Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative.

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection.

Clostridium perfringens phospholipase C induced ROS production and cytotoxicity require PKC, MEK1 and NFκB activation.

Clostridium perfringens phospholipase C (CpPLC), also called α-toxin, is the most toxic extracellular enzyme produced by this bacteria and is essential for virulence in gas gangrene. At lytic concentrations, CpPLC causes membrane disruption, whereas at sublytic concentrations this toxin causes oxidative stress and activates the MEK/ERK pathway, which contributes to its cytotoxic and myotoxic effects. In the present work, the role of PKC, ERK 1/2 and NFκB signalling pathways in ROS generation induced by CpPLC and their contribution to CpPLC-induced cytotoxicity was evaluated. The results demonstrate that CpPLC induces ROS production through PKC, MEK/ERK and NFκB pathways, the latter being activated by the MEK/ERK signalling cascade. Inhibition of either of these signalling pathways prevents CpPLC's cytotoxic effect. In addition, it was demonstrated that NFκB inhibition leads to a significant reduction in the myotoxicity induced by intramuscular injection of CpPLC in mice. Understanding the role of these signalling pathways could lead towards developing rational therapeutic strategies aimed to reduce cell death during a clostridialmyonecrosis.