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Jiang W, Jiang L, Zhao X, Liu Y, Sun H, Zhou X, Liu Y, Huang S. Bioinformatics Analysis Reveals HIST1H2BH as a Novel Diagnostic Biomarker for Atrial Fibrillation-Related Cardiogenic Thromboembolic Stroke. Mol Biotechnol 2024:10.1007/s12033-024-01187-6. [PMID: 38825608 DOI: 10.1007/s12033-024-01187-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 04/29/2024] [Indexed: 06/04/2024]
Abstract
Atrial fibrillation (AF) is a significant precursor to cerebral embolism. Our study sought to unearth new diagnostic biomarkers for atrial fibrillation-related cerebral embolism (AF-CE) by meticulously examining multiple GEO datasets and meta-analysis. The gene expression omnibus (GEO) database provided RNA sequencing data associated with AF and stroke. We began by pinpointing genes with varied expressions in AF-CE patient blood samples. A meta-analysis was subsequently undertaken using several RNA sequencing datasets to verify these genes. LASSO regression discerned key genes for AF-CE, with their diagnostic prowess verified through ROC curve examination. Active signaling pathways within stroke patients were discerned via GO and KEGG enrichment, with PPI interactions detailing gene interplay. Differential gene analysis revealed an upregulation of sixteen genes and a downregulation of four in stroke patient blood samples. Eight genes showcased varied expression in the meta-analysis. LASSO regression zeroed in on five of these, culminating in HIST1H2BH's identification as a characteristic gene. HIST1H2BH's prowess in predicting AF-CE was confirmed through ROC. Integrin signaling, platelet activation, ECM interactions, and the PI3K-Akt pathway were found active in stroke victims. HIST1H2BH's interaction with the notably upregulated ITGA2B was spotlighted by PPI. Additionally, HIST1H2BH exhibited links with NK cells and eosinophils. HIST1H2BH emerges as an insightful diagnostic beacon for AF-CE. Its presence, post AF, potentially modulates pathways, accentuating platelet activation and consequent thrombus generation, leading to cerebral embolism.
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Affiliation(s)
- Wenbing Jiang
- Department of Cardiology, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, No.75 Jinxiu Road, Lucheng District, Wenzhou, 325000, Zhejiang Province, People's Republic of China.
| | - Lelin Jiang
- Second Clinical College of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, People's Republic of China
| | - Xiaoli Zhao
- Wenzhou Medical University, Wenzhou, Zhejiang, 325000, People's Republic of China
| | - Yiying Liu
- Postgraduate Training Base Allianceof Wenzhou Medical University (Wenzhou Central Hosptial), Wenzhou, Zhejiang, 325000, People's Republic of China
| | - Huanghui Sun
- The Dingli Clinical College of Wenzhou Medical University, Heart Function Examination Room, Wenzhou, Zhejiang, 325000, People's Republic of China
| | - Xinlang Zhou
- Department of Cardiology, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, No.75 Jinxiu Road, Lucheng District, Wenzhou, 325000, Zhejiang Province, People's Republic of China
| | - Yin Liu
- Department of Cardiology, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, No.75 Jinxiu Road, Lucheng District, Wenzhou, 325000, Zhejiang Province, People's Republic of China
| | - Shu'se Huang
- Department of Cardiology, Wenzhou Integrated Traditional Chinese and Western Medicine Hospital, No.75 Jinxiu Road, Lucheng District, Wenzhou, 325000, Zhejiang Province, People's Republic of China
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Pei J, Zhang J, Yu C, Luo J, Wen S, Hua Y, Wei G. Transcriptomics-based exploration of shared M1-type macrophage-related biomarker in acute kidney injury after kidney transplantation and acute rejection after kidney transplantation. Transpl Immunol 2024; 85:102066. [PMID: 38815767 DOI: 10.1016/j.trim.2024.102066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 05/12/2024] [Accepted: 05/27/2024] [Indexed: 06/01/2024]
Abstract
BACKGROUND Macrophage type 1 (M1) cells are associated with both acute kidney injury (AKI) during kidney transplantation and acute rejection (AR) after kidney transplantation. Our study explored M1-related biomarkers involved in both AKI and AR and their potential biological functions. METHODS Based on the Gene Expression Omnibus (GEO) database, the immune cell infiltration levels and differentially expressed genes were examined in AKI and AR in the kidney transplantation; M1-related genes shared in AKI and AR were identified using weighted gene co-expression analysis (WGCNA) system. Subsequently, protein-protein interaction (PPI) networks and machine learning methods to identify Hub genes and construct diagnostic models. Both AKI model and AR rat models were built to validate the expressions of Hub genes and test the injury phenotype, oxidative stress markers, and inflammatory factors. Finally, the transcription factor (TF)-Hub gene and micro-RNA (miRNA)-Hub gene regulatory networks were constructed based on identified Hub genes. RESULTS Out of 2167 differential expression genes (DEGs) in AKI and 2100 DEGs in AR, four M1-related Hub genes were obtained by PPI networks and machine learning methods, namely GBP2, TYROBP, CCR5, and TLR8. The calibration curves in the nomogram diagnostic model for these four Hub genes suggested the same predictive probability as an ideal model for AKI and AR after kidney transplantation (AUC values of the area under the ROC curve were all >0.7). The same observations were confirmed in ischemia reperfusion injury (IRI) and AR rat models by identifying common four Hub genes (GBP2, TYROBP, TLR8, and CCR5). Western blots showed that these four Hub genes were significantly different in rat models of IRI and AR (all p<0.05). Compared with the control group, IRI and AR groups showed aggravated histopathological damage and increased secretion of oxidative stress markers and inflammatory factors in rat kidneys (all p<0.05). Finally, TF-Hub and miRNA-Hub gene regulatory networks were constructed to provide a theoretical basis for the regulation of Hub genes. CONCLUSION We identified four macrophage M1-related Hub genes shared among AKI and AR after kidney transplantation. These genes may be considered for diagnosis of AKI and AR after kidney transplantation.
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Affiliation(s)
- Jun Pei
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
| | - Jie Zhang
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
| | - Chengjun Yu
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
| | - Jin Luo
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
| | - Sheng Wen
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
| | - Yi Hua
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
| | - Guanghui Wei
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
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Wang Y, Xie D, Ma S, Shao N, Zhang X, Wang X. Exploring the common mechanism of vascular dementia and inflammatory bowel disease: a bioinformatics-based study. Front Immunol 2024; 15:1347415. [PMID: 38736878 PMCID: PMC11084673 DOI: 10.3389/fimmu.2024.1347415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 04/15/2024] [Indexed: 05/14/2024] Open
Abstract
Objective Emerging evidence has shown that gut diseases can regulate the development and function of the immune, metabolic, and nervous systems through dynamic bidirectional communication on the brain-gut axis. However, the specific mechanism of intestinal diseases and vascular dementia (VD) remains unclear. We designed this study especially, to further clarify the connection between VD and inflammatory bowel disease (IBD) from bioinformatics analyses. Methods We downloaded Gene expression profiles for VD (GSE122063) and IBD (GSE47908, GSE179285) from the Gene Expression Omnibus (GEO) database. Then individual Gene Set Enrichment Analysis (GSEA) was used to confirm the connection between the two diseases respectively. The common differentially expressed genes (coDEGs) were identified, and the STRING database together with Cytoscape software were used to construct protein-protein interaction (PPI) network and core functional modules. We identified the hub genes by using the Cytohubba plugin. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied to identify pathways of coDEGs and hub genes. Subsequently, receiver operating characteristic (ROC) analysis was used to identify the diagnostic ability of these hub genes, and a training dataset was used to verify the expression levels of the hub genes. An alternative single-sample gene set enrichment (ssGSEA) algorithm was used to analyze immune cell infiltration between coDEGs and immune cells. Finally, the correlation between hub genes and immune cells was analyzed. Results We screened 167 coDEGs. The main articles of coDEGs enrichment analysis focused on immune function. 8 shared hub genes were identified, including PTPRC, ITGB2, CYBB, IL1B, TLR2, CASP1, IL10RA, and BTK. The functional categories of hub genes enrichment analysis were mainly involved in the regulation of immune function and neuroinflammatory response. Compared to the healthy controls, abnormal infiltration of immune cells was found in VD and IBD. We also found the correlation between 8 shared hub genes and immune cells. Conclusions This study suggests that IBD may be a new risk factor for VD. The 8 hub genes may predict the IBD complicated with VD. Immune-related coDEGS may be related to their association, which requires further research to prove.
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Affiliation(s)
- Yujiao Wang
- Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Daojun Xie
- Encephalopathy Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Shijia Ma
- Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Nan Shao
- Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Xiaoyan Zhang
- Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Xie Wang
- Anhui University of Chinese Medicine, Hefei, Anhui, China
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Lv X, Fan Q, Li X, Li P, Wan Z, Han X, Wang H, Wang X, Wu L, Huo B, Yang L, Chen G, Zhang Y. Identification of renal ischemia reperfusion injury-characteristic genes, pathways and immunological micro-environment features through bioinformatics approaches. Aging (Albany NY) 2024; 16:2123-2140. [PMID: 38329418 PMCID: PMC10911371 DOI: 10.18632/aging.205471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 12/15/2023] [Indexed: 02/09/2024]
Abstract
BACKGROUND Biomarkers and pathways associated with renal ischemia reperfusion injury (IRI) had not been well unveiled. This study was intended to investigate and summarize the regulatory networks for related hub genes. Besides, the immunological micro-environment features were evaluated and the correlations between immune cells and hub genes were also explored. METHODS GSE98622 containing mouse samples with multiple IRI stages and controls was collected from the GEO database. Differentially expressed genes (DEGs) were recognized by the R package limma, and the GO and KEGG analyses were conducted by DAVID. Gene set variation analysis (GSVA) and weighted gene coexpression network analysis (WGCNA) had been implemented to uncover changed pathways and gene modules related to IRI. Besides the known pathways such as apoptosis pathway, metabolic pathway, and cell cycle pathways, some novel pathways were also discovered to be critical in IRI. A series of novel genes associated with IRI was also dug out. An IRI mouse model was constructed to validate the results. RESULTS The well-known IRI marker genes (Kim1 and Lcn2) and novel hub genes (Hbegf, Serpine2, Apbb1ip, Trip13, Atf3, and Ncaph) had been proved by the quantitative real-time polymerase chain reaction (qRT-PCR). Thereafter, miRNAs targeted to the dysregulated genes were predicted and the miRNA-target network was constructed. Furthermore, the immune infiltration for these samples was predicted and the results showed that macrophages infiltrated to the injured kidney to affect the tissue repair or fibrosis. Hub genes were significantly positively or negatively correlated with the macrophage abundance indicating they played a crucial role in macrophage infiltration. CONCLUSIONS Consequently, the pathways, hub genes, miRNAs, and the immune microenvironment may explain the mechanism of IRI and might be the potential targets for IRI treatments.
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Affiliation(s)
- Xinghua Lv
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Qian Fan
- Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Nankai University Eye Institute, Nankai University, Clinical College of Ophthalmology, Tianjin Medical University, Tianjin, China
| | - Xuanjie Li
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Peng Li
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Zhanhai Wan
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Xuena Han
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
- The First Clinical Medical College of Lanzhou University, Lanzhou, Gansu Province, China
| | - Hao Wang
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
- The First Clinical Medical College of Lanzhou University, Lanzhou, Gansu Province, China
| | - Xiaoxia Wang
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Lin Wu
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Bin Huo
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Li Yang
- Lanzhou First People's Hospital, Lanzhou, Gansu, China
| | - Gen Chen
- Department of Microbiology, School of Basic Medical Sciences, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China
| | - Yan Zhang
- Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
- The First Clinical Medical College of Lanzhou University, Lanzhou, Gansu Province, China
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Wu L, Li S, Wu C, Wu S, Lin Y, Wei D. Causal relationship between systemic lupus erythematosus and primary liver cirrhosis based on two-sample bidirectional Mendelian randomization and transcriptome overlap analysis. Arthritis Res Ther 2024; 26:10. [PMID: 38167341 PMCID: PMC10762944 DOI: 10.1186/s13075-023-03235-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 12/13/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Overlapping cases of systemic lupus erythematosus (SLE) and primary biliary cirrhosis (PBC) are rare and have not yet been fully proven to be accidental or have a common genetic basis. METHODS Two-sample bidirectional Mendelian randomization (MR) analysis was applied to explore the potential causal relationship between SLE and PBC. The heterogeneity and reliability of MR analysis were evaluated through Cochran's Q-test and sensitivity test, respectively. Next, transcriptome overlap analysis of SLE and PBC was performed using the Gene Expression Omnibus database to identify the potential mechanism of hub genes. Finally, based on MR analysis, the potential causal relationship between hub genes and SLE or PBC was validated again. RESULTS The MR analysis results indicated that SLE and PBC were both high-risk factors for the occurrence and development of the other party. On the one hand, MR analysis had heterogeneity, and on the other hand, it also had robustness. Nine hub genes were identified through transcriptome overlap analysis, and machine learning algorithms were used to verify their high recognition efficiency for SLE patients. Finally, based on MR analysis, it was verified that there was no potential causal relationship between the central gene SOCS3 and SLE, but it was a high-risk factor for the potential risk of PBC. CONCLUSION The two-sample bidirectional MR analysis revealed that SLE and PBC were high-risk factors for each other, indicating that they had similar genetic bases, which could to some extent overcome the limitation of insufficient overlap in case samples of SLE and PBC. The analysis of transcriptome overlapping hub genes provided a theoretical basis for the potential mechanisms and therapeutic targets of SLE with PBC overlapping cases.
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Affiliation(s)
- Linyong Wu
- Department of Medical Ultrasound, Maoming People's Hospital, Maoming, Guangdong, 525000, People's Republic of China
| | - Songhua Li
- Department of Medical Ultrasound, Maoming People's Hospital, Maoming, Guangdong, 525000, People's Republic of China.
| | - Chaojun Wu
- Department of Medical Ultrasound, Maoming People's Hospital, Maoming, Guangdong, 525000, People's Republic of China
| | - Shaofeng Wu
- Department of Medical Ultrasound, Maoming People's Hospital, Maoming, Guangdong, 525000, People's Republic of China
| | - Yan Lin
- Department of Medical Ultrasound, Maoming People's Hospital, Maoming, Guangdong, 525000, People's Republic of China
| | - Dayou Wei
- Department of Medical Ultrasound, Maoming People's Hospital, Maoming, Guangdong, 525000, People's Republic of China.
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Shi H, Yuan X, Liu G, Fan W. Identifying and Validating GSTM5 as an Immunogenic Gene in Diabetic Foot Ulcer Using Bioinformatics and Machine Learning. J Inflamm Res 2023; 16:6241-6256. [PMID: 38145013 PMCID: PMC10748866 DOI: 10.2147/jir.s442388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 12/12/2023] [Indexed: 12/26/2023] Open
Abstract
Background A diabetic foot ulcer (DFU) is a serious, long-term condition associated with a significant risk of disability and mortality. However, research on its biomarkers is still limited. This study utilizes bioinformatics and machine learning methods to identify immune-related biomarkers for DFU and validates them through external datasets and animal experiments. Methods This study used bioinformatics and machine learning to analyze microarray data from the Gene Expression Omnibus (GEO) database to identify key genes associated with DFU. Animal experiments were conducted to validate these findings. This research employs the datasets GSE68183 and GSE80178 retrieved from the GEO database as the training dataset for building a gene machine learning model, and after conducting differential analysis on the data, this study used package glmnet and package e1071 to construct LASSO and SVM-RFE machine learning models, respectively. Subsequently, we validated the model using the training set and validation set (GSE134431). We conducted enrichment analysis, including GSEA and GSVA, on the model genes. We also performed immune functional analysis and immune-related analysis on the model genes. Finally, we conducted immunohistochemistry (IHC) validation on the model genes. Results This study identifies GSTM5 as a potential immune-related key target in DFU using machine learning and bioinformatics methods. Subsequent validation through external datasets and IHC experiments also confirms GSTM5 as a critical biomarker for DFU. The gene may be associated with T cells regulatory (Tregs) and T cells follicular helper, and it influences the NF-κB, GnRH, and MAPK signaling pathway. Conclusion This study identified and validated GSTM5 as a biomarker for DFU. This finding may potentially provide a target for immune therapy for DFU.
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Affiliation(s)
- Hongshuo Shi
- Department of Peripheral Vascular Surgery, Institute of Surgery of Traditional Chinese Medicine, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Xin Yuan
- Department of Peripheral Vascular Surgery, Institute of Surgery of Traditional Chinese Medicine, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Guobin Liu
- Department of Peripheral Vascular Surgery, Institute of Surgery of Traditional Chinese Medicine, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Weijing Fan
- Department of Peripheral Vascular Surgery, Institute of Surgery of Traditional Chinese Medicine, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
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