37 research outputs found

    Aberrantly hydroxymethylated differentially expressed genes and the associated protein pathways in osteoarthritis

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    Background The elderly population is at risk of osteoarthritis (OA), a common, multifactorial, degenerative joint disease. Environmental, genetic, and epigenetic (such as DNA hydroxymethylation) factors may be involved in the etiology, development, and pathogenesis of OA. Here, comprehensive bioinformatic analyses were used to identify aberrantly hydroxymethylated differentially expressed genes and pathways in osteoarthritis to determine the underlying molecular mechanisms of osteoarthritis and susceptibility-related genes for osteoarthritis inheritance. Methods Gene expression microarray data, mRNA expression profile data, and a whole genome 5hmC dataset were obtained from the Gene Expression Omnibus repository. Differentially expressed genes with abnormal hydroxymethylation were identified by MATCH function. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the genes differentially expressed in OA were performed using Metascape and the KOBAS online tool, respectively. The protein–protein interaction network was built using STRING and visualized in Cytoscape, and the modular analysis of the network was performed using the Molecular Complex Detection app. Results In total, 104 hyperhydroxymethylated highly expressed genes and 14 hypohydroxymethylated genes with low expression were identified. Gene ontology analyses indicated that the biological functions of hyperhydroxymethylated highly expressed genes included skeletal system development, ossification, and bone development; KEGG pathway analysis showed enrichment in protein digestion and absorption, extracellular matrix–receptor interaction, and focal adhesion. The top 10 hub genes in the protein–protein interaction network were COL1A1, COL1A2, COL2A1, COL3A1, COL5A1, COL5A2, COL6A1, COL8A1, COL11A1, and COL24A1. All the aforementioned results are consistent with changes observed in OA. Conclusion After comprehensive bioinformatics analysis, we found aberrantly hydroxymethylated differentially expressed genes and pathways in OA. The top 10 hub genes may be useful hydroxymethylation analysis biomarkers to provide more accurate OA diagnoses and target genes for treatment of OA

    Discovery of a novel, liver-targeted thyroid hormone receptor-β agonist, CS271011, in the treatment of lipid metabolism disorders

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    IntroductionThyroid hormone receptor β (THR-β) plays a critical role in metabolism regulation and has become an attractive target for treating lipid metabolism disorders in recent years. Thus, in this study, we discovered CS271011, a novel THR-β agonist, and assessed the safety and efficiency of CS271011 compared to MGL-3196 in vitro and in vivo. MethodsWe conducted luciferase reporter gene assays to assess the activation of THR-β and α in vitro. C57BL/6J mice were fed a high-fat diet for 12 weeks, CS271011 was administered by gavage at the dose of 1 mg/kg and 3 mg/kg, and MGL-3196 was administered at the dose of 3 mg/kg for 10 weeks. Body weight, food intake, serum and hepatic parameters, histological analysis, pharmacokinetic studies, RNA sequencing of the liver and heart, and expression of hepatic lipid-metabolic genes were determined to evaluate the safety and efficiency of CS271011. ResultsCompared with MGL-3196, CS271011 showed higher THR-β activation in vitro. In the diet-induced obesity mice model, CS271011 demonstrated favourable pharmacokinetic properties in mice and was enriched in the liver. Finally, CS271011 improved dyslipidaemia and reduced liver steatosis in the diet-induced obesity murine model. Mechanistically, CS271011 and MGL-3196 showed potent regulation of lipid metabolism-related genes. ConclusionsCS271011 is a potent and liver-targeted THR-β agonist for treating lipid metabolism disorders

    Fusobacterium nucleatum upregulates MMP7 to promote metastasis-related characteristics of colorectal cancer cell via activating MAPK(JNK)-AP1 axis

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    Abstract Background Colorectal cancer (CRC) is the third most common malignant tumor. Fusobacterium nucleatum (F. nucleatum) is overabundant in CRC and associated with metastasis, but the role of F. nucleatum in CRC cell migration and metastasis has not been fully elucidated. Methods Differential gene analysis, protein−protein interaction, robust rank aggregation analysis, functional enrichment analysis, and gene set variation analysis were used to figure out the potential vital genes and biological functions affected by F. nucleatum infection. The 16S rDNA sequencing and q-PCR were used to detect the abundance of F. nucleatum in tissues and stools. Then, we assessed the effect of F. nucleatum on CRC cell migration by wound healing and transwell assays, and confirmed the role of Matrix metalloproteinase 7 (MMP7) induced by F. nucleatum in cell migration. Furthermore, we dissected the mechanisms involved in F. nucleatum induced MMP7 expression. We also investigated the MMP7 expression in clinical samples and its correlation with prognosis in CRC patients. Finally, we screened out potential small molecular drugs that targeted MMP7 using the HERB database and molecular docking. Results F. nucleatum infection altered the gene expression profile and affected immune response, inflammation, biosynthesis, metabolism, adhesion and motility related biological functions in CRC. F. nucleatum was enriched in CRC and promoted the migration of CRC cell by upregulating MMP7 in vitro. MMP7 expression induced by F. nucleatum infection was mediated by the MAPK(JNK)-AP1 axis. MMP7 was highly expressed in CRC and correlated with CMS4 and poor clinical prognosis. Small molecular drugs such as δ-tocotrienol, 3,4-benzopyrene, tea polyphenols, and gallic catechin served as potential targeted therapeutic drugs for F. nucleatum induced MMP7 in CRC. Conclusions Our study showed that F. nucleatum promoted metastasis-related characteristics of CRC cell by upregulating MMP7 via MAPK(JNK)-AP1 axis. F. nucleatum and MMP7 may serve as potential therapeutic targets for repressing CRC advance and metastasis

    Systematic Analysis of Sequences and Expression Patterns of Drought-Responsive Members of the HD-Zip Gene Family in Maize

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    Background: Members of the homeodomain-leucine zipper (HD-Zip) gene family encode transcription factors that are unique to plants and have diverse functions in plant growth and development such as various stress responses, organ formation and vascular development. Although systematic characterization of this family has been carried out in Arabidopsis and rice, little is known about HD-Zip genes in maize (Zea mays L.). Methods and Findings: In this study, we described the identification and structural characterization of HD-Zip genes in the maize genome. A complete set of 55 HD-Zip genes (Zmhdz1-55) were identified in the maize genome using Blast search tools and categorized into four classes (HD-Zip I-IV) based on phylogeny. Chromosomal location of these genes revealed that they are distributed unevenly across all 10 chromosomes. Segmental duplication contributed largely to the expansion of the maize HD-ZIP gene family, while tandem duplication was only responsible for the amplification of the HD-Zip II genes. Furthermore, most of the maize HD-Zip I genes were found to contain an overabundance of stress-related ciselements in their promoter sequences. The expression levels of the 17 HD-Zip I genes under drought stress were also investigated by quantitative real-time PCR (qRT-PCR). All of the 17 maize HD-ZIP I genes were found to be regulated by drought stress, and the duplicated genes within a sister pair exhibited the similar expression patterns, suggesting their conserved functions during the process of evolution

    Targeted Oxidation Strategy (TOS) for Potential Inhibition of Coronaviruses by Disulfiram — a 70-Year Old Anti-Alcoholism Drug

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    In the new millennium, the outbreak of new coronavirus has happened three times: SARS-CoV, MERS-CoV, and 2019-nCoV. Unfortunately, we still have no pharmaceutical weapons against the diseases caused by these viruses. The pandemic of 2019-nCoV reminds us of the urgency to search new drugs with totally different mechanism that may target the weaknesses specific to coronaviruses. Herein, we disclose a new targeted oxidation strategy (TOS II) leveraging non-covalent interactions potentially to oxidize and inhibit the activities of cytosolic thiol proteins via thiol/thiolate oxidation to disulfide (TOD). Quantum mechanical calculations show encouraging results supporting the feasibility to selectively oxidize thiol of targeted proteins via TOS II even in relatively reducing cytosolic microenvironments. Molecular docking against the two thiol proteases Mpro and PLpro of 2019-nCoV provide evidence to support a TOS II mechanism for two experimentally identified anti-2019-nCoV disulfide oxidants: disulfiram and PX-12. Remarkably, disulfiram is an anti-alcoholism drug approved by FDA 70 years ago, thus it can be immediately used in phase III clinical trial for anti-2019-nCoV treatment. Finally, a preliminary list of promising TOS II drug candidates targeting the two thiol proteases of 2019-nCoV are proposed upon virtual screening of 32143 disulfides.</p

    Social network structure is predictive of health and wellness.

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    Social networks influence health-related behavior, such as obesity and smoking. While researchers have studied social networks as a driver for diffusion of influences and behavior, it is less understood how the structure or topology of the network, in itself, impacts an individual's health behavior and wellness state. In this paper, we investigate whether the structure or topology of a social network offers additional insight and predictability on an individual's health and wellness. We develop a method called the Network-Driven health predictor (NetCARE) that leverages features representative of social network structure. Using a large longitudinal data set of students enrolled in the NetHealth study at the University of Notre Dame, we show that the NetCARE method improves the overall prediction performance over the baseline models-that use demographics and physical attributes-by 38%, 65%, 55%, and 54% for the wellness states-stress, happiness, positive attitude, and self-assessed health-considered in this paper
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