Toll-like receptor 2 signaling pathway activation contributes to a highly efficient inflammatory response in Japanese encephalitis virus-infected mouse microglial cells by proteomics

TLR9 promotes monocytic myeloid-derived suppressor cell induction during JEV infection

Myeloid-derived suppressor cells (MDSCs) are a group of heterologous populations of immature bone marrow cells consisting of progenitor cells of macrophages, dendritic cells and granulocytes. Recent studies have revealed that the accumulation of MDSCs in the mouse spleen plays a pivotal role in suppressing the immune response following JEV infection. However, the mechanisms by which JEV induces MDSCs are poorly understood. Here, it was found that JEV infection induces mitochondrial damage and the release of mitochondrial DNA (mtDNA), which further leads to the activation of TLR9. TLR9 deficiency decreases the M-MDSCs population and their suppressive function both in vitro and in vivo. Moreover, the increase of MHCⅡ expression on antigen-presenting cells and CD28 expression on T cells in TLR9-/- mice was positively correlated with M-MDSCs reduction. Accordingly, the survival rate of TLR9-/- mice dramatically increased after JEV infection. These findings reveal the connections of mitochondrial damage and TLR9 activation to the induction of M-MDSCs during JEV infection.

From Immunity to Neurogenesis: Toll-like Receptors as Versatile Regulators in the Nervous System

Toll-like receptors (TLRs) are among the main components of the innate immune system. They can detect conserved structures in microorganisms and molecules associated with stress and cellular damage. TLRs are expressed in resident immune cells and both neurons and glial cells of the nervous system. Increasing evidence is emerging on the participation of TLRs not only in the immune response but also in processes of the nervous system, such as neurogenesis and cognition. Below, we present a review of the literature that evaluates the expression and role of TLRs in processes such as neurodevelopment, behavior, cognition, infection, neuroinflammation, and neurodegeneration.

Machine learning reveals neutrophil-to-lymphocyte ratio as a crucial prognostic indicator in severe Japanese encephalitis patients

Japanese encephalitis (JE) is a severe infectious disease affecting the central nervous system (CNS). However, limited risk factors have been identified for predicting poor prognosis (PP) in adults with severe JE. In this study, we analyzed clinical data from thirty-eight severe adult JE patients and compared them to thirty-three patients without organic CNS disease. Machine learning techniques employing branch-and-bound algorithms were used to identify clinical risk factors. Based on clinical outcomes, patients were categorized into two groups: the PP group (mRs ≥ 3) and the good prognosis (GP) group (mRs ≤ 2) at three months post-discharge. We found that the neutrophil-to-lymphocyte ratio (NLR) and the percentage of neutrophilic count (N%) were significantly higher in the PP group compared to the GP group. Conversely, the percentage of lymphocyte count (L%) was significantly lower in the PP group. Additionally, elevated levels of aspartate aminotransferase (AST) and blood glucose were observed in the PP group compared to the GP group. The clinical parameters most strongly correlated with prognosis, as indicated by Pearson correlation coefficient (PCC), were NLR (PCC 0.45) and blood glucose (PCC 0.45). In summary, our findings indicate that increased serum NLR, N%, decreased L%, abnormal glucose metabolism, and liver function impairment are risk factors associated with poor prognosis in severe adult JE patients.