Objective. This study is aimed at understanding the molecular mechanisms and exploring potential therapeutic targets for atrial fibrillation (AF) by multiomics analysis. Methods. Transcriptomics and methylation data of AF patients were retrieved from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and differentially methylated sites between AF and normal samples were screened. Then, highly expressed and hypomethylated and lowly expressed and hypermethylated genes were identified for AF. Weighted gene coexpression network analysis (WGCNA) was presented to construct AF-related coexpression networks. 52 AF blood samples were used for whole exome sequence. The mutation was visualized by the maftools package in R. Key genes were validated in AF using independent datasets. Results. DEGs were identified between AF and controls, which were enriched in neutrophil activation and regulation of actin cytoskeleton. RHOA, CCR2, CASP8, and SYNPO2L exhibited abnormal expression and methylation, which have been confirmed to be related to AF. PCDHA family genes had high methylation and low expression in AF. We constructed two AF-related coexpression modules. Single-nucleotide polymorphism (SNP) was the most common mutation type in AF, especially T > C . MUC4 was the most frequent mutation gene, followed by PHLDA1, AHNAK2, and MAML3. There was no statistical difference in expression of AHNAK2 and MAML3, for AF. PHLDA1 and MUC4 were confirmed to be abnormally expressed in AF. Conclusion. Our findings identified DEGs related to DNA methylation and mutation for AF, which may offer possible therapeutic targets and a new insight into the pathogenesis of AF from a multiomics perspective.

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Currently, bolt-support technology is commonly applied throughout the world during mining activities, civil engineering, and hydraulic projects. The theory of a pretensioned and fully bonded bolting system has long been proposed for use as tunnel supports; however, this technology is difficult to implement in coal mining, particularly for roadways that require immediate support. In this study, a modified cement with water-to-cement ratio of 0.25 was used to work in tandem with a traditional resin cartridge to create a pretensioned, fully bonded bolting system. The fast-setting epoxy resin is positioned at the bottom of the borehole for pretension, and the cement is positioned along the rest of the borehole for full-length bonding along the bolt. Based on a series of pullout tests on the proposed bolting system with different pretension forces, this study shows that a pretensioned, fully bonded bolting system is more durable and stable than the end-encapsulated resin bolting system that is currently utilized in most of China’s coal mines. Additionally, an acoustic emission detection test was simultaneously conducted to further describe the inner fracture mechanisms of the bolting system under different pretension forces ranging from 50 to 140 kN, with an increment of 30 kN. The results of this test indicate that a higher pretension force can decrease the damage events in the bolting system. Additionally, the failure form of a pretensioned, fully bonded bolting system is more likely to be dominated by the fracture of the bolt rod in most circumstances. Finally, this combined bolting technology is successfully implemented in a coal mine, and the monitored results confirm that the proposed bolting measure is effective and reliable.

Objective. Multiple genes have been identified to cause dilated cardiomyopathy (DCM). Nevertheless, there is still a lack of comprehensive elucidation of the molecular characteristics for DCM. Herein, we aimed to uncover putative molecular features for DCM by multiomics analysis. Methods. Differentially expressed genes (DEGs) were obtained from different RNA sequencing (RNA-seq) datasets of left ventricle samples from healthy donors and DCM patients. Furthermore, protein-protein interaction (PPI) analysis was then presented. Differentially methylated genes (DMGs) were identified between DCM and control samples. Following integration of DEGs and DMGs, differentially expressed and methylated genes were acquired and their biological functions were analyzed by the clusterProfiler package. Whole exome sequencing of blood samples from 69 DCM patients was constructed in our cohort, which was analyzed the maftools package. The expression of key mutated genes was verified by three independent datasets. Results. 1407 common DEGs were identified for DCM after integration of the two RNA-seq datasets. A PPI network was constructed, composed of 171 up- and 136 downregulated genes. Four hub genes were identified for DCM, including C3 ( degree = 24 ), GNB3 ( degree = 23 ), QSOX1 ( degree = 21 ), and APOB ( degree = 17 ). Moreover, 285 hyper- and 321 hypomethylated genes were screened for DCM. After integration, 20 differentially expressed and methylated genes were identified, which were associated with cell differentiation and protein digestion and absorption. Among single-nucleotide variant (SNV), C>T was the most frequent mutation classification for DCM. MUC4 was the most frequent mutation gene which occupied 71% across 69 samples, followed by PHLDA1, AHNAK2, and MAML3. These mutated genes were confirmed to be differentially expressed between DCM and control samples. Conclusion. Our findings comprehensively analyzed molecular characteristics from the transcriptome, epigenome, and genome perspectives for DCM, which could provide practical implications for DCM.