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Background Epithelial ovarian cancer (EOC) is a female malignant tumor. Bioinformatics has been widely utilized to analyze genes related to cancer progression. Targeted therapy for specific biological factors has become more valuable. Materials and methods Gene expression profiles of GSE18520 and GSE27651 were downloaded from Gene Expression Omnibus. We used the “limma” package to screen differentially expressed genes (DEGs) between EOC and normal ovarian tissue samples and then used Clusterprofiler to do functional and pathway enrichment analyses. We utilized Search Tool for the Retrieval of Interacting Genes Database to assess protein–protein interaction (PPI) information and the plug-in Molecular Complex Detection to screen hub modules of PPI network in Cytoscape, and then performed functional analysis on the genes in the hub module. Next, we utilized the Weighted Gene Expression Network Analysis package to establish a co-expression network. Validation of the key genes in databases and Gene Expression Profiling Interactive Analysis (GEPIA) were completed. Finally, we used quantitative real-time PCR to validate hub gene expression in clinical tissue samples. Results We analyzed the DEGs (96 samples of EOC tissue and 16 samples of normal ovarian tissue) for functional analysis, which showed that upregulated DEGs were strikingly enriched in phosphate ion binding and the downregulated DEGs were significantly enriched in glycosaminoglycan binding. In the PPI network, CDK1 was screened as the most relevant protein. In the co-expression network, one EOC-related module was identified. For survival analysis, database and clinical sample validation of genes in the turquoise module, we found that ITLN1 was positively correlated with EOC prognosis and had lower level in EOC than in normal tissues, which was consistent with the results predicted in GEPIA. Conclusion In this study, we exhibited the key genes and pathways involved in EOC and speculated that ITLN1 was a tumor suppressor which could be used as a potential biomarker for treating EOC, Gene Expression Omnibus, prognosis.

Additional file 1: Fig. S1. Identification of DEGs in EC and normal tissues. (A) The volcano plot of all DEGs. (B) Heatmap of the top 200 DEGs according to the value of |logFC|. Fig. S2. GO analysis and KEGG analysis of the DEGs. (A) In GO analysis, upregulated DEGs with fold change > 1. (B) In GO analysis, down-regulated DEGs with fold change > 1. (C) In KEGG analysis, upregulated DEGs with fold change > 1. (D) In KEGG analysis, down-regulated DEGs with fold change > 1. Fig.S3. GO analysis of the hub module. (A) Module rank 1. (B) Specific information of Module rank 1 (C) Module rank 2. (D) Specific information of Module rank 2. Fig.S4. KEGG analysis of the hub module. (A) Module rank 1. (B) Specific information of Module rank 1 (C) Module rank 2. (D) Specific information of Module rank 2. Fig.S5. Determination of soft-thresholding power in WGCNA. (A) Analysis of the scale-free fit index for various soft-thresholding powers (β). (B) Analysis of the mean connectivity for various soft-thresholding powers. (C) Histogram of connectivity distribution when β = 4. (D) Checking the scale free topology when β = 4. Fig.S6. GO enrichment analysis of 5 hub modules. (A) Green module. (B) Turquoise module. (C) Blue module. (D) Brown module. (E) Yellow module. Fig.S7. KEGG enrichment analysis of 5 hub modules. (A) Green module. (B) Turquoise module. (C) Blue module. (D) Brown module. (E) Yellow module. Fig.S8. Validation of 11 hub genes in TCGA databases. These 11 genes are all highly expressed in EC tissue samples compared with normal tissue samples. Fig.S9. Survival analysis of 11 hub genes. These 11 genes are all negative prognosis factors in EC, while patients with higher expression have significantly shorter overall survival. Fig.S10. Validation of 11 hub genes expression in GEPIA. Higher expression in tumor tissues compared with normal tissues. Fig.S11. Validation of 11 hub genes expression in UALCAN. The expression of 11 hub genes in EC tissues at different stages are all higher than normal tissues. (A) ANLN. (B)ASPM. (C) CDCA8. (D) DLGAP5. (E) FOXM1. (F) HJURP. (G) HMMR. (H) NCAPH. (I) NUF2. (J) RAD54L. (K) RRM2. Fig.S12. Validation of 11 hub genes expression in UALCAN. The expression of 11 hub genes in EC tissues of diffrent histological subtypes are all higher than normal tissues. (A) ANLN. (B)ASPM. (C) CDCA8. (D) DLGAP5. (E) FOXM1. (F) HJURP. (G) HMMR. (H) NCAPH. (I) NUF2. (J) RAD54L. (K) RRM2. Fig.S13. Immunohistochemistry of the five hub genes based on the Human Protein Atlas. (A) Protein levels of ANLN in tumor tissue (staining: High; intensity: Strong; quantity: 75–25%). Protein levels of ANLN in normal tissue (staining: Low; intensity: Moderate; quantity: 75%; Location: Cytoplasmic/membranou). Protein levels of ASPM in normal tissue (staining: Low; intensity: Weak; quantity: 75–25%; Location:Cytoplasmic/membranous). (C) Protein levels of CDCA8 in tumor tissue (staining: High; intensity: Strong; quantity: 75–25%; Location:Nuclear). Protein levels of CDCA8 in normal tissue (staining: Low; intensity: Moderate; quantity: Rare). (D) Protein levels of DLGAP5 in tumor tissue (staining: Medium; intensity: Strong; quantity: 75%; Location: Cytoplasmic/membranous nuclear). Protein levels of FOMX1 in normal tissue (staining: Medium; intensity: Moderate; quantity: > 75%). Fig.S14. Immunohistochemistry of the five hub genes based on the Human Protein Atlas. (A) Protein levels of HJURP in tumor tissue (staining: High; intensity: Moderate; quantity: 75–25%; Location:Cytoplasmic/membran). Protein levels of HJURP in normal tissue (staining: Low; intensity: moderate; quantity: 75%). Protein levels of NCAPH in normal tissue (staining: low; intensity: weak; quantity: 75–25%). (D) Protein levels of RAD54L in tumor tissue (staining: Medium; intensity: Moderate; quantity: > 75%; Location: Nuclear). Protein levels of RAD54L in normal tissue (staining: low; intensity: Moderate; quantity

Dance and music are expressive art forms. Previous behavioural studies have reported that dancers/musicians show a better sensorimotor ability and emotional representation of others. However, the neural mechanism behind this phenomenon is not completely understood. Recently, intensive researches have identified that the insula is highly enrolled in the empathic process. Thus, to expand the knowledge of insular function associated with empathy under the dance/music training background, we mapped the insular network and its associated brain regions in 21 dancers, 20 musicians, and 24 healthy controls using resting-state functional connectivity (FC) analysis. Whole brain voxel-based analysis was performed using seeds from the posterior insula (PI), the ventral anterior insula (vAI), and the dorsal anterior insula (dAI). The training effects of dance and music on insular subnetworks were then evaluated using one-way analysis of variance ANOVA. Increased insular FC with those seeds was found in dancers/musicians, including PI and anterior cingulated cortex (ACC), vAI and middle temporal gyrus (MTG) and middle cingulated cortex (MCC), and dAI and ACC and MTG. In addition, significant associations were found between discrepant insular FC patterns and empathy scores in dancers and musicians. These results indicated that dance/music training might enhance insular subnetwork function, which would facilitate integration of intero/exteroceptive information and result in better affective sensitivity. Those changes might finally facilitate the subjects’ empathic ability.

A parallel-flow exhaust hood is an effective ventilation device to control dust and toxic pollutants and protect the occupational health of workers, whether it is used alone or combined with a uniform air supply hood in a push&ndash, pull ventilation system. Some scholars have studied the outside air flow characteristics of the conventional exhaust hood with non-uniform air speed at the hood face, but the law of velocity variation outside the parallel-flow exhaust hood is not clear at present. Therefore, this paper uses the dimensionless method to study the center-line velocity change regime in a parallel-flow square exhaust hood based on simulation and experimental data. The results show that the dimensionless center-line velocity has a good change law with the characteristic length of exhaust hood in a parallel-flow square exhaust hood, which can eliminate the influence of hood face velocity and the hood size on the velocity change regime, and the experimental data is basically consistent with the calculated data, which shows that the regression equation method is reliable.

Additional file 1. The primers used for real-time PCR. The 3â -UTR of HOXA10 cDNA which contains a putative target region for miR-139-5p (bold stands for the putative target site for miR-139-5p).

In this paper we present a necessary and sufficient condition to guarantee that the extended function of the solution for Poisson equation by zero extension near the boundary of a domain is still the solution of the corresponding extension problem in the extended domain. We prove the results under the frameworks of classical solutions, strong solutions and weak solutions.

In this paper, we study the hydrodynamic limit of a binary mixture of rigid spheres. When Knudsen numbers of two different species are equal and go to zero, we show formally that the hydrodynamic variables satisfy the compressible Euler and Navier-Stokes equations. Like single species gas, we develop Enskog-Chapman theory up to the second order. It turns out that the macro velocities corresponding to the different spheres are equal and the ratio of the temperatures is the mass ratio of the spheres. However, the macro mass densities satisfy independent conservation laws in the case of the compressible flows. Explicit formulas of viscosity, heat conductivity and heat diffusion coefficient are established in term of particle parameters.