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      Protective effect of Gastrodia elata Blume in a Caenorhabditis elegans model of Alzheimer's disease based on network pharmacology

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          Abstract

          The aim of the present study was to investigate the protective effect of Gastrodia elata Blume (GEB) against Caenorhabditis elegans ( C. elegans) in Alzheimer's disease (AD) through network pharmacology. Firstly, the active constituents of GEB through ETCM and BATMAN-TCM databases were collected and its potential AD-related targets in Swiss Target Prediction were predicted. The potential targets related to AD were collected from the GeneCards, OMIM, CTD and DisGeNET databases, and the differential genes (DEGs) between the normal population and the AD patient population in GSE5281 chip of the Gene Expression Omnibus database were collected at the same time. The intersection of the three targets yielded 59 key targets of GEB for the treatment of AD. The drug-active ingredient-target-AD network diagram was constructed and visualized with Cytoscape software to obtain the core components. Subsequently, protein-protein interaction analysis (PPI) was performed on 59 key targets through STRING database, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses was performed on 59 key targets. Finally, molecular docking was conducted between core components and core targets using AutoDock software, and the C. elegans AD model was used for experimental verification to explore the regulatory paralysis effect of core components on the C. elegans model, β-amyloid (Aβ) plaque deposition, and quantitative polymerase chain reaction verification of the regulatory effect of components on targets. The GEB components 4,4'-dihydroxydiphenyl methane (DM) and protocatechuic aldehyde (PA) were found to be most strongly associated with AD, and five core targets were identified in the PPI network, including GAPDH, EP300, HSP90AB1, KDM6B, and CREBBP. In addition to GAPDH, the other four targets were successfully docked with DM and PA using AutoDock software. Compared with the control group, 0.5 mM DM and 0.25 mM PA significantly delayed C. elegans paralysis (P<0.01), and inhibited the aggregation of Aβ plaques in C. elegans. Both DM and PA could upregulate the expression level of core target gene HSP90AB1 (P<0.01), and DM upregulated the expression of KDM6B (P<0.01), suggesting that DM and PA may be potential active components of GEB in the treatment of AD.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              limma powers differential expression analyses for RNA-sequencing and microarray studies

              limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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                Author and article information

                Journal
                Biomed Rep
                Biomed Rep
                BR
                Biomedical Reports
                D.A. Spandidos
                2049-9434
                2049-9442
                May 2023
                12 April 2023
                12 April 2023
                : 18
                : 5
                : 37
                Affiliations
                Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, Kunming, Yunnan 650500, P.R. China
                Author notes
                Correspondence to: Dr Xiaohua Duan, Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, 1076 Yuhua Road, Chenggong, Kunming, Yunnan 650500, P.R. China 1047896527qq.com huangzonghai@ 123456outlook.com
                Article
                BR-18-5-01620
                10.3892/br.2023.1620
                10126622
                37113386
                b6138113-027d-4dc5-94a8-521fcd471718
                Copyright: © Shi et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 11 October 2022
                : 29 March 2023
                Funding
                Funding: The present study was supported by the National Natural Science Foundation of China (grant no. 81960733), the Open Project of Yunnan Key Laboratory of Dai and Yi Medicines (grant no. 202210ZD2206), the Xingdian Talent Support Program-Special for Young Talent (2022), the National Administration of Traditional Chinese Medicine High-level Key Discipline Construction Project ‘Dai Medicine’.
                Categories
                Articles

                gastrodia,alzheimer disease,network pharmacology,pharmacological mechanism,caenorhabditis elegans

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