MicroRNA expression profiling in myopia: a meta-analysis and systematic review

Background: Myopia (nearsightedness) is currently the most common human eye disorder worldwide. In the recent years, several studies have addressed the role of microRNAs (miRNAs) in the pathogenesis of myopia. Objectives: The aim of this study was to perform a meta-analysis on the miRNA expression profiling studies in myopia to identify commonly dysregulated miRNAs in myopic tissues. Method: Seven independent studies were included in the meta-analysis. A vote-counting strategy were employed as the meta-analysis method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Ontology (GO) functional enrichment analysis were performed to identify the pathways most strongly affected by the dysregulated mouse miRNAs. Results: According to the vote-counting method, eighteen miRNAs were reported in at least two studies with the consistent direction, of which 13 miRNAs were commonly up-regulated in myopic samples compared with control samples and five miRNAs were commonly down-regulated. Subgroup analyses divided and compared the differentially expressed miRNAs according to species (human and animal) and ocular tissue types. The KEGG analysis showed that the dysregulated mouse miRNAs were most enriched in extracellular matrix (ECM)-receptor interaction signal pathway. The most enriched GO processes regulated by the dysregulated mouse miRNAs was cellular protein modification process. Conclusions. Our meta-analysis recommends several miRNAs may provide some clues of the potential biomarkers in myopia. Further mechanistic studies are warranted to elucidate the biological role of the dysregulated miRNAs in the development of myopia.

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Is There a Relationship Between Psoriasis and Hepatitis C?: a Meta-analysis and Bioinformatics Investigation

10.21203/rs.3.rs-249926/v1 ◽

2021 ◽

Author(s):

Yong Liu ◽

Sheng Nan Cui ◽

Meng Yao Duan ◽

Zhi Li Dou ◽

Yi Zhen Li ◽

...

Keyword(s):

Hepatitis C ◽

Meta Analysis ◽

Enrichment Analysis ◽

Case Control ◽

Cochrane Library ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Overlapping Genes ◽

Cross Sectional ◽

Pathway Enrichment

Abstract Background: The relationship between psoriasis and hepatitis C was previously controversial, so our purpose is to investigate this connection.Methods: We conducted a systematic review of the case-control, cross-sectional and cohort studies examining the association between psoriasis and hepatitis C in PubMed, EMBASE and Cochrane library databases and investigated the overlapping genes between psoriasis targets and hepatitis C targets using bioinformatics analysis. Based on overlapping genes and hub nodes, we also constructed the protein-protein interaction (PPI) network and module respectively, followed by the pathway enrichment analysis. Results: We included 11 publications that reported a total of 11 studies (8 cross-sectional and 3 case-control). The case–control and cross-sectional studies included 25,047 psoriasis patients and 4,091,631 controls in total. Psoriasis was associated with a significant increase of prevalent hepatitis C (OR 1.72; 95% confidence interval [CI] (1.17-2.52)). A total of 389 significant genes were common to both hepatitis C and psoriasis, which mainly involved IL6, TNF, IL10, ALB, STAT3 and CXCL8. The module and pathway enrichment analyses showed that the common genes had the potential to influence varieties of biological pathways, including the inflammatory response, cytokine activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, which play an important role in the pathogenesis of hepatitis C and psoriasis.Conclusion: Patients with psoriasis display increased prevalence of hepatitis C and the basic related mechanisms between hepatitis C and psoriasis had been preliminarily clarified.

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The Role of Circular RNA CDR1as/ciRS-7 in Regulating Tumor Microenvironment: A Pan-Cancer Analysis

Biomolecules ◽

10.3390/biom9090429 ◽

2019 ◽

Vol 9 (9) ◽

pp. 429 ◽

Cited By ~ 24

Author(s):

Zou ◽

Zheng ◽

Deng ◽

Yang ◽

Xie ◽

...

Keyword(s):

Tumor Microenvironment ◽

Signaling Pathway ◽

Malignant Tumors ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Circular Rna ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Receptor Interaction

Circular RNA CDR1as/ciRS-7 functions as an oncogenic regulator in various cancers. However, there has been a lack of systematic and comprehensive analysis to further elucidate its underlying role in cancer. In the current study, we firstly performed a bioinformatics analysis of CDR1as among 868 cancer samples by using RNA-seq datasets of the MiOncoCirc database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), CIBERSORT, Estimating the Proportion of Immune and Cancer cells (EPIC), and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were applied to investigate the underlying functions and pathways. Functional enrichment analysis suggested that CDR1as has roles associated with angiogenesis, extracellular matrix (ECM) organization, integrin binding, and collagen binding. Moreover, pathway analysis indicated that it may regulate the TGF-β signaling pathway and ECM-receptor interaction. Therefore, we used CIBERSORT, EPIC, and the ESTIMATE algorithm to investigate the association between CDR1as expression and the tumor microenvironment. Our data strongly suggest that CDR1as may play a specific role in immune and stromal cell infiltration in tumor tissue, especially those of CD8+ T cells, activated NK cells, M2 macrophages, cancer-associated fibroblasts (CAFs) and endothelial cells. Generally, systematic and comprehensive analyses of CDR1as were conducted to shed light on its underlying pro-cancerous mechanism. CDR1as regulates the TGF-β signaling pathway and ECM-receptor interaction to serve as a mediator in alteration of the tumor microenvironment.

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Identification of Latent Diagnostic Biomarkers and Biological Pathways in Dermatomyositis Based on WGCNA

Journal of Oncology ◽

10.1155/2021/1920111 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Shaxi Ouyang ◽

Yifang Liu ◽

Changjuan Xiao ◽

Qinghua Zeng ◽

Xun Luo ◽

...

Keyword(s):

Cell Lines ◽

Differentially Expressed Gene ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Receptor Interaction ◽

Interferon Α ◽

Pathway Enrichment Analysis ◽

Oligoadenylate Synthetase

Introduction. Dermatomyositis (DM) is a chronic autoimmune disease of predominantly lymphocytic infiltration mainly involving the transverse muscle. Its pathogenesis is remaining unknown. This research is designed to probe the latent pathogenesis of dermatomyositis, identify potential biomarkers, and reveal the pathogenesis of dermatomyositis through information biology analysis of gene chips. Methods. In this study, we utilised the GSE14287 and GSE11971 datasets rooted in the Gene Expression Omnibus (GEO) databank, which included a total of 62 DM samples and 9 normal samples. The datasets were combined, and the differentially expressed gene sets were subjected to weighted gene coexpression network analysis, and the hub gene was screened using a protein interaction network from genes in modules highly correlated with dermatomyositis progression. Results. A total of 3 key genes—myxovirus resistance-2 (MX2), oligoadenylate synthetase 1 (OAS1), and oligoadenylate synthetase 2 (OAS2)—were identified in combination with cell line samples, and the expressions of the 3 genes were verified separately. The results showed that MX2, OAS1, and OAS2 were highly expressed in LPS-treated cell lines compared to normal cell lines. The results of pathway enrichment analysis of the genes indicated that all 3 genes were enriched in the cytosolic DNA signalling and cytokine and cytokine receptor interaction signalling pathways; the results of functional enrichment analysis showed that all 3 were enriched in interferon-α response and interferon-γ response functions. Conclusions. This is important for the study of the pathogenesis and objective treatment of dermatomyositis and provides important reference information for the targeted therapy of dermatomyositis.

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Meta-Analysis of miRNAs and Their Involvement as Biomarkers in Oral Cancers

BioMed Research International ◽

10.1155/2018/8439820 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 6

Author(s):

Andleeb Zahra ◽

Itrat Rubab ◽

Sumaira Malik ◽

Amina Khan ◽

Muhammad Jawad Khan ◽

...

Keyword(s):

Diagnostic Marker ◽

Meta Analysis ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Oral Carcinoma ◽

Functional Enrichment ◽

Oral Cancers ◽

Extracellular Mirnas ◽

Potential Use

Oral Squamous Cell Carcinoma (OSCC) is one of the most common cancers worldwide. Recent studies have highlighted the role of miRNA in disease pathology, indicating its potential use as an early diagnostic marker. Dysregulated expression of miRNAs is known to affect cell growth, and these may function as tumor suppressors or oncogenes in various cancers. The main objective of this study was to characterize the extracellular miRNAs involved in oral cancer (OC) that can potentially be used as biomarkers of OC. A total of 318 miRNAs involved in oral carcinoma were shortlisted. Differentially expressed genes (DEGs) of oral carcinoma from reported experiments were identified. Common genes between lists of DEGs of OC of each miRNA were identified. These common genes are the targets of specific miRNA, which may be used as biomarkers of OC. A list of significant biomarkers for cancer was generated like CDH2 and CDK7, and functional enrichment analysis identified the role of miRNAs in major pathways like cell adhesion molecules pathway affected by cancer. We observed that at least 25 genes like ABCF3, ALDH2, CD163L1, and so forth are regulated by a maximum number of miRNAs; thereby, they can be used as biomarkers of OC.

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Small Nucleolar RNA and Small Nucleolar RNA Host Gene Signatures as Biomarkers for Pancreatic Cancer

10.21203/rs.3.rs-42719/v1 ◽

2020 ◽

Author(s):

Shuwen Han ◽

Yangyang Xie ◽

Xi Yang ◽

Siqi Dai ◽

Xiaoyu Dai

Keyword(s):

Pancreatic Cancer ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Small Nucleolar Rna ◽

Cerna Network ◽

Tcga Dataset ◽

Nucleolar Rna ◽

Host Genes

Abstract Objective: The objective of this study was to identify key molecules including small nucleolar RNAs (snoRNAs) and small nucleolar RNA host genes (SNHGs) involved in pancreatic cancer.Methods: First, we screened the differentially expressed snoRNAs (DEsnoRNAs) and trend-related snoRNAs based on the cancer genome atlas (TCGA) dataset for pancreatic cancer, and then performed methylation correlation analysis, survival analysis, and extraction of snoRNA host genes for Gene ontology (GO) functional and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Next, DESNHGs and trend-related SNHGs were screened according to the TCGA dataset for pancreatic cancer, and a competing endogenous RNA (ceRNA) network was constructed for pathway and functional enrichment analysis. Results: A total of eight DEsnoRNAs and 93 trend-related snoRNAs were extracted. Then, ten host genes of the snoRNAs were identified. Functional analysis suggested that the ten host genes were significantly enriched in several GO terms including mitotic chromosome condensation and endocytosis pathway. SNORA38B was considered to associate with survival and prognosis. The SNORD17 and SNORA11 were considered to negatively correlate with methylation. In addition, two trend-related SNHGs were extracted. Additionally, a ceRNA network was constructed with 11 miRNAs, one lncRNAs, and one mRNA. SNHG24 mainly correlated with GnRH secretion and neuroactive ligand-receptor interaction in pancreatic cancer. Conclusion: The identified snoRNAs and SNHGs could serve as potential markers for the early detection of pancreatic cancer.

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Integrated transcriptome meta-analysis of pancreatic ductal adenocarcinoma and matched adjacent pancreatic tissues

PeerJ ◽

10.7717/peerj.10141 ◽

2020 ◽

Vol 8 ◽

pp. e10141

Author(s):

Sevcan Atay

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Interaction Analysis ◽

Meta Analysis ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Prognostic Biomarkers ◽

Ductal Adenocarcinoma ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Adjacent Tissue

A comprehensive meta-analysis of publicly available gene expression microarray data obtained from human-derived pancreatic ductal adenocarcinoma (PDAC) tissues and their histologically matched adjacent tissue samples was performed to provide diagnostic and prognostic biomarkers, and molecular targets for PDAC. An integrative meta-analysis of four submissions (GSE62452, GSE15471, GSE62165, and GSE56560) containing 105 eligible tumor-adjacent tissue pairs revealed 344 differentially over-expressed and 168 repressed genes in PDAC compared to the adjacent-to-tumor samples. The validation analysis using TCGA combined GTEx data confirmed 98.24% of the identified up-regulated and 73.88% of the down-regulated protein-coding genes in PDAC. Pathway enrichment analysis showed that “ECM-receptor interaction”, “PI3K-Akt signaling pathway”, and “focal adhesion” are the most enriched KEGG pathways in PDAC. Protein-protein interaction analysis identified FN1, TIMP1, and MSLN as the most highly ranked hub genes among the DEGs. Transcription factor enrichment analysis revealed that TCF7, CTNNB1, SMAD3, and JUN are significantly activated in PDAC, while SMAD7 is inhibited. The prognostic significance of the identified and validated differentially expressed genes in PDAC was evaluated via survival analysis of TCGA Pan-Cancer pancreatic ductal adenocarcinoma data. The identified candidate prognostic biomarkers were then validated in four external validation datasets (GSE21501, GSE50827, GSE57495, and GSE71729) to further improve reliability. A total of 28 up-regulated genes were found to be significantly correlated with worse overall survival in patients with PDAC. Twenty-one of the identified prognostic genes (ITGB6, LAMC2, KRT7, SERPINB5, IGF2BP3, IL1RN, MPZL2, SFTA2, MET, LAMA3, ARNTL2, SLC2A1, LAMB3, COL17A1, EPSTI1, IL1RAP, AK4, ANXA2, S100A16, KRT19, and GPRC5A) were also found to be significantly correlated with the pathological stages of the disease. The results of this study provided promising prognostic biomarkers that have the potential to differentiate PDAC from both healthy and adjacent-to-tumor pancreatic tissues. Several novel dysregulated genes merit further study as potentially promising candidates for the development of more effective treatment strategies for PDAC.

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Identification and Validation of Hub Genes Related to Meniscus Senescence Based on Gene Expression Profiling Analysis

10.21203/rs.3.rs-457294/v1 ◽

2021 ◽

Author(s):

ming chen ◽

Siqi Zhou ◽

Huasong Shi ◽

Hanwen Gu ◽

Yinxian Wen ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profiling ◽

Expression Profiling ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Meniscus Cells ◽

Toxic Drugs ◽

Profiling Analysis

Abstract Background: The incidence of meniscal injury is on the rise, partly due to the general aging of the population. The compositional change in the meniscus with aging would increase the tissue vulnerability of the meniscus, which would induce meniscus tearing. Here, we investigated the molecular mechanism of age-related meniscus degeneration with gene expression profiling analysis.Methods: The GSE45233 dataset, including 6 elderly meniscus samples and 6 younger meniscus samples, which were obtained from patients undergoing arthroscopic partial meniscectomy, was downloaded from the Gene Expression Omnibus (GEO) database for subsequent bioinformatics analysis. To screen the differential expression of mRNAs, identify the miRNAs targeting hub genes, and forecast the potentially toxic drugs, we completed a series of bioinformatics analyses, including functional and pathway enrichment analysis, protein-protein interaction network, hub genes screening, construction of a lncRNA–miRNA–mRNA network, and molecular docking of potential drugs. Furthermore, hub genes were examined in human senescent menisci, mouse senescent meniscus tissues and mouse meniscus cells stimulated by IL-1β.Results: In total, the most significant 4 hub genes (RRM2, AURKB, CDK1, and TIMP1), 5 miRNAs (hsa-miR-6810-5p, hsa-miR-4676-5p, hsa-miR-6877-5p, hsa-miR-8085, and hsa-miR-6133) that could regulate such 4 hub genes and potential toxic drugs (Cladribine, Danusertib, Barasertib, Riviciclib, and Dinaciclib) that may have a targeting effect on these genes, were finally identified. The functional enrichment results showed that hub genes were mainly concentrated in aging and regulation of the cell cycle process. Further pathways enrichment analysis of these miRNA revealed that these miRNAs were involved in the synthesis of glycosaminoglycans. The hub genes were decreased in meniscus cells in vitro and meniscus tissues in vivo, which indicated that hub genes were related to meniscus senescence.Conclusions: In a word, our current study would provide a basis for finding markers of the aging meniscus to a certain extent.

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Quantitative Phosphoproteomic and Physiological Analyses Provide Insights into the Formation of the Variegated Leaf in Catalpa fargesii

International Journal of Molecular Sciences ◽

10.3390/ijms20081895 ◽

2019 ◽

Vol 20 (8) ◽

pp. 1895 ◽

Cited By ~ 3

Author(s):

Nan Wang ◽

Tianqing Zhu ◽

Nan Lu ◽

Zhi Wang ◽

Guijuan Yang ◽

...

Keyword(s):

Enrichment Analysis ◽

Functional Enrichment ◽

Formation Mechanisms ◽

Pathway Enrichment Analysis ◽

Leaf Color ◽

Leaf Variegation ◽

Go Enrichment ◽

Response To Stress ◽

Photosynthesis Regulation

Variegated plants are valuable materials for investigating leaf color regulated mechanisms. To unveil the role of posttranslational modification in the variegated phenotype, we conducted global quantitative phosphoproteomic analysis on different leaf color sectors of Maiyuanjinqiu and the corresponding of Catalpa fargesii using Ti4+-IMAC phosphopeptide enrichment. A total of 3778 phosphorylated sites assigned to 1646 phosphoproteins were identified, and 3221 in 1434 proteins were quantified. Differential phosphoproteins (above 1.5 or below 1/1.5) in various leaf color sectors were selected for functional enrichment analyses. Gene ontology (GO) enrichment revealed that processes of photosynthesis, regulation of the generation of precursor metabolites, response to stress, homeostasis, amino acid metabolism, transport–related processes, and most of the energy metabolisms might contribute to leaf color. KEGG pathway enrichment analysis was performed based on differential phosphoproteins (DPs) in different organelles. The result showed that most enriched pathways were located in the chloroplasts and cytosol. The phosphorylation levels of glycometabolism enzymes might greatly affect leaf variegation. Measurements of fluorescence parameters and enzyme activities confirmed that protein phosphorylation could affect plant physiology by regulating enzyme activity. These results provide new clues for further study the formation mechanisms of naturally variegated phenotype.

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VEGF as a potential molecular target in periodontitis: a meta-analysis and microarray data validation

Journal of Inflammation ◽

10.1186/s12950-021-00281-9 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Bo Ren ◽

Que Feng ◽

Shan He ◽

Yanfeng Li ◽

Jiadong Fan ◽

...

Keyword(s):

Growth Factor ◽

Clinical Sample ◽

Meta Analysis ◽

Enrichment Analysis ◽

Therapeutic Drug ◽

Data Validation ◽

Control Groups ◽

Vegf Expression ◽

Healthy Control

Abstract Background Anti-vascular endothelial growth factor (VEGF) has been used as a therapeutic drug for the treatment of some human diseases. However, no systematic evidence is performed for assessing the role of VEGF in periodontitis. We carried out a comprehensive analysis to explore the role of VEGF in patients with periodontitis. Methods Multiple databases were searched for eligible studies. The pooled standardized mean difference (SMD) and odds ratio (OR) with the corresponding 95% confidence interval (CI) were applied to evaluate the effect sizes. Clinical data validation from microarray analysis was used. Pathway and process enrichment analysis were also investigated. Results Finally, 16 studies were included in this analysis. Overall, there was a significantly higher level of VEGF expression in periodontitis than in healthy control groups (OR = 16.64, 95% CI = 6.01–46.06, P < 0.001; SMD = 2.25, 95% CI = 1.25–3.24, P < 0.001). Subgroup analysis of ethnicity showed that VEGF expression was still correlated with periodontitis in the Asian and European populations. No correlation was observed between VEGF expression and age, gender, and pathological type. A large clinical sample data (427 periodontitis patients and 136 healthy controls) further validated that VEGF expression was higher in periodontitis than in healthy control groups (P = 0.023). VEGF was involved in many functions such as blood vessel development, response to growth factor, cell proliferation, and cell adhesion. Conclusions High levels of VEGF were credible implications for the development of periodontitis. Anti-VEGF therapy may be valuable for the treatment of periodontitis in clinical management.

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AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.1773 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1037.2-1038

Author(s):

X. Sun ◽

S. X. Zhang ◽

S. Song ◽

T. Kong ◽

C. Zheng ◽

...

Keyword(s):

Gene Expression ◽

Signaling Pathways ◽

Differentially Expressed Genes ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Shanxi Province ◽

Receptor Interaction ◽

Term Therapy ◽

Pathway Enrichment Analysis ◽

Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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