frontiers in Cardiovascular Medicine
Verified
Journal Article
Open access
JXJie Xiang
Jie Xiang
JSJun Shen
Jun Shen
LZLing Zhang
Ling Zhang
BTBaopeng Tang
Baopeng Tang
Background: Acute myocardial infarction (AMI) is the main clinical cause of death and cardiovascular disease and thus has high rates of morbidity and mortality. The increase in cardiovascular disease with aging is partly the result of vascular endothelial cell senescence and associated vascular dysfunction. This study was performed to identify potential key cellular senescence-related genes (SRGs) as biomarkers for the diagnosis of AMI using bioinformatics.Methods: Using the CellAge database, we identified cellular SRGs. GSE66360 and GSE48060 for AMI patients and healthy controls and GSE19322 for mice were downloaded from the Gene Expression Omnibus (GEO) database. The GSE66360 dataset was divided into a training set and a validation set. The GSE48060 dataset was used as another validation set. The GSE19322 dataset was used to explore the evolution of the screened diagnostic markers in the dynamic process of AMI. Differentially expressed genes (DEGs) of AMI were identified from the GSE66360 training set. Differentially expressed senescence-related genes (DESRGs) selected from SRGs and DEGs were analyzed using Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. Hub genes in DESRGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed.Results: A total of 520 DEGs were screened from the GSE66360 training set, and 279 SRGs were identified from the CellAge database. The overlapping DEGs and SRGs constituted 14 DESRGs, including 4 senescence suppressor genes and 10 senescence inducible genes. The top 10 hub genes, including FOS, MMP9, CEBPB, CDKN1A, CXCL1, ETS2, BCL6, SGK1, ZFP36, and IGFBP3, were screened. Furthermore, three diagnostic genes were identified: MMP9, ETS2, and BCL6. The ROC analysis showed that the respective area under the curves (AUCs) of MMP9, ETS2, and BCL6 were 0.786, 0.848, and 0.852 in the GSE66360 validation set and 0.708, 0.791, and 0.727 in the GSE48060 dataset. In the GSE19322 dataset, MMP9 (AUC, 0.888) and ETS2 (AUC, 0.929) had very high diagnostic values in the early stage of AMI. Finally, based on these three diagnostic genes, we found that drugs such as acetylcysteine and genistein may be targeted for the treatment of age-related AMI.Conclusion: The results of this study suggest that cellular SRGs might play an important role in AMI. MMP9, ETS2, and BCL6 have potential as specific biomarkers for the early diagnosis of AMI.

16 October 2018 in Journal of the American Heart Association
Verified
Journal Article
Open access
WZWen‐Hui Zhang
Wen‐Hui Zhang
QZQi‐Na Zhou
Qi‐Na Zhou
YLYan‐Mei Lu
Yan‐Mei Lu
YLYao‐Dong Li
Yao‐Dong Li
LZLing Zhang
Ling Zhang
XZXianhui Hui Zhou
Xianhui Hui Zhou
Background: Ventricular arrhythmia after myocardial infarction is the most important risk factor for sudden cardiac death, which poses a serious threat to human health. As the correlation between autonomic nervous systemic dysfunction and heart rhythm abnormality has been gradually revealed, remedies targeting autonomic nervous system dysfunction, especially the sympathetic nerve, have emerged. Among them, renal denervation is noted for its powerful effect on the inhibition of sympathetic nerve activity. We aim to investigate whether renal denervation can reduce ventricular arrhythmia after myocardial infarction and thus decrease the risk of sudden cardiac death. In addition, we explore the potential mechanism with respect to nerve activity and remodeling. Methods and Results: Twenty‐four beagles were randomized into the control (n=4), renal denervation (n=10), and sham (n=10) groups. Permanent left anterior descending artery ligation was performed to establish myocardial infarction in the latter 2 groups. Animals in the renal denervation group underwent both surgical and chemical renal denervation. Compared with dogs in the sham group, dogs in the renal denervation group demonstrated attenuated effective refractory period shortening and inhomogeneity, flattened restitution curve, increased ventricular threshold, and decreased ventricular arrhythmia. Heart rate variability assessment, catecholamine measurement, and nerve discharge recordings all indicated that renal denervation could reduce whole‐body and local tissue sympathetic tone. Tissue analysis revealed a significant decrease in neural remodeling in both the heart and stellate ganglion. Conclusions: Surgical and chemical renal denervation decreased whole‐body and local tissue sympathetic activity and reversed neural remodeling in the heart and stellate ganglion. Consequently, renal denervation led to beneficial remodeling of the electrophysiological characteristics in the infarction border zone, translating to a decrease in ventricular arrhythmia after myocardial infarction.

19 November 2020 in Frontiers in Physiology
Verified
Journal Article
Open access
PDF file
WLWenkui Lv
Wenkui Lv
LZLing Zhang
Ling Zhang
XCXinchun Cheng
Xinchun Cheng
HWHongli Wang
Hongli Wang
WQWen Qin
Wen Qin
BTBaopeng Tang
Baopeng Tang
Background: Angiotensin II (Ang II) could promote the development of atrial fibrosis in atrial fibrillation (AF). Apelin can inhibit the occurrence of myocardial fibrosis. However, the effect of apelin on Ang II-induced atrial fibrosis and subsequent AF still remains unknown.Objective: In the present study, we examined the effect of apelin on the suppression of atrial fibrosis and subsequent AF, and investigated its underlying mechanisms.Methods: Sprague-Dawley rats were treated for 2 weeks with Ang II (1080 μg/kg/24 h) and apelin-13 (140 μg/kg/24 h) using implantable mini-pumps. The incidence of AF induced by atrial pacing was determined. Atrial electrophysiological mapping was recorded by a 32-electrode microelectrode array. Blood was collected to measure the levels of Ang II and apelin. Atrial tissue samples were preserved to assess the pathohistological changes, DDR2 and α-SMA co-staining were performed, and the protein expression of Smad2 phosphorylation was evaluated.Results: Apelin significantly inhibited Ang II-induced atrial fibrosis (HE:1.45 ± 0.11 vs 6.12 ± 0.16, P < 0.001; Masson:1.49 ± 0.25 vs 8.15 ± 0.23, P < 0.001; Picrosirius Red:1.98 ± 0.64 vs 9.59 ± 0.56, P < 0.001, respectively) and decreased the vulnerability of AF (inducibility of AF: z = −4.40, P < 0.001; total AF duration: z = −4.349, P < 0.001). Left atrial epicardial mapping studies demonstrated preservation of atrial conduction homogeneity by apelin. The protective effects of apelin from fibrotic remodeling were mediated by suppression of Smad2-dependent fibrosis.Conclusion: Apelin potently inhibited Ang II-induced atrial fibrosis and subsequent vulnerability to AF induction via suppression TGF-β/Smad2/α-SMA pathway. Our results indicated that apelin might be an effective up-stream therapy for atrial fibrosis and AF.

1 June 2022 in Journal of Cardiothoracic and Vascular Anesthesia
Verified
Journal Article
Closed access
PDF file
XZXiao-Xue Zhang
Xiao-Xue Zhang
MWMeng Wei
Meng Wei
RXRan Xiang
Ran Xiang
YLYan-Mei Lu
Yan-Mei Lu
LZLing Zhang
Ling Zhang
XZXian-Hui Zhou
Xian-Hui Zhou

24 January 2025 in Heart Rhythm
Verified
Journal Article
Closed access
YXYuankai Xu
Yuankai Xu
TGTaalaibek Kyzy Gulburak
Taalaibek Kyzy Gulburak
YLYanmei Lu
Yanmei Lu
JZJianghua Zhang
Jianghua Zhang
ZTZukela TuErhong
Zukela TuErhong
XZXianhui Hui Zhou
Xianhui Hui Zhou

30 July 2020 in Infection
Verified
Journal Article
Closed access
PDF file
LCLi Cheng
Li Cheng
建杨建中 杨
建中 杨
WBWen-Hui Bai
Wen-Hui Bai
ZLZhuan-Yun Li
Zhuan-Yun Li
LSLi-Fang Sun
Li-Fang Sun
BTBaopeng Tang
Baopeng Tang