Global Transcriptomic Study of Circular-RNA Expression Profile in Osteoclasts Infected by Intracellular Staphylococcus aureus.

Osteomyelitis is difficult to cure, and the rapidly rising morbidity is a thorny problem accompanied by a large number of joint replacement applications. Staphylococcus aureus is the main pathogen of osteomyelitis. Circular RNAs (circRNAs), as emerging noncoding RNAs, play important roles in multiple physiopathological processes which could provide novel insights into osteomyelitis. However, little is known about the roles of circRNAs in the pathogenesis of osteomyelitis. Osteoclasts, considered bone sentinels, are the resident macrophages in bone and may play the immune defense roles in osteomyelitis. It has been reported that S. aureus can survive in osteoclasts, but the function of osteoclast circRNAs in response to intracellular S. aureus infection remains unclear. In this study, we investigated the profile of circRNAs in osteoclasts infected by intracellular S. aureus through high-throughput RNA sequencing. In total, 24 upregulated and 62 downregulated differentially expressed circRNAs were identified and subsequently analyzed to demonstrate their potential functions. On this basis, three circRNAs (chr4:130718154-130728164+, chr8:77409548-77413627-, and chr1:190871592-190899571-) were confirmed as potential novel biomarkers for the diagnosis of osteomyelitis through the murine model of osteomyelitis. Most importantly, we verified that the circRNA chr4:130718154-130728164+ named circPum1 could regulate the host autophagy to affect the intracellular infection of S. aureus through miR-767. In addition, circPum1 could serve as a promising serum biomarker in osteomyelitis patients caused by S. aureus infection. Taken together, this study provided the first global transcriptomic profile analysis of circRNAs in osteoclasts infected by intracellular S. aureus and first proposed a novel perspective for the pathogenesis and immunotherapy of S. aureus-induced osteomyelitis from the term of circRNAs.

Towards Understanding Neurodegenerative Diseases: Insights from Caenorhabditis elegans.

The elevated occurrence of debilitating neurodegenerative disorders, such as amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Machado-Joseph disease (MJD), demands urgent disease-modifying therapeutics. Owing to the evolutionarily conserved molecular signalling pathways with mammalian species and facile genetic manipulation, the nematode Caenorhabditis elegans (C. elegans) emerges as a powerful and manipulative model system for mechanistic insights into neurodegenerative diseases. Herein, we review several representative C. elegans models established for five common neurodegenerative diseases, which closely simulate disease phenotypes specifically in the gain-of-function aspect. We exemplify applications of high-throughput genetic and drug screenings to illustrate the potential of C. elegans to probe novel therapeutic targets. This review highlights the utility of C. elegans as a comprehensive and versatile platform for the dissection of neurodegenerative diseases at the molecular level.

Bacteriophages from human skin infecting coagulase-negative Staphylococcus: diversity, novelty and host resistance.

The human skin microbiome comprises diverse populations that differ temporally between body sites and individuals. The virome is a less studied component of the skin microbiome and the study of bacteriophages is required to increase knowledge of the modulation and stability of bacterial communities. Staphylococcus species are among the most abundant colonisers of skin and are associated with both health and disease yet the bacteriophages infecting the most abundant species on skin are less well studied. Here, we report the isolation and genome sequencing of 40 bacteriophages from human skin swabs that infect coagulase-negative Staphylococcus (CoNS) species, which extends our knowledge of phage diversity. Six genetic clusters of phages were identified with two clusters representing novel phages, one of which we characterise and name Alsa phage. We identified that Alsa phages have a greater ability to infect the species S. hominis that was otherwise infected less than other CoNS species by the isolated phages, indicating an undescribed barrier to phage infection that could be in part due to numerous restriction-modification systems. The extended diversity of Staphylococcus phages here enables further research to define their contribution to skin microbiome research and the mechanisms that limit phage infection.

CSGAN: Modality-Aware Trajectory Generation via Clustering-based Sequence GAN.

Human mobility data is useful for various applications in urban planning, transportation, and public health, but collecting and sharing real-world trajectories can be challenging due to privacy and data quality issues. To address these problems, recent research focuses on generating synthetic trajectories, mainly using generative adversarial networks (GANs) trained by real-world trajectories. In this paper, we hypothesize that by explicitly capturing the modality of transportation (e.g., walking, biking, driving), we can generate not only more diverse and representative trajectories for different modalities but also more realistic trajectories that preserve the geographical density, trajectory, and transition level properties by capturing both cross-modality and modality-specific patterns. Towards this end, we propose a Clustering-based Sequence Generative Adversarial Network (CSGAN) that simultaneously clusters the trajectories based on their modalities and learns the essential properties of real-world trajectories to generate realistic and representative synthetic trajectories. To measure the effectiveness of generated trajectories, in addition to typical density and trajectory level statistics, we define several new metrics for a comprehensive evaluation, including modality distribution and transition probabilities both globally and within each modality. Our extensive experiments with real-world datasets show the superiority of our model in various metrics over state-of-the-art models.

Rotation configuration control of the sp2 bond in the diimidazole-dicarboxylate linker for the isomerism of porous coordination polymers.

Porous isomers constructed from the same building blocks but different topology break the general preferred coordination rule of organic linkers and metal nodes, representing an invaluable opportunity for enriching their pore chemistry. Herein, a new group of porous isomers (termed as NTU-69 and NTU-70) was prepared from a C2v symmetric diimidazole-dicarboxylate ligand and mononuclear Cu ion. The structural differences arise from the different rotation configuration of the sp2 bond in the ligand, leading them to exhibit completely different topologies of unc (NTU-69) and sod (NTU-70) as well as framework rigidness. This rotation configuration of the sp2 bond can be controlled by the different acidity of the synthetic solution and the metal/ligand ratio. Gas adsorption and IAST selectivity show that NTU-70 features high potential for CH4 purification from C2H4, C2H6, C3H6 and CO2 mixtures at room temperature. The insight from this work establishes a new bridge between the ligand design and controlled construction of porous isomers.

Delineation of retroperitoneal metastatic lymph nodes in ovarian cancer with near-infrared fluorescence imaging.

Lymph node metastasis occurs in early-stage and late-stage ovarian cancers. Systematic lymphadenectomy is frequently conducted in an attempt to prevent disease progression. However, this method is associated with multiple complications. Therefore, it is necessary to develop a less invasive and more sensitive method for detecting lymphatic metastasis in ovarian cancer. The aim of the present study was to develop an appropriate fluorescent label for the analysis of lymphatic metastasis in vivo. To this end, epithelial ovarian cancer cells with high potential for lymph node metastasis were labeled using mCherry fluorescence. The cells were then imaged in vitro to determine the expression of mCherry, and in a mouse xenograft model in vivo. The data demonstrated the successful identification of metastatic retroperitoneal lymph nodes by co-localization with lymph nodes labeled by near-infrared fluorescence nanoparticles in vivo. These data provided important insights into the further development of methods for intra-operative identification of lymphatic metastasis and the mechanisms underlying lymphatic metastasis.