Peng Ren

Prof. Dr. Peng Ren

orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

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

Representative Publications

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8 June 2024 in Brain, Behavior, and Immunity
Verified
Journal Article
Closed access
JWJing-Ya Wang
Jing-Ya Wang
PRPeng Ren
Peng Ren
LCLin-Yu Cui
Lin-Yu Cui
JDJing-Yao Duan
Jing-Yao Duan
HCHong-Lei Chen
Hong-Lei Chen
YLYun-Feng Li
Yun-Feng Li

8 March 2023 in European Journal of Pharmacology
Verified
Journal Article
Closed access
PRPeng Ren
Peng Ren
JWJing-Ya Wang
Jing-Ya Wang
HCHong-Lei Chen
Hong-Lei Chen
HCHai-Xia Chang
Hai-Xia Chang
ZZZhi-Rui Zeng
Zhi-Rui Zeng
YLYun-Feng Li
Yun-Feng Li

28 January 2025 in Neurochemistry International
Verified
Journal Article
Closed access
PRPeng Ren
Peng Ren
JWJing-Ya Wang
Jing-Ya Wang
MXMeng-Jie Xu
Meng-Jie Xu
HCHong-Lei Chen
Hong-Lei Chen
JDJing-Yao Duan
Jing-Yao Duan
YLYun-Feng Li
Yun-Feng Li

24 November 2025 in Molecular Neurobiology
Verified
Journal Article
Closed access
PDF file
PRPeng Ren
Peng Ren
JWJing-Ya Wang
Jing-Ya Wang
MXMeng-Jie Xu
Meng-Jie Xu
HNHan Ni
Han Ni
SZShuang Zhang
Shuang Zhang
YLYun-Feng Li
Yun-Feng Li


Verified
Journal Article
Open access
PDF file
NLNanxi Li
Nanxi Li
PRPeng Ren
Peng Ren
JWJingya Wang
Jingya Wang
XZXiaohui Zhu
Xiaohui Zhu
XQXuan Qiao
Xuan Qiao
RGRuolan Gu
Ruolan Gu
Sepsis ranks among the most common health problems worldwide, characterized by organ dysfunction resulting from infection. Excessive inflammatory responses, cytokine storms, and immune-induced microthrombosis are pivotal factors influencing the progression of sepsis. Our objective was to identify novel immune-related hub genes for sepsis through bioinformatic analysis, subsequently validating their specificity and potential as diagnostic and prognostic biomarkers in an animal experiment involving a sepsis mice model. Gene expression profiles of healthy controls and patients with sepsis were obtained from the Gene Expression Omnibus (GEO) and analysis of differentially expressed genes (DEGs) was conducted. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to analyze genes within crucial modules. The functional annotated DEGs which related to the immune signal pathways were used for constructing protein–protein interaction (PPI) analysis. Following this, two hub genes, FERMT3 and CD3G, were identified through correlation analyses associated with sequential organ failure assessment (SOFA) scores. These two hub genes were associated with cell adhesion, migration, thrombosis, and T-cell activation. Furthermore, immune infiltration analysis was conducted to investigate the inflammation microenvironment influenced by the hub genes. The efficacy and specificity of the two hub genes were validated through a mice sepsis model study. Concurrently, we observed a significant negative correlation between the expression of CD3G and IL-1β and GRO/KC. These findings suggest that these two genes probably play important roles in the pathogenesis and progression of sepsis, presenting the potential to serve as more stable biomarkers for sepsis diagnosis and prognosis, deserving further study.