Wenzhi Guo

First Affiliated Hospital of Zhengzhou University

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Shuijun Zhang

First Affiliated Hospital of Zhengzhou University

153

Jihua Shi

First Affiliated Hospital of Zhengzhou University

Peihao Wen

First Affiliated Hospital of Zhengzhou University

Yuting He

First Affiliated Hospital of Zhengzhou University

Jiakai Zhang

First Affiliated Hospital of Zhengzhou University

Hongwei Tang

First Affiliated Hospital of Zhengzhou University

Shengli Cao

First Affiliated Hospital of Zhengzhou University

Huapeng Zhang

First Affiliated Hospital of Zhengzhou University

Jie Gao

First Affiliated Hospital of Zhengzhou University

Xiao Yu

Third Xiangya Hospital

Cooperative Institutions

First Affiliated Hospital of Zhengzhou University

294

Shanghai Jiao Tong University

152

Sun Yat-sen University

133

Chinese Academy of Medical Sciences & Peking Union Medical College

127

Zhengzhou University

119

Chinese Academy of Sciences

103

Zhejiang University

101

Fudan University

100

Sichuan University

Capital Medical University

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Advances in Pharmacological Research on Icaritin: A Comprehensive Review

The American Journal of Chinese Medicine (2025)

Ran Guo Zhiping Yan Rui Wang Tongxuan Guo Hao Li

Epimedium has been widely used in traditional Chinese medicine for several thousands of years. This plant is known for tonifying kidney Yang, strengthening muscles and bones, and dispelling wind and dampness. It is worth noting that icaritin, a prenylated flavonoid isolated from Epimedium, has received increasing attention in recent years due to its wide range of pharmacological activities. Icaritin exhibits significant therapeutic potential against various diseases, such as osteoporosis, tumors (hepatocellular carcinoma, stomach cancer, breast cancer, and glioblastoma), cerebral ischemia skin injury, thrombocytopenia, and systemic lupus erythematosus. We review the pharmacological activities of icaritin and its potential molecular mechanisms for the treatment of related diseases. The data suggest that icaritin can have the pharmacological effects of mediating Wnt/[Formula: see text]-catenin, IL-6/JAK2/STAT3, AMPK/mTOR, PTEN/AKT, MAPK, NF-[Formula: see text]B, and other signaling pathways. This paper also discusses the progress of clinical trials of icaritin. Icaritin was approved by the State Food and Drug Administration in January 2022 for the treatment of advanced HCC, and has various clinical drug prospects. Although it has some disadvantages, including poor solubility, and low bioavailability, icaritin is still a prospective candidate for the development of naturally derived drugs, especially in the treatment of tumors and inflammatory diseases. This review aims to update and deepen the understanding of icaritin, and provide a theoretical basis for its further study.

Epimedium

10.1142/s0192415x25500089

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Experimental study on the wound characteristics of high explosive bomb injury to goats

Journal of Traumatic Surgery (2005)

Wenzhi Guo

Objective To observe the wounding characteristics of the high explosive bomb injurys to goats.Methods Thirty-two goats were placed around the explosive center with the distances from the explosive center 10,10m(in trench),15m,15m(in trench),20,25,30,40,50,65,80m respectively.The animal number at the different distances were 3,3,3,2,3,3,3,3,3,3,3 respectively.All animals faced the explosive center by the right side of their bodies.The high explosive bomb was placed 1.6m high from the ground and initiated by electro-primer.Results Twenty-one goats were dead immediately after the bomb explosion(65.63%),and 3 goats were dead with in 18 hours after being injured (6.25%) .Eight goats were alive longer than 18 hours after being injured(25.0%).Destructive injuries were found in 6 goats (18.72%) .The survivial rates of animals at two different distances trench were 1/3and 2/2.The rate of the fragment wounds,blast injuries,mulitiple injuries,comples injuries and fractures were 68.75%,37.5%,65.63%,6.25% and 42.75% respectively,in which the rate of the blind wounds and perforated wounds were 12.20% and 87.80%.Conclusion The explosion of high explosive bomb induced a combined effects of fragments and shock waves,which caused complicated wound type and wound character,to which must be paid more attention in the treatment.There are protective effects of trench against fragment and shock wave.

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MicroRNA-297a regulates vascular calcification by targeting fibroblast growth factor 23.

DOAJ (DOAJ: Directory of Open Access Journals) (2016)

Shouhua Zheng Shuijun Zhang Yan Song Wenzhi Guo Wenlong Zhai

Vascular calcification is one the major characteristics in patients with various types of chronic inflammatory disorders. MiRNAs have been shown to be involved in many normal biological functions as well as diseases; however, their role in vascular calcification has not received much attention.In the current study, we built a vascular calcification rat model using vitamin D3 plus nicotine and analyzed miRNA expression profile by miRNA chip assay. Potential target of one selected miRNA with sharpest variation in expression were predicted by both PicTar and TargetScan. The impact of the selected miRNA on the expression of the potential target on both mRNA and protein levels were measured by RT-PCR and Western blot, respectively.Our results identified 16 dysregulated miRNAs, among which miR-297a showed the sharpest variation. Further analysis focusing on miR-297a revealed that fibroblast growth factor 23 (FGF23) was a potential target of miR297a. Measurement of FGF23 and its regulator Klotho on both mRNA and protein levels demonstrated that FGF23 was significantly increased while Klotho was decreased in rats with vascular calcification.Our results indicated that FGF23 was target of miR-297a and decreased miR-297a in vascular calcification lead to the increase of FGF23, which together with Klotho might enhance vascular calcification. The findings of this study could provide valuable information for the understanding of mechanisms underlying miR-dependent vascular calcification as well as potential treatment target for the disease.

Klotho

10.22038/ijbms.2016.7920

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Single-cell sequencing and establishment of an 8-gene prognostic model for pancreatic cancer patients

Frontiers in Oncology (2022)

Xiao Yu Qiyao Zhang Shuijun Zhang Yuting He Wenzhi Guo

Single-cell sequencing (SCS) technologies enable analysis of gene structure and expression data at single-cell resolution. However, SCS analysis in pancreatic cancer remains largely unexplored.We downloaded pancreatic cancer SCS data from different databases and applied appropriate dimensionality reduction algorithms. We identified 10 cell types and subsequently screened differentially expressed marker genes of these 10 cell types using FindAllMarkers analysis. Also, we evaluated the tumor immune microenvironment based on ESTIMATE and MCP-counter. Statistical enrichment was evaluated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. We used all candidate gene sets in KEGG database to perform gene set enrichment analysis. We used LASSO regression to reduce the number of genes in the pancreatic risk model by R package glmnet, followed by rtPCR to validate the expression of the signature genes in different pancreatic cancer cell lines.We identified 15 cell subpopulations by dimension reduction and data clustering. We divided the 15 subpopulations into 10 distinct cell types based on marker gene expression. Then, we performed functional enrichment analysis for the 352 marker genes in pancreatic cancer cells. Based on RNA expression data and prognostic information from TCGA and GEO datasets, we identified 42 prognosis-related genes, including 5 protective genes and 37 high-risk genes, which we used to identified two molecular subtypes. C1 subtype was associated with a better prognosis, whereas C2 subtype was associated with a worse prognosis. Moreover, chemokine and chemokine receptor genes were differentially expressed between C1 and C2 subtypes. Functional and pathway enrichment uncovered functional differences between C1 and C2 subtype. We identified eight genes that could serve as potential biomarkers for prognosis prediction in pancreatic cancer patients. These genes were used to establish an 8-gene pancreatic cancer prognostic model.We established an 8-gene pancreatic cancer prognostic model. This model can meaningfully predict prognosis and treatment response in pancreatic cancer patients.

KEGG

10.3389/fonc.2022.1000447

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Necroptosis throws novel insights on patient classification and treatment strategies for hepatocellular carcinoma

Frontiers in Immunology (2022)

Bowen Hu Jie Gao Jihua Shi Feng Zhang Chengcheng Shi

Introduction Necroptosis is a novel pattern of immunogenic cell death and has triggered an emerging wave in antitumor therapy. More evidence has suggested the potential associations between necroptosis and intra-tumoral heterogeneity. Currently, the underlying role of necroptosis remains elusive in hepatocellular carcinoma (HCC) at antitumor immunity and inter-tumoral heterogeneity. Methods This study enrolled a total of 728 HCC patients and 139 immunotherapy patients from eight public datasets. The consensus clustering approach was employed to depict tumor heterogeneity of cancer necroptosis. Subsequently, our study further decoded the heterogeneous clinical outcomes, genomic landscape, biological behaviors, and immune characteristics in necroptosis subtypes. For each patient, providing curative clinical recommendations and developing potential therapeutic drugs were used to promote precise medicine. Results With the use of the weighted gene coexpression network analysis (WGCNA) algorithm, necroptosis-associated long non-coding RNAs (lncRNAs) (NALRs) were identified in HCC. Based on the NALR expression, two heterogeneous subtypes were decoded with distinct clinical outcomes. Compared to patients in C1, patients in C2 harbored superior pathological stage and presented more unfavorable overall survival and recurrence-free survival. Then, the robustness and reproducibility of necroptosis subtypes were further validated via the nearest template prediction (NTP) approach and classical immune phenotypes. Through comprehensive explorations, C1 was characterized by enriched immune-inflammatory and abundant immune infiltration, while C2 possessed elevated proliferative and metabolic activities and highly genomic instability. Moreover, our results indicated that C1 was more prone to obtain desirable benefits from immunotherapy. For patients in C2, numerous underlying therapeutic agents were developed, which might produce significant efficacy. Conclusion This study identified two necroptosis subtypes with distinct characteristics, decoding the tumor heterogeneity. For an individualized patient, our work tailored corresponding treatment strategies to improve clinical management.

10.3389/fimmu.2022.970117

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Development of a New Rockbolt with High Load and Large Deformation Capacities

Rock Mechanics and Rock Engineering (2023)

Zhengming Yang Shuai Xu Hao Zhang Wenzhi Guo Ming Cai

Piston (optics)

10.1007/s00603-023-03416-x

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Natural constituents of St. John's Wort inhibit the proteolytic activity of human thrombin

International Journal of Biological Macromolecules (2019)

Ling-Hua Wei Tianran Chen Hongbo Fang Qiang Jin Shuijun Zhang

Hypericin

IC50

Natural product

10.1016/j.ijbiomac.2019.04.181

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Identification of Context-Specific Fitness Genes Associated With Metabolic Rearrangements for Prognosis and Potential Treatment Targets for Liver Cancer

Frontiers in Genetics (2022)

Shizhe Yu Haoren Wang Jie Gao Long Liu Xiaoyan Sun

Liver cancer is the most frequent fatal malignancy. Furthermore, there is a lack of effective therapeutics for this cancer type. To construct a prognostic model for potential beneficiary screens and identify novel treatment targets, we used an adaptive daisy model (ADaM) to identify context-specific fitness genes from the CRISPR-Cas9 screens database, DepMap. Functional analysis and prognostic significance were assessed using data from TCGA and ICGC cohorts, while drug sensitivity analysis was performed using data from the Liver Cancer Model Repository (LIMORE). Finally, a 25-gene prognostic model was established. Patients were then divided into high- and low-risk groups; the high-risk group had a higher stemness index and shorter overall survival time than the low-risk group. The C-index, time-dependent ROC curves, and multivariate Cox regression analysis confirmed the excellent prognostic ability of this model. Functional enrichment analysis revealed the importance of metabolic rearrangements and serine/threonine kinase activity, which could be targeted by trametinib and is the key pathway in regulating liver cancer cell viability. In conclusion, the present study provides a prognostic model for patients with liver cancer and might help in the exploration of novel therapeutic targets to ultimately improve patient outcomes.

Liver Cancer

10.3389/fgene.2022.863536

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Polymorphisms of DNA repair gene XRCC1 and hepatocellular carcinoma risk among East Asians: a meta-analysis

Tumor Biology (2012)

Jie Li Zhenzhen Li Liushun Feng Wenzhi Guo Shuijun Zhang

Association studies on the X-ray repair cross-complementing group 1 (XRCC1) polymorphisms (Arg194Trp, Arg280His, and Arg399Gln) in hepatocellular carcinoma (HCC) have shown conflicting results. The aim of this study was to quantitatively summarize the evidence for such a relationship. Published literatures from PubMed, Embase, CNKI, and Chinese Biomedicine Database were retrieved. Pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated using fixed- or random-effects model. Thirteen studies including 3,011 HCC cases and 3,619 controls were included in the meta-analysis of the association between XRCC1 Arg399Gln polymorphism and HCC risk. The results indicated that Arg399Gln polymorphism was significantly associated with risk of HCC in a codominant model (Gln/Gln vs. Arg/Arg, OR = 1.32, 95 % CI = 1.08–1.61; Arg/Gln vs. Arg/Arg, OR = 1.41, 95 % CI = 1.12–1.80) and a dominant model (Gln/Gln + Arg/Gln vs. Arg/Arg, OR = 1.39, 95 % CI = 1.15–1.69), but not in a recessive model (Gln/Gln vs. Arg/Gln + Arg/Arg, OR = 1.13, 95 % CI = 0.95–1.35). Limiting the analysis to the studies within Hardy–Weinberg equilibrium, the results were persistent and robust. When stratifying for region and source of controls, persistent results were observed in any subgroup. No evidence of association of Arg194Trp (980 HCC cases and 966 controls) and Arg280His (1,200 HCC cases and 1,236 controls) with HCC risk was found. No publication bias was found in the present study. The results from the present meta-analysis indicated that the Arg399Gln polymorphisms of XRCC1 may be a genetic susceptibility for HCC in the East Asian population. Further, large and well-designed studies are needed to confirm this conclusion.

XRCC1

Subgroup analysis

10.1007/s13277-012-0546-5

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ARTIFICIAL NEURAL NETWORK PREDICTION OF PARAMETERS OF NON-LINEAR SEEPAGE MODEL WITH PLANAR INTERSECTING FRACTURES

工程地质学报 (2020)

WU Zhenhua Zhechao Wang Wenzhi Guo Yang Bin Liu Jie

The fluid flow in rock fracture network exists widely in underground engineering,which has important influences on the safety of engineering construction and operation. Therefore,the study of flow in fracture network has important theoretical and practical significance. This paper is based on the flow model of intersecting fractures. The model is derived based on the cubic law and Forchheimer equation. It studies the nonlinear parameters of the flow model of planar intersecting fractures by numerical simulation and artificial neural network. Using the artificial neural network genetic algorithm,the paper explores the relationship between the geometry of the intersecting fractures and the nonlinear coefficient in the flow model. It proves that the nonlinear flow model of the plane intersecting fractures can adequately describe the flow characteristics of the intersecting fractures. It verifies the feasibility and accuracy of the neural network method in predicting the nonlinear coefficient. At the same time,it obtains the characteristics of the two methods of fitting numerical expression and artificial neural network.

Network model

10.13544/j.cnki.jeg.2020-184

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