A Novel Kinase Inhibitor AX-0085 Inhibits Interferon-γ-Mediated Induction of PD-L1 Expression and Promotes Immune Reaction to Lung Adenocarcinoma Cells

The Tick Saliva Peptide HIDfsin2 TLR4-Dependently Inhibits the Tick-Borne Severe Fever with Thrombocytopenia Syndrome Virus in Mouse Macrophages

Ticks transmit a variety of pathogens to their hosts by feeding on blood. The interactions and struggle between tick pathogens and hosts have evolved bilaterally. The components of tick saliva can directly or indirectly trigger host biological responses in a manner that promotes pathogen transmission; however, host cells continuously develop strategies to combat pathogen infection and transmission. Moreover, it is still unknown how host cells develop their defense strategies against tick-borne viruses during tick sucking. Here, we found that the tick saliva peptide HIDfsin2 enhanced the antiviral innate immunity of mouse macrophages by activating the Toll-like receptor 4 (TLR4) signaling pathway, thereby restricting tick-borne severe fever with thrombocytopenia syndrome virus (SFTSV) replication. HIDfsin2 was identified to interact with lipopolysaccharide (LPS), a ligand of TLR4, and then depolymerize LPS micelles into smaller particles, effectively enhancing the activation of the nuclear factor kappa-B (NF-κB) and type I interferon (IFN-I) signaling pathways, which are downstream of TLR4. Expectedly, TLR4 knockout completely eliminated the promotion effect of HIDfsin2 on NF-κB and type I interferon activation. Moreover, HIDfsin2 enhanced SFTSV replication in TLR4-knockout mouse macrophages, which is consistent with our recent report that HIDfsin2 hijacked p38 mitogen-activated protein kinase (MAPK) to promote the replication of tick-borne SFTSV in A549 and Huh7 cells (human cell lines) with low expression of TLR4. Together, these results provide new insights into the innate immune mechanism of host cells following tick bites. Our study also shows a rare molecular event relating to the mutual antagonism between tick-borne SFTSV and host cells mediated by the tick saliva peptide HIDfsin2 at the tick-host-virus interface.

Automated characterisation of microglia in ageing mice using image processing and supervised machine learning algorithms

The resident macrophages of the central nervous system, microglia, are becoming increasingly implicated as active participants in neuropathology and ageing. Their diverse and changeable morphology is tightly linked with functions they perform, enabling assessment of their activity through image analysis. To better understand the contributions of microglia in health, senescence, and disease, it is necessary to measure morphology with both speed and reliability. A machine learning approach was developed to facilitate automatic classification of images of retinal microglial cells as one of five morphotypes, using a support vector machine (SVM). The area under the receiver operating characteristic curve for this SVM was between 0.99 and 1, indicating strong performance. The densities of the different microglial morphologies were automatically assessed (using the SVM) within wholemount retinal images. Retinas used in the study were sourced from 28 healthy C57/BL6 mice split over three age points (2, 6, and 28-months). The prevalence of 'activated' microglial morphology was significantly higher at 6- and 28-months compared to 2-months (p < .05 and p < .01 respectively), and 'rod' significantly higher at 6-months than 28-months (p < 0.01). The results of the present study propose a robust cell classification SVM, and further evidence of the dynamic role microglia play in ageing.