Current community transmission and future perspectives on the COVID-19 process

Background/aim: COVID-19 syndrome due to the SARS-CoV-2 virus is a currently challenging situation ongoing worldwide. Since the current pandemic of the SARS-CoV-2 virus is a great concern for everybody in the World, the frequently asked question is how and when the COVID-19 process will be concluded. The aim of this paper is to propose hypotheses in order to answer this essential question. As recently demonstrated, SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the human genome. Our main hypothesis is that the ultimate aim of the SARS-CoV-2 virus is the incorporation to human genome and being an element of the intestinal virobiota. Materials and methods: We propose that the SARS-CoV-2 genomic incorporation to be a part of human virobiota is essentially based on three pathobiological phases which are called as the 'induction', 'consolidation', and 'maintenance phases'. The phase of 'recurrence' complicates any of these three disease phases based on the viral load, exposure time, and more contagious strains and/or mutants. We have performed the 'random walk model' in order to predict the community transmission kinetics of the virus. Results: Chimerism-mediated immunotherapy at the individual and community level with the help of vaccination seems to be the only option for ending the COVID-19 process. After the integration of SARS-CoV-2 virus into the human genome via the induction, consolidation, and maintenance phases as an element of intestinal virobiota, the chimerism would be concluded. The 'viral load', the 'genomic strain of the SARS-CoV-2', and 'host immune reaction against the SARS-CoV-2' are the hallmarks of this long journey. Conclusion: Elucidation of the functional viral dynamics will be helpful for disease management at the individual- and community- based long-term management strategies.

In vitro analysis of the renin-angiotensin system and inflammatory gene transcripts in human bronchial epithelial cells after infection with severe acute respiratory syndrome coronavirus.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recently identified coronavirus family member that triggers a respiratory disease similar to severe acute respiratory syndrome coronavirus (SARS-CoV). SARS-CoV and SARS-CoV-2 are very similar to each other in many respects, such as structure, genetics, and pathobiology. We hypothesized that coronaviruses could affect pulmonary tissues via integration with the critical immune genes after their interaction with renin-angiotensin system (RAS) elements. The aim of the present bioinformatics study was to assess expression changes of the RAS and non-RAS genes, particularly immune response genes, in the lung epithelial cells after infection with SARS-CoV. METHODS: Linear regression, hierarchical clustering, pathway analysis, and network analysis were performed using the E-GEOD-17400 data set. RESULTS: The whole-genome expression data of the lung epithelial cells infected with SARS-CoV for 12, 24, and 48 hours were analyzed, and a total of 15 RAS family and 29 immune genes were found to be highly correlated with the exposure time to the virus in the studied groups. CONCLUSION: RAS genes are important at the initiation of the infections caused by coronavirus family members and may have a strong relationship with the exchange of immune genes in due course following the infection.

The impact of JAK/STAT inhibitor ruxolitinib on the genesis of lymphoproliferative diseases

Background/aim: Ruxolitinib, a JAK/STAT signaling pathway inhibitor targeted drug, has been approved for the controlling of disease symptoms and splenomegaly in patients with myeloproliferative neoplastic diseases. Recently, it has been proposed that ruxolitinib-induced JAK/STAT pathway inhibition in myelofibrosis is associated with an elevated frequency of aggressive B-cell lymphomas. However, the biological basis and significance of this pharmacobiological adverse event is unknown. The aim of this bioinformatics study is to detect any possible confounding effects of ruxolitinib on the genesis of lymphoproliferative disorders. Materials and methods: The gene expression data were retrieved from the E-MTAB-783 Cancer Genome Project database. Gene expression data for all available genes in 26 cell lines belonging to various types of lymphomas were chosen for use in this in silico analysis. Results: We identified genes that were significant in developing resistance to ruxolitinib in lymphoma cell lines. Conclusion: Based on the results of our present study, ruxolitinib may potentially lead to the pathological expression of the transcription factors important in lymphoma genesis, neoplastic commitment on the progenitor lymphoid cells, inhibition of repressor transcriptions protective for lymphoma development, inhibition of apoptosis, promotion of neoplastic proliferation, transcriptional activation, and proliferation of malignant neoplastic B cells.