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Li Z, Wang S, Yin X, Tao D, Wang X, Zhang J. Identification and Validation of Diagnostic Model Based on Angiogenesis- and Epithelial Mesenchymal Transition-Related Genes in Myocardial Infarction. Int J Gen Med 2024; 17:3239-3255. [PMID: 39070220 PMCID: PMC11283268 DOI: 10.2147/ijgm.s465411] [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: 05/23/2024] [Accepted: 07/03/2024] [Indexed: 07/30/2024] Open
Abstract
Background Myocardial infarction (MI) is a chronic cardiovascular disease. This study aims to discern potentially angiogenesis- and epithelial mesenchymal transition (EMT)-related genes as biomarkers for MI diagnosis through bioinformatics. Methods All datasets and angiogenesis- and EMT-related genes were collected from the public database. The differentially expressed genes (DEGs) of MI and MI-related genes were acquired. DEGs, MI-related genes, and angiogenesis- and EMT-related genes were intersected to obtain hub genes. Functional enrichment, immune microenvironment, and transcription factors (TFs)-hub genes regulatory network analysis were performed. The diagnostic markers and models were developed and validated. Drug prediction and molecular docking were performed. Finally, diagnostic markers expressions were validated using RT-qPCR. Results A total of 224 angiogenesis- and EMT-related genes, 2,897 DEGs, 1,217 MI-related genes, and 9 hub genes were acquired. The immune infiltration levels of plasma cells, T cells CD4 memory activated, monocytes, macrophages M0, mast cells resting, and neutrophils were higher in patients with MI. LRPAP1, COLGALT1, QSOX1, THBD, VCAN, PLOD1, and PLAUR as the diagnostic markers were identified and used to construct diagnostic models, which can distinguish MI from controls well. Then, 9 drugs were screened, and the binding energies ranged from -7.08 to -5.21 kcal/mol. RT-qPCR results showed that the expression of LRPAP1, PLAUR, and PLOD1 was significantly increased in the MI group. Conclusion The 7 diagnostic markers may play potential roles in MI and could contribute to improved future diagnostics.
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Affiliation(s)
- Zhengmei Li
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, People’s Republic of China
| | - Shiai Wang
- Department of Cardiovascular Medicine, The Seventh People’s Hospital of Jinan, Jinan, Shandong, People’s Republic of China
| | - Xunli Yin
- Department of Cardiovascular Medicine, The Seventh People’s Hospital of Jinan, Jinan, Shandong, People’s Republic of China
| | - Dong Tao
- Department of Cardiovascular Medicine, The Seventh People’s Hospital of Jinan, Jinan, Shandong, People’s Republic of China
| | - Xuebing Wang
- Department of Cardiovascular Medicine, The Seventh People’s Hospital of Jinan, Jinan, Shandong, People’s Republic of China
| | - Junli Zhang
- Department of Emergency Medicine, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, People’s Republic of China
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Zhu Y, Chen Y, Xu J, Zu Y. Unveiling the Potential of Migrasomes: A Machine-Learning-Driven Signature for Diagnosing Acute Myocardial Infarction. Biomedicines 2024; 12:1626. [PMID: 39062199 PMCID: PMC11274667 DOI: 10.3390/biomedicines12071626] [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: 06/18/2024] [Revised: 07/16/2024] [Accepted: 07/19/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND Recent studies have demonstrated that the migrasome, a newly functional extracellular vesicle, is potentially significant in the occurrence, progression, and diagnosis of cardiovascular diseases. Nonetheless, its diagnostic significance and biological mechanism in acute myocardial infarction (AMI) have yet to be fully explored. METHODS To remedy this gap, we employed an integrative machine learning (ML) framework composed of 113 ML combinations within five independent AMI cohorts to establish a predictive migrasome-related signature (MS). To further elucidate the biological mechanism underlying MS, we implemented single-cell RNA sequencing (scRNA-seq) of cardiac Cd45+ cells from AMI-induced mice. Ultimately, we conducted mendelian randomization (MR) and molecular docking to unveil the therapeutic effectiveness of MS. RESULTS MS demonstrated robust predictive performance and superior generalization, driven by the optimal combination of Stepglm and Lasso, on the expression of nine migrasome genes (BMP1, ITGB1, NDST1, TSPAN1, TSPAN18, TSPAN2, TSPAN4, TSPAN7, TSPAN9, and WNT8A). Notably, ITGB1 was found to be predominantly expressed in cardiac macrophages in AMI-induced mice, mechanically regulating macrophage transformation between anti-inflammatory and pro-inflammatory. Furthermore, we showed a positive causality between genetic predisposition towards ITGB1 expression and AMI risk, positioning it as a causative gene. Finally, we showed that ginsenoside Rh1, which interacts closely with ITGB1, could represent a novel therapeutic approach for repressing ITGB1. CONCLUSIONS Our MS has implications in forecasting and curving AMI to inform future diagnostic and therapeutic strategies for AMI.
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Affiliation(s)
- Yihao Zhu
- International Research Center for Marine Biosciences, Ministry of Science and Technology, Shanghai Ocean University, Shanghai 201306, China
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China
| | - Yuxi Chen
- International Research Center for Marine Biosciences, Ministry of Science and Technology, Shanghai Ocean University, Shanghai 201306, China
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China
| | - Jiajin Xu
- Department of Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang 212013, China
| | - Yao Zu
- International Research Center for Marine Biosciences, Ministry of Science and Technology, Shanghai Ocean University, Shanghai 201306, China
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China
- Marine Biomedical Science and Technology Innovation Platform of Lin-Gang Special Area, Shanghai 201306, China
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Yang X, Huang Y, Tang D, Yue L. Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization study. PLoS One 2024; 19:e0305532. [PMID: 39024234 PMCID: PMC11257238 DOI: 10.1371/journal.pone.0305532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 06/02/2024] [Indexed: 07/20/2024] Open
Abstract
OBJECTIVE Acute myocardial infarction (AMI) is a severe condition with high morbidity and mortality rates. This study aimed to identify hub genes potentially associated with AMI and assess their clinical utility in predicting AMI occurrence. METHODS Gene microarray data were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were conducted on samples from patients with AMI and control samples to identify modules significantly associated with AMI. GO and KEGG analyses were applied to investigate the potential functions of these hub genes. Lastly, the mendelian randomization (MR) method was applied to analyze the causal relationship between the hub gene TNF and AMI. RESULTS 285 differentially expressed genes (DEGs) were identified through WCGNA and were clustered into 6 modules. The yellow module appeared most relevant to AMI. Further exploration through GO and KEGG pathway enrichment showed that key hub genes in the yellow module were linked to positive regulation of cytokine production, cytokine receptor binding, NF-kappa B signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. The top 10 genes identified through Cytoscape software analysis were IL1B, TNF, TLR4, TLR2, FCGR3B, MMP9, CXCL8, TLR8, ICAM1, and JUK. Utilizing inverse variance weighting (IVW) analysis, we discovered a significant association between TNF and AMI risk, with an OR of 0.946 (95% CI = 0.911-0.984, p = 0.005). CONCLUSIONS The result of this study indicated that TNF, TLR2, TLR4, IL1B and FCGR3B may be potential biodiagnostic markers for AMI. TNF can inhibit inflammatory and oxidative stress responses in AMI, exerting a protective role in the heart.
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Affiliation(s)
- Xiaohe Yang
- Department of Cardiology, Guangyuan Hospital of Traditional Chinese Medicine, Guangyuan, China
| | - Yingtao Huang
- Department of Orthopedics, Liaoning University of Traditional Chinese Medicine, Shenyang, China
| | - Dadong Tang
- School of Clinical College of Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Liangming Yue
- Department of Cardiology, Guangyuan Hospital of Traditional Chinese Medicine, Guangyuan, China
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Gao W, Wang XY, Wang XJ, Huang L. An integrated signature of clinical metrics and immune-related genes as a prognostic indicator for ST-segment elevation myocardial infarction patient survival. Heliyon 2024; 10:e31247. [PMID: 38813183 PMCID: PMC11133808 DOI: 10.1016/j.heliyon.2024.e31247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 04/26/2024] [Accepted: 05/13/2024] [Indexed: 05/31/2024] Open
Abstract
Background The immune-inflammatory pathway plays a critical role in myocardial infarction development. However, few studies have systematically explored immune-related genes in relation to myocardial infarction prognosis using bioinformatic analysis. Our study aims to identify differentially expressed immune-related genes(DEIRGs) in ST-segment elevation myocardial infarction (STEMI) patients and investigate their association with clinical outcomes. Materials and methods We conducted a systematic review of Gene Expression Omnibus datasets, selecting GSE49925, GSE60993, and GSE61144 for analysis. DEIRGs were identified using GEO2R and overlapped across the chosen datasets. Functional enrichment analysis elucidated the DEIRGs' biological functions and pathways. We established an optimal prognostic prediction model using LASSO penalized Cox proportional hazards regression. The signature's clinical utility was evaluated through survival analysis, ROC curve assessment, and decision curve analysis. Additionally, we constructed a prognostic nomogram for survival rate prediction. External validation was performed using our own plasma samples. Results The resulting prognostic signature integrated two dysregulated DEIRGs (S100A12 and IL2RB) and two clinical variables (serum creatinine level and Gensini score). This signature effectively stratified patients into low- and high-risk groups. Survival analysis, ROC curve analysis, and decision curve analysis demonstrated its robust predictive performance and clinical utility within the first two years post-disease onset. External validation confirmed significant outcome differences between risk groups. Conclusions Our study establishes a prognostic signature that combines DEIRGs and clinical variables for STEMI patients. The signature exhibits promising predictive capabilities for patient stratification and survival risk assessment.
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Affiliation(s)
- Wei Gao
- Department of Heart Center, Tianjin Third Central Hospital, Tianjin, 300170, PR China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin Third Central Hospital, Tianjin, 300170, PR China
- Artificial Cell Engineering Technology Research Center, Tianjin, 300170, PR China
- Tianjin Institute of Hepatobiliary Disease, Tianjin, 300170, PR China
| | - Xiao-yan Wang
- Institute of Biomedical Science, Fudan University, Shanghai, 200030, PR China
| | - Xing-jie Wang
- Clinical Laboratory of Tianjin Chest Hospital, Tianjin, 300222, PR China
| | - Lei Huang
- Department of Heart Center, Tianjin Third Central Hospital, Tianjin, 300170, PR China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin Third Central Hospital, Tianjin, 300170, PR China
- Artificial Cell Engineering Technology Research Center, Tianjin, 300170, PR China
- Tianjin Institute of Hepatobiliary Disease, Tianjin, 300170, PR China
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Sharma V, Singh J, Kumar A, Kansara S, Akhtar MS, Khan MF, Aldosari SA, Mukherjee M, Sharma AK. Integrative experimental validation of concomitant miRNAs and transcription factors with differentially expressed genes in acute myocardial infarction. Eur J Pharmacol 2024; 971:176540. [PMID: 38552938 DOI: 10.1016/j.ejphar.2024.176540] [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: 01/09/2024] [Revised: 03/21/2024] [Accepted: 03/26/2024] [Indexed: 04/20/2024]
Abstract
Identification of concomitant miRNAs and transcription factors (TFs) with differential expression (DEGs) in MI is crucial for understanding holistic gene regulation, identifying key regulators, and precision in biomarker and therapeutic target discovery. We performed a comprehensive analysis using Affymetrix microarray data, advanced bioinformatic tools, and experimental validation to explore potential biomarkers associated with human pathology. The search strategy includes the identification of the GSE83500 dataset, comprising gene expression profiles from aortic wall punch biopsies of MI and non-MI patients, which were used in the present study. The analysis identified nine distinct genes exhibiting DEGs within the realm of MI. miRNA-gene/TF and TF-gene/miRNA regulatory relations were mapped to retrieve interacting hub genes to acquire an MI miRNA-TF co-regulatory network. Furthermore, an animal model of I/R-induced MI confirmed the involved gene based on quantitative RT-PCR and Western blot analysis. The consequences of the bioinformatic tool substantiate the inference regarding the presence of three key hub genes (UBE2N, TMEM106B, and CXADR), a central miRNA (hsa-miR-124-3p), and sixteen TFs. Animal studies support the involvement of predicted genes in the I/R-induced myocardial infarction assessed by RT-PCR and Western blotting. Thus, the final consequences suggest the involvement of promising molecular pathways regulated by TF (p53/NF-κB1), miRNA (hsa-miR-124-3p), and hub gene (UBE2N), which may play a key role in the pathogenesis of MI.
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Affiliation(s)
- Vikash Sharma
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India
| | - Jitender Singh
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India
| | - Ashish Kumar
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India
| | - Samarth Kansara
- Amity Institute of Biotechnology, Amity University Haryana, Panchgaon, Manesar, Haryana, 122413, India
| | - Md Sayeed Akhtar
- Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Alfara, Abha, 62223, Saudi Arabia
| | - Mohd Faiyaz Khan
- Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Saad A Aldosari
- Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Monalisa Mukherjee
- Molecular Sciences and Engineering Laboratory, Amity Institute of Click Chemistry Research and Studies, Amity University, Noida, Uttar Pradesh, 201303, India
| | - Arun K Sharma
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India.
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Ke D, Ni J, Yuan Y, Cao M, Chen S, Zhou H. Identification and Validation of Hub Genes Related to Neutrophil Extracellular Traps-Mediated Cell Damage During Myocardial Infarction. J Inflamm Res 2024; 17:617-637. [PMID: 38323113 PMCID: PMC10844013 DOI: 10.2147/jir.s444975] [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: 11/06/2023] [Accepted: 01/23/2024] [Indexed: 02/08/2024] Open
Abstract
Purpose Studies have shown that neutrophil-mediated formation of neutrophil extracellular traps (NETs) leads to increased inflammatory response and cellular tissue damage during myocardial infarction (MI). We aimed to identify and validate possible hub genes in the process of NETs-mediated cell damage. Methods We performed an immune cell infiltration analysis of the MI transcriptome dataset based on CIBERSORT and ssGSEA algorithms. Gene expression profiles of NETs formation (GSE178883) were used to analyze the physiological processes of peripheral blood neutrophils after phorbol myristate acetate (PMA) stimulation. Bioinformatics and machine learning algorithms were utilized to find candidate hub genes based on NETs-related genes and transcriptome datasets (GSE66360 and GSE179828). We generated the receiver operating curve (ROC) to evaluate the diagnostic value of hub genes. Next, the correlation between hub genes and immune cells was analyzed using CIBERSORT, ssGSEA and xCell algorithms. Finally, we used quantitative real-time PCR (qRT-PCR) and immunohistochemistry to verify gene expression. Results Immune cell infiltration analysis revealed that inflammatory cells such as neutrophils were highly expressed in the peripheral blood of patients with MI. Functional analysis of differentially expressed genes (DEGs) in GSE178883 indicated that the potential pathogenesis lies in immune terms. Using weighted gene co-expression network analysis (WGCNA) and machine learning algorithms, we finally identified the seven hub genes (FCAR, IL1B, MMP9, NFIL3, CXCL2, ICAM1, and ZFP36). The qRT-PCR results showed that IL-1B, MMP9, and NFIL3 mRNA expression was up-regulated in the MI group compared to the control. Immunohistochemical results showed high MMP9, IL-1B, and NFIL3 expression in the infarcted area compared to the non-infarcted area and sham-operated groups. Conclusion We identified seven hub genes associated with NETs-mediated cellular damage during MI. Our results may provide insights into the mechanisms of neutrophil-mediated cell injury during MI.
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Affiliation(s)
- Da Ke
- Department of Cardiology, Renmin Hospital of Wuhan University, Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, 430060, People’s Republic of China
| | - Jian Ni
- Department of Cardiology, Renmin Hospital of Wuhan University, Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, 430060, People’s Republic of China
| | - Yuan Yuan
- Department of Cardiology, Renmin Hospital of Wuhan University, Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, 430060, People’s Republic of China
| | - Mingzhen Cao
- Department of Cardiology, Renmin Hospital of Wuhan University, Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, 430060, People’s Republic of China
| | - Si Chen
- Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, 430060, People’s Republic of China
| | - Heng Zhou
- Department of Cardiology, Renmin Hospital of Wuhan University, Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, 430060, People’s Republic of China
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Tang C, Yang C, Wang P, Li L, Lin Y, Yi Q, Tang F, Liu L, Zhou W, Liu D, Zhang L, Yuan X. Identification and Validation of Glomeruli Cellular Senescence-Related Genes in Diabetic Nephropathy by Multiomics. Adv Biol (Weinh) 2024; 8:e2300453. [PMID: 37957539 DOI: 10.1002/adbi.202300453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 10/08/2023] [Indexed: 11/15/2023]
Abstract
Accumulating evidence indicates that cellular premature senescence of the glomerulus, including endothelial cells, mesangial cells, and podocytes leads to diabetic nephropathy (DN), and DN is regarded as a clinical model of premature senescence. However, the role of cellular senescence-associated genes in the glomerulus in DN progression remains unclear. Therefore, this work aims to identify and validate potential cellular aging-related genes in the glomerulus in DN to provide novel clues for DN treatment based on anti-aging. The microarray GSE96804 dataset, including 41 diabetic glomeruli and 20 control glomeruli, is retrieved from the Gene Expression Omnibus (GEO) database and cellular senescence-related genes (CSRGs) are obtained from the GeneCards database and literature reports. Subsequently, PPI, GO, and KEGG enrichment are analyzed by screening the intersection between differentially expressed genes (DEGs) and CSRGs. scRNA-seq dataset GSE127235 is used to verify core genes expression in glomerulocytes of mice. Finally, db/db mice are utilized to validate the hub gene expression in the glomeruli, and high glucose-induced mesangial cells are used to confirm key gene expression. This study reveals that FOS and ZFP36 may play an anti-aging role in DN to ameliorate cell intracellular premature aging in mesangial cells of glomeruli.
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Affiliation(s)
- Chunyin Tang
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
- College of Life Science, Mudanjiang Medical University, Mudanjiang, 157000, China
| | - Chunsong Yang
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
| | - Peiwen Wang
- College of Life Science, Mudanjiang Medical University, Mudanjiang, 157000, China
| | - Luxin Li
- College of Life Science, Mudanjiang Medical University, Mudanjiang, 157000, China
| | - Yunzhu Lin
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
| | - Qiusha Yi
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
| | - Fengru Tang
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
| | - Lantao Liu
- Postgraduate Department, Mudanjiang Medical University, Mudanjiang, 157011, China
| | - Wei Zhou
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
| | - Dongwen Liu
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
| | - Lingli Zhang
- Evidence-Based Pharmacy Center, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, 610000, China
| | - Xiaohuan Yuan
- College of Life Science, Mudanjiang Medical University, Mudanjiang, 157000, China
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