SARS-CoV-2 Exposed Mesenchymal Stromal Cell from Congenital Pulmonary Airway Malformations: Transcriptomic Analysis and the Expression of Immunomodulatory Genes

Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes

The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in millions of deaths worldwide. The disease presents with various manifestations that can vary in severity and long-term outcomes. Previous efforts have contributed to the development of effective strategies for treatment and prevention by uncovering the mechanism of viral infection. We now know all the direct protein-protein interactions that occur during the lifecycle of SARS-CoV-2 infection, but it is critical to move beyond these known interactions to a comprehensive understanding of the "full interactome" of SARS-CoV-2 infection, which incorporates human microRNAs (miRNAs), additional human protein-coding genes, and exogenous microbes. Potentially, this will help in developing new drugs to treat COVID-19, differentiating the nuances of long COVID, and identifying histopathological signatures in SARS-CoV-2-infected organs. To construct the full interactome, we developed a statistical modeling approach called MLCrosstalk (multiple-layer crosstalk) based on latent Dirichlet allocation. MLCrosstalk integrates data from multiple sources, including microbes, human protein-coding genes, miRNAs, and human protein-protein interactions. It constructs "topics" that group SARS-CoV-2 with genes and microbes based on similar patterns of co-occurrence across patient samples. We use these topics to infer linkages between SARS-CoV-2 and protein-coding genes, miRNAs, and microbes. We then refine these initial linkages using network propagation to contextualize them within a larger framework of network and pathway structures. Using MLCrosstalk, we identified genes in the IL1-processing and VEGFA-VEGFR2 pathways that are linked to SARS-CoV-2. We also found that Rothia mucilaginosa and Prevotella melaninogenica are positively and negatively correlated with SARS-CoV-2 abundance, a finding corroborated by analysis of single-cell sequencing data.

Development of an Active Training Method for Belt Conveyor

The global situation related to the COVID-19 pandemic has forced employers to find an adequate way to conduct training in order to ensure work safety. The underground mining industry is one of the industries which, due to its nature, was not able to switch to remote work. Conducting traditional training risked spreading the virus among workers. For this purpose, it was necessary to start a search for a form of training that would be safe and would not cause additional stress for employees. Research on the development of an active employee training method and testing of the method itself was conducted online. In order to develop a method of active training, one of the most important workstations was selected, which is the operation of the conveyor belt. The training method comprises four training modules. The modules cover questions related to the operation of the conveyor belt, emergencies, its assembly and disassembly, repair and maintenance. The developed issues also take into account questions concerning natural hazards and work safety. The entire training course lasts 10 days. Every day, an employee receives a set of eight questions sent to their email address, which they must answer before starting work. The article describes the methodology and implementation of the training.