Transition of Serum Cytokine Concentration in Rickettsia japonica Infection

(1) Background. Rickettsia japonica (R. japonica) infection induces severe inflammation, and the disappearance of eosinophil in the acute stage is one of the phenomena. (2) Materials and Methods. In the current study, we measured the serum concentrations of Th1, Th2, and Th17 cytokines in the acute and recovery stages. (3) Results. In the acute phase, IL-6 and IFN-γ levels were elevated and we speculated that they played a role as a defense mechanism against R. japonica. The high concentration of IFN-γ suppressed the differentiation of eosinophil and induced apoptosis of eosinophil, leading to the disappearance of eosinophil. On day 7, IL-6 and IFN-γ concentrations were decreased, and Th2 cytokines such as IL-5 and IL-9 were slightly increased. On day 14, eosinophil count recovered to the normal level. The transition of serum cytokine concentration in R. japonica infection was presented. (4) Conclusions. IL-6 and IFN-γ seem to be critical cytokines as defense mechanism against R. japonica in the acute phase, and this may deeply connect to the decrease of eosinophil.

A correlation-based network for biomarker discovery in obesity with metabolic syndrome

Background Obesity is associated with chronic activation of the immune system and an altered gut microbiome, leading to increased risk of chronic disease development. As yet, no biomarker profile has been found to distinguish individuals at greater risk of obesity-related disease. The aim of this study was to explore a correlation-based network approach to identify existing patterns of immune-microbiome interactions in obesity. Results The current study performed correlation-based network analysis on five different datasets obtained from 11 obese with metabolic syndrome (MetS) and 12 healthy weight men. These datasets included: anthropometric measures, metabolic measures, immune cell abundance, serum cytokine concentration, and gut microbial composition. The obese with MetS group had a denser network (total number of edges, n = 369) compared to the healthy network (n = 299). Within the obese with MetS network, biomarkers from the immune cell abundance group was found to be correlated to biomarkers from all four other datasets. Conversely in the healthy network, immune cell abundance was only correlated with serum cytokine concentration and gut microbial composition. These observations suggest high involvement of immune cells in obese with MetS individuals. There were also three key hubs found among immune cells in the obese with MetS networks involving regulatory T cells, neutrophil and cytotoxic cell abundance. No hubs were present in the healthy network. Conclusion These results suggest a more complex interaction of inflammatory markers in obesity, with high connectivity of immune cells in the obese with MetS network compared to the healthy network. Three key hubs were identified in the obese with MetS network, involving Treg, neutrophils and cytotoxic cell abundance. Compared to a t-test, the network approach offered more meaningful results when comparing obese with MetS and healthy weight individuals, demonstrating its superiority in exploratory analysis.