scholarly journals Metabolic responses to elevated pCO2 in the gills of the Pacific Oyster (Magallana gigas) using a GC-TOF-MS-based metabolomics approach

2018 ◽  
Author(s):  
Zengjie Jiang ◽  
Xiaoqin Wang ◽  
Samuel P.S. Rastrick ◽  
Jinghui Fang ◽  
Meirong Du ◽  
...  
Keyword(s):  
Atmospheric Carbon Dioxide ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Tca Cycle ◽  
Potential Effect ◽  
Metabolic Responses ◽  
Pathway Enrichment Analysis ◽  
Human Fossil ◽  
Flight Mass Spectrometry ◽  
Tof Ms

Rising atmospheric carbon dioxide (CO2), primarily from human fossil fuel combustion and cement production, are resulting in increasing absorption of CO2 by the oceans, which has led to a decline in ocean pH in a process known as ocean acidification (OA). There is a growing body of evidence demonstrating the potential effect of OA on life-history traits of marine organisms. Consequently, gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) based metabolic profiling approach was applied to examine the metabolic responses of Magallana gigas to elevated pCO2 levels, under otherwise natural field conditions. CO2. Oysters were exposed natural environmental pCO2 (~625.40 μatm) and elevated pCO2 (~1432.94 μatm) levels for 30 days. Results indicated that 36 differential metabolites with variable importance in the projection (VIP) value greater than 1 and Student's t-test lower than 0.05 were identified. Differential metabolites were mapped in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to search for the related metabolic pathways. Pathway enrichment analysis indicates that alanine, aspartate and glutamate metabolism and glycine, serine and threonine metabolism were the most statistically enriched pathways. Further analysis suggested that elevated pCO2 disturb the TCA cycle via succinate accumulation and Magallana gigas most likely adjust their energy metabolic via alanine and GABA accumulation accordingly to cope with elevated pCO2. These findings provide an understanding of the molecular mechanisms involved in modulating metabolism under elevated pCO2 levels associated with predicted OA.

scholarly journals Metabolic responses to elevated pCO2 in the gills of the Pacific Oyster (Magallana gigas) using a GC-TOF-MS-based metabolomics approach

2018 ◽  
Author(s):  
Zengjie Jiang ◽  
Xiaoqin Wang ◽  
Samuel P.S. Rastrick ◽  
Jinghui Fang ◽  
Meirong Du ◽  
...  
Keyword(s):  
Atmospheric Carbon Dioxide ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Tca Cycle ◽  
Potential Effect ◽  
Metabolic Responses ◽  
Pathway Enrichment Analysis ◽  
Human Fossil ◽  
Flight Mass Spectrometry ◽  
Tof Ms

Rising atmospheric carbon dioxide (CO2), primarily from human fossil fuel combustion and cement production, are resulting in increasing absorption of CO2 by the oceans, which has led to a decline in ocean pH in a process known as ocean acidification (OA). There is a growing body of evidence demonstrating the potential effect of OA on life-history traits of marine organisms. Consequently, gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) based metabolic profiling approach was applied to examine the metabolic responses of Magallana gigas to elevated pCO2 levels, under otherwise natural field conditions. CO2. Oysters were exposed natural environmental pCO2 (~625.40 μatm) and elevated pCO2 (~1432.94 μatm) levels for 30 days. Results indicated that 36 differential metabolites with variable importance in the projection (VIP) value greater than 1 and Student's t-test lower than 0.05 were identified. Differential metabolites were mapped in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to search for the related metabolic pathways. Pathway enrichment analysis indicates that alanine, aspartate and glutamate metabolism and glycine, serine and threonine metabolism were the most statistically enriched pathways. Further analysis suggested that elevated pCO2 disturb the TCA cycle via succinate accumulation and Magallana gigas most likely adjust their energy metabolic via alanine and GABA accumulation accordingly to cope with elevated pCO2. These findings provide an understanding of the molecular mechanisms involved in modulating metabolism under elevated pCO2 levels associated with predicted OA.

Metabolic responses of shrimp Palaemonetes sinensis to isopod Tachaea chinensis parasitization

2020 ◽  
Vol 138 ◽  
pp. 227-235 ◽  
Author(s):  
Y Li ◽  
W Xu ◽  
X Li ◽  
Z Han ◽  
R Zhang ◽  
...  
Keyword(s):  
Amino Acids ◽  
Inflammatory Responses ◽  
Grass Shrimp ◽  
Enrichment Analysis ◽  
Tca Cycle ◽  
Metabolic Responses ◽  
Pathway Enrichment Analysis ◽  
Primary Metabolite ◽  
Mineral Absorption ◽  
Host Interaction

Tachaea chinensis, a parasitic isopod, negatively affects the production of several commercially important shrimp species in China. The mechanism of parasite-host interaction cannot be accurately described by transcriptomic and proteomic approaches individually. Here, comparative metabolite profiling was used to achieve a broad coverage of primary metabolite changes in Chinese grass shrimp Palaemonetes sinensis following T. chinensis parasitization. In total, 66 metabolites were significantly differentially accumulated between the control and infected groups; of these, 19 were upregulated and 47 were downregulated after T. chinensis infection. Moreover, the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that 10 pathways were significantly enriched. The protein digestion and absorption pathways were highly enriched, followed by the mineral absorption, aminoacyl-tRNA biosynthesis, biosynthesis of amino acids, and metabolic metabolism pathways. Parasitization by T. chinensis enhanced the glycolytic pathway and tricarboxylic acid (TCA) cycle in P. sinensis, thereby releasing more energy for swimming, foraging, and evading predation. Glucogenic amino acids such as alanine, histidine, glutamine, and proline were consumed to generate glutamate and enhance the TCA cycle. Nucleotide-related metabolic pathways were downregulated, possibly because T. chinensis can secrete molecules to degrade nucleotides and inhibit hemostasis and inflammatory responses. These results suggest that the isopod parasite can increase the host’s metabolic burden by enhancing the host’s TCA cycle and secreting molecules to degrade host proteins, thereby enabling the parasite to feed on the host and inhibit an inflammatory response. The results will be a valuable contribution to understanding the metabolic responses of crustaceans to isopod parasitism.

scholarly journals Analysis of MCM Proteins’ Role as a Potential Target of Statins in Patients with Acute Type A Aortic Dissection through Bioinformatics

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 387
Author(s):  
Zheyong Liang ◽  
Yongjian Zhang ◽  
Qiang Chen ◽  
Junjun Hao ◽  
Haichen Wang ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Molecular Mechanisms ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Type A ◽  
Protective Role ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Acute Type ◽  
Type A Aortic Dissection

Acute aortic dissection is one of the most severe vascular diseases. The molecular mechanisms of aortic expansion and dissection are unclear. Clinical studies have found that statins play a protective role in aortic dissection development and therapy; however, the mechanism of statins’ effects on the aorta is unknown. The Gene Expression Omnibus (GEO) dataset GSE52093, GSE2450and GSE8686 were analyzed, and genes expressed differentially between aortic dissection samples and normal samples were determined using the Networkanalyst and iDEP tools. Weight gene correlation network analysis (WGCNA), functional annotation, pathway enrichment analysis, and the analysis of the regional variations of genomic features were then performed. We found that the minichromosome maintenance proteins (MCMs), a family of proteins targeted by statins, were upregulated in dissected aortic wall tissues and play a central role in cell-cycle and mitosis regulation in aortic dissection patients. Our results indicate a potential molecular target and mechanism for statins’ effects in patients with acute type A aortic dissection.

scholarly journals Metabonomic-Transcriptome Integration Analysis on Osteoarthritis and Rheumatoid Arthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Ningyang Gao ◽  
Li Ding ◽  
Jian Pang ◽  
Yuxin Zheng ◽  
Yuelong Cao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gap Junction ◽  
Molecular Mechanisms ◽  
Linear Models ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Nf Kappa B ◽  
Linear Module ◽  
Hedgehog Acyltransferase

Purpose. This study is aimed at exploring the potential metabolite/gene biomarkers, as well as the differences between the molecular mechanisms, of osteoarthritis (OA) and rheumatoid arthritis (RA). Methods. Transcriptome dataset GSE100786 was downloaded to explore the differentially expressed genes (DEGs) between OA samples and RA samples. Meanwhile, metabolomic dataset MTBLS564 was downloaded and preprocessed to obtain metabolites. Then, the principal component analysis (PCA) and linear models were used to reveal DEG-metabolite relations. Finally, metabolic pathway enrichment analysis was performed to investigate the differences between the molecular mechanisms of OA and RA. Results. A total of 976 DEGs and 171 metabolites were explored between OA samples and RA samples. The PCA and linear module analysis investigated 186 DEG-metabolite interactions including Glycogenin 1- (GYG1-) asparagine_54, hedgehog acyltransferase- (HHAT-) glucose_70, and TNF receptor-associated factor 3- (TRAF3-) acetoacetate_35. Finally, the KEGG pathway analysis showed that these metabolites were mainly enriched in pathways like gap junction, phagosome, NF-kappa B, and IL-17 pathway. Conclusions. Genes such as HHAT, GYG1, and TRAF3, as well as metabolites including glucose, asparagine, and acetoacetate, might be implicated in the pathogenesis of OA and RA. Metabolites like ethanol and tyrosine might participate differentially in OA and RA progression via the gap junction pathway and phagosome pathway, respectively. TRAF3-acetoacetate interaction may be involved in regulating inflammation in OA and RA by the NF-kappa B and IL-17 pathway.

scholarly journals Elucidation of the mechanisms and molecular targets of Qishen Yiqi formula for the treatment of pulmonary arterial hypertension using a bioinformatics/network topology-based strategy

2020 ◽  
Vol 23 ◽  
Author(s):  
Peiliang Wu ◽  
Xiaona Xie ◽  
Mayun Chen ◽  
Junwei Sun ◽  
Luqiong Cai ◽  
...  
Keyword(s):  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Network Topology ◽  
Molecular Mechanisms ◽  
Molecular Targets ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Bioactive Ingredients ◽  
Pulmonary Arterial

Background and Objective: Qishen Yiqi formula (QSYQ) is used to treat cardiovascular disease in the clinical practice of traditional Chinese medicine. However, few studies have explored whether QSYQ affects pulmonary arterial hypertension (PAH), and the mechanisms of action and molecular targets of QSYQ for the treatment of PAH are unclear. A bioinformatics/network topology-based strategy was used to identify the bioactive ingredients, putative targets, and molecular mechanisms of QSYQ in PAH. Methods: A network pharmacology-based strategy was employed by integrating active component gathering, target prediction, PAH gene collection, network topology, and gene enrichment analysis to systematically explore the multicomponent synergistic mechanisms. Results: In total, 107 bioactive ingredients of QSYQ and 228 ingredient targets were identified. Moreover, 234 PAH-related differentially expressed genes with a |fold change| >2 and an adjusted P value < 0.005 were identified between the PAH patient and control groups, and 266 therapeutic targets were identified. The pathway enrichment analysis indicated that 85 pathways, including the PI3K-Akt, MAPK, and HIF-1 signaling pathways, were significantly enriched. TP53 was the core target gene, and 7 other top genes (MAPK1, RELA, NFKB1, CDKN1A, AKT1, MYC, and MDM2) were the key genes in the gene-pathway network based on the effects of QSYQ on PAH. Conclusion: An integrative investigation based on network pharmacology may elucidate the multicomponent synergistic mechanisms of QSYQ in PAH and lay a foundation for further animal experiments, human clinical trials and rational clinical applications of QSYQ.

scholarly journals Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yun Tang ◽  
Xiaobo Yang ◽  
Huaqing Shu ◽  
Yuan Yu ◽  
Shangwen Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Acute Kidney Injury ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Kidney Injury ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

scholarly journals Identification of Urine Metabolic Biomarkers for Vogt-Koyanagi-Harada Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Rui Chang ◽  
Ying Zhu ◽  
Jing Xu ◽  
Lin Chen ◽  
Guannan Su ◽  
...  
Keyword(s):  
High Performance ◽  
Area Under The Curve ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Healthy Controls ◽  
Roc Curve Analysis ◽  
Multivariate Statistical ◽  
Flight Mass Spectrometry ◽  
Laboratory Biomarkers ◽  
Vkh Disease

The diagnosis of Vogt-Koyanagi-Harada (VKH) disease is mainly based on a complex clinical manifestation while it lacks objective laboratory biomarkers. To explore the potential molecular biomarkers for diagnosis and disease activity in VKH, we performed an untargeted urine metabolomics analysis by ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS). Through univariate and multivariate statistical analysis, we found 9 differential metabolites when comparing VKH patients with healthy controls, and 26 differential metabolites were identified when comparing active VKH patients with inactive VKH patients. Pathway enrichment analysis showed that glycine, serine and threonine metabolism, and arginine and proline metabolism were significantly altered in VKH versus healthy controls. Lysine degradation and biotin metabolism pathways were significantly altered in active VKH versus inactive VKH. Furthermore, the receiver operating characteristic (ROC) curve analysis revealed that the combination of acetylglycine and gamma-glutamylalanine could differentiate VKH from healthy controls with an area under the curve (AUC) of 0.808. A combination of ureidopropionic acid and 5′-phosphoribosyl-5-amino-4-imidazolecarboxamide (AICAR) had an excellent AUC of 0.958 for distinguishing active VKH from inactive VKH. In summary, this study identified abnormal metabolites in urine of patients with VKH disease. Further studies are needed to confirm whether these metabolites are specific for this disease.

scholarly journals Gene Expression Profile of Active HE4 Stimulation in Epithelial Ovarian Cancer Cells: Microarray Study and Comprehensive Bioinformatics Analysis

2020 ◽  
Author(s):  
Liancheng Zhu ◽  
Mingzi Tan ◽  
Haoya Xu ◽  
Bei Lin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Clinical Significance ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Coexpression Analysis ◽  
Pathway Enrichment

Abstract Background.Human Epididymis Protein 4 (HE4) is a novel serum biomarker for diagnosis of epithelial ovarian cancer (EOC) with high specificity and sensitivity compared with CA125, and the increasing researches have been carried out on its roles in promoting carcinogenesis and chemoresistance in EOC in recent years, however, its underlying molecular mechanisms remain poorly understood. The aim of this study was to elucidate the molecular mechanisms of HE4 stimulation and to identify the key genes and pathways mediating carcinogenesis in EOC using microarray and bioinformatics analysis.Methods. We established a stable HE4-silence ES-2 ovarian cancer cell line labeled as “S”, and its active HE4 protein stimulated cells labeled as “S4”. Human whole genome microarray analysis was used to identify deferentially expressed genes (DEGs) from triplicate samples of S4 and S cells. “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis (GSEA) were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal for WFDC2 coexpression analysis. GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction (qRT-PCR) was applied for validation. The protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape. Results.In total, 713 DEGs were found (164 up regulated and 549 down regulated) and further analyzed by GO, pathway enrichment and PPI analyses. We found that MAPK pathway accounted for a significant portion of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2 coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) that were also dramatically changed in S4 cells and validated by dataset GSE51088. Kaplan–Meier survival statistics revealed clinical significance for all of the 10 target genes. Finally, PPI was constructed, sixteen hub genes and eight molecular complex detections (MCODEs) were identified, the seeds of five most significant MCODEs were subjected to GO and KEGG enrichment analysis and their clinical significance was evaluated.Conclusions.By applying microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network of active HE4 stimulation in EOC cells. We offered several possible mechanisms and identified therapeutic and prognostic targets of HE4 in EOC.

Metabolomic alterations associated with copper stress in Cryptococcus neoformans

2021 ◽  
Author(s):  
Tianshu Sun ◽  
Xiaogang Li ◽  
Wei Song ◽  
Shuying Yu ◽  
Linqi Wang ◽  
...  
Keyword(s):  
Cryptococcus Neoformans ◽  
Metabolic Profile ◽  
Pathogenic Fungus ◽  
Copper Toxicity ◽  
Enrichment Analysis ◽  
Copper Stress ◽  
Pathway Enrichment Analysis ◽  
Flight Mass Spectrometry ◽  
Opportunistic Pathogenic ◽  
Better Than

Background: Copper stress is an effective host strategy in resisting the opportunistic pathogenic fungus Cryptococcus neoformans. We studied metabolic changes in C. neoformans under copper stress. Materials & methods: Wild-type and metallothionein-null C. neoformans were treated with copper on agar containing glucose, glycerol or ethanol as the carbon source and their metabolites were analyzed by untarget metabolomics strategy using gas chromatography coupled with time of flight mass spectrometry. Results: The metabolic profile of C. neoformans varied in the presence and absence of copper. Pathway enrichment analysis showed that the differentially abundant metabolites were related to amino acid and carbohydrate metabolism. C. neoformans grown on glycerol or ethanol resisted copper toxicity better than C. neoformans grown on glucose. Conclusion: Copper stress alters the metabolic profile of C. neoformans.

Gene expression profiles following active HE4 stimulation in epithelial ovarian cancer cells: microarray study and comprehensive bioinformatics analysis

2020 ◽  
Author(s):  
Liancheng Zhu ◽  
Mingzi Tan ◽  
Haoya Xu ◽  
Bei Lin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Coexpression Analysis ◽  
Pathway Enrichment

Abstract Background: Human epididymis protein 4 (HE4) is a novel serum biomarker for diagnosing epithelial ovarian cancer (EOC) with high specificity and sensitivity, compared with CA125. Recent studies have focused on the roles of HE4 in promoting carcinogenesis and chemoresistance in EOC; however, the molecular mechanisms underlying its action remain poorly understood. This study was conducted to determine the molecular mechanisms underlying HE4 stimulation and identifying key genes and pathways mediating carcinogenesis in EOC by microarray and bioinformatics analysis.Methods: We established a stable HE4-silenced ES-2 ovarian cancer cell line labeled as “S”; the S cells were stimulated with the active HE4 protein, yielding cells labeled as “S4”. Human whole-genome microarray analysis was used to identify differentially expressed genes (DEGs) in S4 and S cells. The “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal was used for WFDC2 coexpression analysis. The GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction were used to validate the results. Protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape, respectively. Results: In total, 713 DEGs were identified (164 upregulated and 549 downregulated) and further analyzed by GO, pathway enrichment, and PPI analyses. We found that the MAPK pathway accounted for a significant large number of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2-coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) whose expression levels were dramatically altered in S4 cells; this was validated using the GSE51088 dataset. Kaplan–Meier survival statistics revealed that all 10 target genes were clinically significant. Finally, in the PPI network, 16 hub genes and 8 molecular complex detections (MCODEs) were identified; the seeds of the five most significant MCODEs were subjected to GO and KEGG enrichment analyses and their clinical relevance was evaluated.Conclusions: Through microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network following active HE4 stimulation in EOC cells. We proposed several possible mechanisms underlying the action of HE4 and identified the therapeutic and prognostic targets of HE4 in EOC.

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