1.The effects of S100A9 gene knockout on lupus-like phenotype in mice.
Jie ZHA ; Xusen ZHANG ; Xiaosi YANG ; Chun YE ; Genhong YAO
Chinese Journal of Cellular and Molecular Immunology 2025;41(4):318-323
Objective To explore the effects of S100 calcium-binding protein A9 (S100A9) gene knockout on the phenotype of systemic lupus erythematosus (SLE) in mice and to clarify the role of S100A9 in the pathogenesis of SLE. Methods Ten female C57BL/6 wild-type and S100A9 knockout (S100A9-KO ) mice were selected, with five wild-type and five S100A9-KO B6 mice receiving imiquimod (IMQ) cream to establish SLE mouse model. The other five wild-type and five S100A9-KO B6 mice were treated as control groups by wiping the skin of the right ear with a cotton swab. After 8 weeks, the mice were sacrificed. The serum was collected from each mouse to detect the levels of anti-double-stranded DNA (dsDNA) antibodies, immunoglobulin G (IgG), B cell activating factor (BAFF), and interleukin 6 (IL-6) using ELISA. The levels of serum creatinine were determined using a sarcosine oxidase method. Urine was collected to measure urinary protein concentration. Kidneys were collected and stained with hematoxylin and eosin (H&E) for evaluating histological changes. Results After IMQ treatment, the length and weight of spleen, levels of serum creatinine, anti-dsDNA antibodies, IgG, BAFF, IL-6, and urinary protein in the IMQ B6 group and IMQ S100A9-KO B6 group were significantly higher than those of the control groups. Lupus-like changes including increased glomerular volume and tubular epithelial swelling were observed in kidneys from the IMQ and IMQ S100A9-KO groups. However, compared with the IMQ B6 group, the IMQ S100A9-KO B6 group exhibited milder levels of serum and urine indicators as well as the lupus-like symptoms. Conclusion IMQ could induce lupus-like symptoms in both wild-type B6 mice and S100A9-KO B6 mice, but the lesions in S100A9 knockout mice are milder. Theses results suggested that S100A9 is involved in and promotes the pathogenesis of SLE.
Animals
;
Lupus Erythematosus, Systemic/chemically induced*
;
Female
;
Calgranulin B/genetics*
;
Mice, Knockout
;
Mice, Inbred C57BL
;
Phenotype
;
Mice
;
Interleukin-6/blood*
;
Disease Models, Animal
;
Antibodies, Antinuclear/blood*
;
B-Cell Activating Factor/blood*
;
Immunoglobulin G/blood*
;
Kidney/pathology*
2.Expert consensus on prognostic evaluation of cochlear implantation in hereditary hearing loss.
Xinyu SHI ; Xianbao CAO ; Renjie CHAI ; Suijun CHEN ; Juan FENG ; Ningyu FENG ; Xia GAO ; Lulu GUO ; Yuhe LIU ; Ling LU ; Lingyun MEI ; Xiaoyun QIAN ; Dongdong REN ; Haibo SHI ; Duoduo TAO ; Qin WANG ; Zhaoyan WANG ; Shuo WANG ; Wei WANG ; Ming XIA ; Hao XIONG ; Baicheng XU ; Kai XU ; Lei XU ; Hua YANG ; Jun YANG ; Pingli YANG ; Wei YUAN ; Dingjun ZHA ; Chunming ZHANG ; Hongzheng ZHANG ; Juan ZHANG ; Tianhong ZHANG ; Wenqi ZUO ; Wenyan LI ; Yongyi YUAN ; Jie ZHANG ; Yu ZHAO ; Fang ZHENG ; Yu SUN
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2025;39(9):798-808
Hearing loss is the most prevalent disabling disease. Cochlear implantation(CI) serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system(Favorable, Marginal, Poor). The consensus focuses on common hereditary non-syndromic hearing loss(such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1) and syndromic hereditary hearing loss(such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome), which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans
;
Cochlear Implantation
;
Prognosis
;
Hearing Loss/surgery*
;
Consensus
;
Connexin 26
;
Mutation
;
Sulfate Transporters
;
Connexins/genetics*
3.Gut microbiota and noninfectious gastroenteritis: a bidirectional Mendelian randomization study
Journal of Preventive Medicine 2025;37(8):814-817
Objective:
To examine the causal relationship between gut microbiota and noninfectious gastroenteritis using bidirectional Mendelian randomization (MR) approach, so as to provide the basis for the prevention and treatment of noninfectious gastroenteritis.
Methods:
Genome-wide association study (GWAS) data of gut microbiota were obtained from the MiBioGen database, comprising 18 340 participants. GWAS data of noninfectious gastroenteritis were obtained from the IEU OpenGWAS database, including 416 adult cases and 7 235 adult controls. The bidirectional MR analysis between gut microbiota and noninfectious gastroenteritis was conducted using inverse-variance weighted method. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger regression, and the MR-PRESSO test.
Results:
Forward MR analyses demonstrated statistically significant associations between a higher risk of noninfectious gastroenteritis and Clostridium gangrenexotoxin genus (OR=2.201, 95%CI: 1.295-3.740) and Ruminococcaceae UCG-013 genus (OR=2.683, 95%CI: 1.258-5.720). Conversely, statistically significant associations were observed between a lower risk of noninfectious gastroenteritis and Eubacterium hallii group (OR=0.534, 95%CI: 0.307-0.927), Lachnospiraceae NK4A136 group (OR=0.490, 95%CI: 0.252-0.953), and Oxalobacter formigenes group (OR=0.561, 95%CI: 0.348-0.903). Reverse MR analysis showed no evidence for the causal association between the aforementioned five types of gut microbiota and noninfectious gastroenteritis (all P>0.05). Sensitivity analyses revealed no evidence of heterogeneity or horizontal pleiotropy (all P>0.05).
Conclusion
Clostridium gangrenexotoxin genus and Ruminococcaceae UCG-013 genus were risk factors for the noninfectious gastroenteritis, while Eubacterium hallii group, Lachnospiraceae NK4A136 group and Oxalobacter formigenes group were protective factors for the noninfectious gastroenteritis.
4.Molecular epidemiology of an acute gastroenteritis outbreak caused by GⅠ.6 Sapovirus in Taizhou, 2024
Jie ZHA ; Yanqiu CAI ; Jiang LI ; Wenjun DAI ; Da WANG
Chinese Journal of Experimental and Clinical Virology 2025;39(3):333-339
Objective:To investigate the pathogen of an acute gastroenteritis outbreak in a school in Taizhou, and to understand the epidemiological characteristics and patterns of the outbreak and the etiology of the pathogen.Methods:Twelve anal swab samples from patients who met the suspected case definition during the outbreak in March 2024 were collected. FilmArray GI was used to screen 22 common pathogens in the 12 samples, and the real-time fluorescent RT-PCR was performed for verification. Nested RT-PCR was used to amplify and sequence the nucleotide sequence of the viral capsid region VP1, and the variability of the sequence sites was analyzed. Based on the sequence relationship, a molecular phylogenetic tree was constructed and the viral genotypes were determined. Molecular transmission network analysis was conducted by integrating field epidemiological information.Results:The VP1 gene sequences were obtained from 8 of the 12 specimens. Systematic evolution showed that the molecular typing of the 8 strains of Sapoviuses (SaV) was all GI.6 genotype, and there was a C/T mutation at position 1236 in the VP1 gene. The inferred molecular transmission network was largely consistent with the information from the field epidemiological investigation, such as the initial infected person being the earliest case of the outbreak, and there was a closer transmission link between the two teachers.Conclusions:This article reported a school outbreak caused by a SaV GI.6 type. We speculated a more reliable molecular transmission network, estimated the rate of gene mutation and provided a reasonable elaboration for the C/T mutation at position 1236 of the VP1 gene.
5.Analysis of risk factors for amputation in patients with diabetic foot ulcer
Jie WANG ; Tianjian ZHA ; Mengyun LIU ; Xiaolong LIU ; Junjie YAO ; Jian ZHANG
Journal of Chinese Physician 2025;27(3):402-407
Objective:To investigate the risk factors of amputation in patients with diabetic foot ulcer (DFU) in order to improve the prognosis and reduce the amputation rate.Methods:The clinical data of 359 DFU patients admitted to the People′s Hospital of Xinjiang Uygur Autonomous Region from January 2017 to August 2021 were retrospectively analyzed, and they were divided into amputation group (161 cases) and non-amputation group (198 cases) according to whether amputation surgery was performed. Demographic characteristics, Wagner grading and other data of the two groups were collected. Forward step logistic regression analysis was used to identify independent risk factors for amputation, and receiver operating characteristic (ROC) curves were used to evaluate the predictive value of each risk factor for amputation in DFU patients.Results:There were significant differences between the amputation and non-amputation groups in terms of previous amputation history, peripheral vascular diseases (PVD), diabetic foot secondary osteomyelitis, diabetic nephropathy (DN), history of angioplasty, Wanger grade, K +, age, white blood cell count, C-reactive protein, high density lipoprotein cholesterol (HDL-C), estimated glomerular filtration rate, cardiac troponin T, and cardiac troponin I, lactic acid (all P<0.05). Previous amputation history ( OR=2.329, 95% CI: 1.092-4.970, P=0.029), DN ( OR=4.091, 95% CI: 2.222-7.532, P<0.001), PVD ( OR=2.556, 95% CI: 1.487-4.395, P=0.001), diabetic foot secondary osteomyelitis ( OR=6.332, 95% CI: 3.595-11.153, P<0.001), Wagner grade were independent risk factors for amputation in DFU patients, HDL-C ( OR=0.392, 95% CI: 0.182-0.842, P=0.016) were protective factors for amputation in DFU patients. Moreover, the combined accuracy of the above factors in predicting amputation in DFU patients was high, and the area under ROC curve was 0.839 (95% CI: 0.798-0.880), sensitivity was 83%, and specificity was 73% ( OR=0.05). Conclusions:Previous amputation history, DN, PVD, diabetic foot secondary osteomyelitis and Wagner grade are independent risk factors for amputation in DFU patients, while HDL-C is a protective factor for amputation in DFU patients. Further investigation will help to establish a stratified system for predicting the risk of diabetic foot, so as to achieve better individualized treatment.
6.Analysis of risk factors for amputation in patients with diabetic foot ulcer
Jie WANG ; Tianjian ZHA ; Mengyun LIU ; Xiaolong LIU ; Junjie YAO ; Jian ZHANG
Journal of Chinese Physician 2025;27(3):402-407
Objective:To investigate the risk factors of amputation in patients with diabetic foot ulcer (DFU) in order to improve the prognosis and reduce the amputation rate.Methods:The clinical data of 359 DFU patients admitted to the People′s Hospital of Xinjiang Uygur Autonomous Region from January 2017 to August 2021 were retrospectively analyzed, and they were divided into amputation group (161 cases) and non-amputation group (198 cases) according to whether amputation surgery was performed. Demographic characteristics, Wagner grading and other data of the two groups were collected. Forward step logistic regression analysis was used to identify independent risk factors for amputation, and receiver operating characteristic (ROC) curves were used to evaluate the predictive value of each risk factor for amputation in DFU patients.Results:There were significant differences between the amputation and non-amputation groups in terms of previous amputation history, peripheral vascular diseases (PVD), diabetic foot secondary osteomyelitis, diabetic nephropathy (DN), history of angioplasty, Wanger grade, K +, age, white blood cell count, C-reactive protein, high density lipoprotein cholesterol (HDL-C), estimated glomerular filtration rate, cardiac troponin T, and cardiac troponin I, lactic acid (all P<0.05). Previous amputation history ( OR=2.329, 95% CI: 1.092-4.970, P=0.029), DN ( OR=4.091, 95% CI: 2.222-7.532, P<0.001), PVD ( OR=2.556, 95% CI: 1.487-4.395, P=0.001), diabetic foot secondary osteomyelitis ( OR=6.332, 95% CI: 3.595-11.153, P<0.001), Wagner grade were independent risk factors for amputation in DFU patients, HDL-C ( OR=0.392, 95% CI: 0.182-0.842, P=0.016) were protective factors for amputation in DFU patients. Moreover, the combined accuracy of the above factors in predicting amputation in DFU patients was high, and the area under ROC curve was 0.839 (95% CI: 0.798-0.880), sensitivity was 83%, and specificity was 73% ( OR=0.05). Conclusions:Previous amputation history, DN, PVD, diabetic foot secondary osteomyelitis and Wagner grade are independent risk factors for amputation in DFU patients, while HDL-C is a protective factor for amputation in DFU patients. Further investigation will help to establish a stratified system for predicting the risk of diabetic foot, so as to achieve better individualized treatment.
7.Molecular epidemiology of an acute gastroenteritis outbreak caused by GⅠ.6 Sapovirus in Taizhou, 2024
Jie ZHA ; Yanqiu CAI ; Jiang LI ; Wenjun DAI ; Da WANG
Chinese Journal of Experimental and Clinical Virology 2025;39(3):333-339
Objective:To investigate the pathogen of an acute gastroenteritis outbreak in a school in Taizhou, and to understand the epidemiological characteristics and patterns of the outbreak and the etiology of the pathogen.Methods:Twelve anal swab samples from patients who met the suspected case definition during the outbreak in March 2024 were collected. FilmArray GI was used to screen 22 common pathogens in the 12 samples, and the real-time fluorescent RT-PCR was performed for verification. Nested RT-PCR was used to amplify and sequence the nucleotide sequence of the viral capsid region VP1, and the variability of the sequence sites was analyzed. Based on the sequence relationship, a molecular phylogenetic tree was constructed and the viral genotypes were determined. Molecular transmission network analysis was conducted by integrating field epidemiological information.Results:The VP1 gene sequences were obtained from 8 of the 12 specimens. Systematic evolution showed that the molecular typing of the 8 strains of Sapoviuses (SaV) was all GI.6 genotype, and there was a C/T mutation at position 1236 in the VP1 gene. The inferred molecular transmission network was largely consistent with the information from the field epidemiological investigation, such as the initial infected person being the earliest case of the outbreak, and there was a closer transmission link between the two teachers.Conclusions:This article reported a school outbreak caused by a SaV GI.6 type. We speculated a more reliable molecular transmission network, estimated the rate of gene mutation and provided a reasonable elaboration for the C/T mutation at position 1236 of the VP1 gene.
8.Predictive value of balanced steady-state free precession MRI combined with IVIM-DWI and Gd-DTPA enhancement for extramural vascular status in rectal cancer
Jun ZHANG ; Hai-Qing ZHANG ; Yan-Jun LIU ; Peng XIA ; Bing YU ; Hui-Jie ZHA
Chinese Journal of Current Advances in General Surgery 2024;27(5):369-372
Objective:To investigate the predictive value of MRI balanced steady-state free precession(b SSFP)synergistic voxel incoherent motion diffusion weighted imaging(IVIM-DWI)and Gd-DTPA enhanced scanning for the status of extramural vascular invasion(EMVI)in rectal cancer before surgery.Methods:A total of 105 rectal cancer patients from the People's Hospital of Lujiang County,Anhui Province,were retrospectively selected and included.All patients were confirmed by postoperative pathology and underwent preoperative b SSFP sequences,IVIM-DWI functional imaging,and Gd-DTPA-enhanced multiparameter MRI scans.Three seven-point schemes based on individual b SSFP sequences,IVIM-DWI functional imaging,and Gd-DTPA en-hancement,two-by-two synergy,and multi-sequence combined diagnosis were utilized in con-junction with conventional MRI sequences for preoperative prediction of EMVI status.The diag-nostic efficacy of T2WI and b SSFP sequences was compared with that of postoperative patho-logic results.ROC curves were plotted to obtain the corresponding area under the ROC curve(AUC),specificity,and sensitivity.Results:The AUC for predicting the preoperative vascular status outside the rectal wall was 0.572(95%CI:0.408~0.737)for the conventional T2 lipid sup-pression sequence,with a specificity of 0.811 and a sensitivity of 0.667.The AUC for the b SSPF sequence was 0.817(95%CI:0.680~0.954),with a specificity of 0.900 and a sensitivity of 0.733.All of the statistical parameters were higher than the diagnostic efficacy of conventional T2 lipid suppression sequences.The multi-sequence MRI co-diagnosis had an AUC of 0.961(95%CI:0.886~1.000),with a specificity of 0.988 and a sensitivity of 0.875(P<0.05).Conclusion:Mag-netic resonance b SSFP sequence synergized with IVIM-DWI and Gd-DTPA-enhanced multipa-rameter scanning has high clinical application value for the preoperative prediction of EMVI inva-sion in rectal cancer.
9.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
10.Mechanism of Anti-cancer Essence Formula in the treatment of gastric cancer based on network pharmacology
Shuihong YU ; Zhenzhen WU ; Jing XIA ; Jie ZHA ; Huijuan LIU
Journal of Shenyang Medical College 2024;26(3):237-243
Objective:To investigate the pharmacological basis and mechanism of Anti-cancer Essence Formula in the treatment of gastric cancer based on network pharmacology,and to provide bioinformatics basis for the clinical treatment of gastric cancer with traditional Chinese medicine.Methods:The active ingredients of Anti-cancer Essence Formula were searched in TCMSP database,and the targets of the active ingredients were further obtained using UniProt database.The targets of gastric cancer were obtained using GeneCards,OMIM and TTD databases.Cytoscape 3.9.1 software was used to build the"Disease-Component-Target"network.String database and Cytoscape 3.9.1 software were used to construct the PPI network.The transcript levels of the core genes were analyzed by UALCAN database,and the relationship between core gene expression and patient survival was analyzed by Kaplan-Meier plotter.GO function and KEGG pathway enrichment analyses were performed by DAVID database.Results:There were 236 active ingredients of Anti-Cancer Essence Formula,and 16 key targets were screened by PPI network.MAPK3,MAPK1,RELA,AKT1,TP53,FOS,MAPK14,RXRA,MAPK8 and EGFR were abnormally expressed in gastric cancer tissues(P<0.05),and all of them showed correlation with the prognosis of gastric cancer patients(P<0.05).GO analysis was mainly enriched in cell division,cell proliferation and apoptosis,and KEGG analysis was mainly enriched in cancer pathway,MAPK signaling pathway,Relaxin signaling pathway,TNF signaling pathway,T-cell receptor signaling pathway,Prolactin signaling pathway,and PI3K-Akt signaling pathway.Conclusion:Anti-cancer Essence Formula is characterized by the synergistic effect of multi-components,multi-targets,and multi-pathways.It mainly acts on the targets of MAPK3,MAPK1,RELA,AKT1,TP53,FOS,MAPK14,RXRA,MAPK8,and EGFR through the active ingredients such as quercetin,kaempferol,β-sitosterol,and racemic carvacrol.It also regulates the signaling pathways of MAPK,Relaxin,TNF,T-cell receptor,Prolactin,and PI3K-Akt.


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