Glycosylation in SARS-CoV-2 variants: A path to infection and recovery.

Glycan is an essential molecule that controls and drives life in a precise direction. The paucity of research in glycobiology may impede the significance of its role in the pandemic guidelines. The SARS-CoV-2 spike protein is heavily glycosylated, with 22 putative N-glycosylation sites and 17 potential O-glycosylation sites discovered thus far. It is the anchor point to the host cell ACE2 receptor, TMPRSS2, and many other host proteins that can be recognized by their immune system; hence, glycosylation is considered the primary target of vaccine development. Therefore, it is essential to know how this surface glycan plays a role in viral entry, infection, transmission, antigen, antibody responses, and disease progression. Although the vaccines are developed and applied against COVID-19, the proficiency of the immunizations is not accomplished with the current mutant variations. The role of glycosylation in SARS-CoV-2 and its receptor ACE2 with respect to other putative cell glycan receptors and the significance of glycan in host cell immunity in COVID-19 are discussed in this paper. Hence, the molecular signature of the glycan in the coronavirus infection can be incorporated into the mainstream therapeutic process.

Mathematical Modeling of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Network with Cytokine Storm, Oxidative Stress, Thrombosis, Insulin Resistance, and Nitric Oxide Pathways.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a systemic disease affecting not only the lungs but also multiple organ systems. Clinical studies implicate that SARS-CoV-2 infection causes imbalance of cellular homeostasis and immune response that trigger cytokine storm, oxidative stress, thrombosis, and insulin resistance. Mathematical modeling can offer in-depth understanding of the SARS-CoV-2 infection and illuminate how subcellular mechanisms and feedback loops underpin disease progression and multiorgan failure. We report here a mathematical model of SARS-CoV-2 infection pathway network with cytokine storm, oxidative stress, thrombosis, insulin resistance, and nitric oxide (NO) pathways. The biochemical systems theory model shows autocrine loops with positive feedback enabling excessive immune response, cytokines, transcription factors, and interferons, which can imbalance homeostasis of the system. The simulations suggest that changes in immune response led to uncontrolled release of cytokines and chemokines, including interleukin (IL)-1ß, IL-6, and tumor necrosis factor α (TNFα), and affect insulin, coagulation, and NO signaling pathways. Increased production of NETs (neutrophil extracellular traps), thrombin, PAI-1 (plasminogen activator inhibitor-1), and other procoagulant factors led to thrombosis. By analyzing complex biochemical reactions, this model forecasts the key intermediates, potential biomarkers, and risk factors at different stages of COVID-19. These insights can be useful for drug discovery and development, as well as precision treatment of multiorgan implications of COVID-19 as seen in systems medicine.

What virtual laboratory usage tells us about laboratory skill education pre- and post-COVID-19: Focus on usage, behavior, intention and adoption.

COVID-19 pandemic has brought uncertainty in educational response, skilling methods, and training practices among teachers and institutions. Even before the pandemic shutdowns, the incorporation of virtual laboratories within classroom education had brought transformations in teaching laboratory courses. Virtual laboratories were integrated as training platforms for complementing learning objectives in laboratory education especially during this pandemic imposed shutdown. In context of suspended face-to-face teaching, this study explores the role of virtual laboratories as Massive Open Online Courses (MOOCs) in ensuring the continuity of teaching-learning, providing alternative ways for skill training from home. As an innovative approach, the study presents push-pull mooring theory to analyze switching intention of users from offline conventional education to online education. The study explores the complements of physical experiments brought in with animations, simulations, and remote laboratory set-ups for providing skill trainings to learners. To test whether virtualization techniques have global impact in education sector, the study included a comparative analysis of student users during the academic year 2019 (before-COVID) who had a blended approach of learning and those of the year 2020 (post-COVID), with remote learning. Initial before-COVID behavioral analysis on university students (n = 1059) indicated the substantial popularity of virtual laboratories in education for skill training and instructor dependency. Usage adoption of virtual laboratories increased during the pandemic-imposed lockdowns and learners were being less instructor dependent. 24% of students accessed more 10 times a week without the instructor being present and overall, 90% contributed to a minimum of 5 usages a week. In terms of Kolb's learning styles, most of the virtual laboratory learners were assimilators. The results suggest virtual laboratories may have a prominent role in inquiry based and self-guided education with minimum instructor dependency, which may be crucial for complementing practice skills and planning online tools to add to this post-COVID-19 teaching and learning scenarios.