MSdb: An integrated expression atlas of human musculoskeletal system.

The global prevalence and burden of musculoskeletal (MSK) disorders are immense. Advancements in next-generation sequencing (NGS) have generated vast amounts of data, accelerating the research of pathological mechanisms and the development of therapeutic approaches for MSK disorders. However, scattered datasets across various repositories complicate uniform analysis and comparison. Here, we introduce MSdb, a database for visualization and integrated analysis of next-generation sequencing data from human musculoskeletal system, along with manually curated patient phenotype data. MSdb provides various types of analysis, including sample-level browsing of metadata information, gene/miRNA expression, and single-cell RNA-seq dataset. In addition, MSdb also allows integrated analysis for cross-samples and cross-omics analysis, including customized differentially expressed gene/microRNA analysis, microRNA-gene network, scRNA-seq cross-sample/disease integration, and gene regulatory network analysis. Overall, systematic categorizing, standardized processing, and freely accessible knowledge features MSdb a valuable resource for MSK research community.

Anchoring Pt Particles onto Mesoporousized ZnO Holey Cubes for Triethylamine Detection with Multifaceted Superiorities.

Designing sensing materials with integrating unique spatial structures, functional units, and surface activity is vital to achieve high-performance gas sensor toward triethylamine (TEA) detection. Herein, a simple spontaneous dissolution is used with subsequent thermal decomposition strategy to fabricate mesoporousized ZnO holey cubes. The squaric acid is crucial to coordinate Zn2+ to form a cubic shape (ZnO-0) and then tailor the inner part to open a holey cube with simultaneously mesoporousizing the left cubic body (ZnO-72). To enhance the sensing performance, the mesoporous ZnO holey cubes have been functionalized with catalytic Pt nanoparticles, which deliver superior performances including high response, low detection limit, and fast response and recovery time. Notably, the response of Pt/ZnO-72 towards 200 ppm TEA is up to 535, which is much higher than those of 43 and 224 for pristine ZnO-0 and ZnO-72. A synergistic mechanism combining the intrinsic merits of ZnO, its unique mesoporous holey cubic structure, the oxygen vacancies, and the catalytic sensitization effect of Pt has been proposed for the significant enhancement in TEA sensing. Our work provides an effective facile approach to fabricate an advanced micro-nano architecture with manipulating its spatial structure, functional units, and active mesoporous surface for promising TEA gas sensors.

Characteristic genes in THP­1 derived macrophages infected with Mycobacterium tuberculosis H37Rv strain identified by integrating bioinformatics methods.

Mycobacterium tuberculosis (M. tb) is a highly successful pathogen that has co­existed with humans for 1,000's of years. As the cornerstone of the immune system, macrophages are a key part of innate immunity. They ingest and degrade foreign substances including aging cells and microorganisms, coordinate the inflammatory process, and are the first line of defense against M. tb infection. Recent advances in cellular mycobacteriology have indicated that M. tb uses an remarkably complex strategy to disrupt macrophage function, in order to counteract the antimicrobial mechanisms of the innate and adaptive immune responses, thereby achieving immune escape. With the popularity of microarray technology, a variety of public platforms have provided a variety of gene expression data associated with physiological and disease conditions. Meta­analysis can systematically and quantitatively analyze multiple independent data concerning the same disease, greatly improving the statistical significance and credibility of the gene expression data analysis performed. In the present study, 6 microarray expression datasets of human acute monocytic leukemia THP­1 cell line infected by M. tb H37Rv strain were collected from the GEO database. A total of 4 high­quality datasets were identified using meta­analysis methods in R language, and 306 differentially expressed genes with statistical significance were obtained. Then, a protein­protein interaction (PPI) network of these differentially expressed genes was constructed on the Search Tool for the Retrieval of Interacting Genes/Proteins Database online tool and visualized by Cytoscape v. 3.6.1 software. Using CentiScape and MCODE plugin in the Cytoscape software to mine the functional modules associated with M. tb infection process, 32 characteristic genes were identified. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis was performed on the 32 characteristic genes, and it was demonstrated that these genes were primarily associated with the type I interferon (IFN) pathway. In the established model of THP­1­derived macrophages infected by M. tb, the actual differential expression levels of IFN­stimulated gene 15 (ISG15), 2'­5­oligoadenylate synthetase like (OASL), IFN regulatory factor 7 (IRF7) and DExD/H­box helicase 58 (DDX58), the first 4 genes of the 32 characteristic genes, were verified by reverse transcription quantitative polymerase chain reaction. The results were consistent with the results of microarray analysis. The association between ISG15, OASL and IRF7 and TB infection was also verified. Although a number of studies have identified that the type I IFN pathway may assist M. tb to achieve immune escape, the present study used a meta­analysis of microarray data and PPI network analysis to examine some of the novel genes identified in the IFN pathway. The results furthered the understanding of the molecular mechanisms of the TB immune response and provided a novel perspective for future therapeutic goals.

Identification of unique key genes and miRNAs in latent tuberculosis infection by network analysis.

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (M.tb). New cases are now mainly caused by the progression of latent tuberculosis infection (LTBI). Thus, methods to diagnose and treat LTBI are urgently needed to prevent the development of active TB in infected individuals and the subsequent spread of the disease. In this study, a systems biology approach was utilized to obtain numerous microarray data sets for mRNAs and microRNAs (miRNAs) expressed in the peripheral blood mononuclear cells (PBMCs) of TB patients and individuals with LTBI. Within these data sets, we identified the differentially expressed mRNAs and miRNAs and further investigated which differentially expressed genes and miRNAs were uniquely expressed during LTBI. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to analyze the functional annotations and pathway classifications of the identified genes. To further understand the unique miRNA-gene regulatory network of LTBI, we constructed a protein-protein interaction (PPI) network for the targeted genes. The PPI network included 39 genes that were differentially and uniquely expressed in PBMCs of individuals with LTBI, and KEGG pathway enrichment analysis showed that these genes were predominantly involved in the PI3K-Akt signaling pathway, which plays an important role in chronic inflammation. DIANA TOOLs-mirPath analysis revealed that the identified miRNAs in the miRNA-gene regulatory network for LTBI were mainly associated with the Hippo signaling pathway, which functions in the development of inflammation. Quantitative real-time PCR verified the up expression of hsa-miR-212-3p and its predicted target gene -MAPK1 which had low expression and was a major component of the PPI network, and MAPK1 expression was correlated with the clinicopathological characteristics of LTBI by receiver operating characteristic (ROC) curve analysis. Therefore, MAPK1 has potential to be a new investigable marker during LTBI, which merits our further study and solution. The unique aberrant miRNA-gene regulatory network and the related PPI network identified in this study provide insight into the molecular mechanisms of the immune response to LTBI, and thus, may aid in the development of a novel treatment strategy.