Mucosal-associated invariant T cells augment immunopathology and gastritis in chronic helicobacter pyloriInfection

Mucosal-associated invariant T (MAIT) cells produce inflammatory cytokines and cytotoxic granzymes in response to by-products of microbial riboflavin synthesis. Although MAIT cells are protective against some pathogens, we reasoned that they might contribute to pathology in chronic bacterial infection. We observed MAIT cells in proximity to Helicobacter pylori bacteria in human gastric tissue, and so, using MR1-tetramers, we examined whether MAIT cells contribute to chronic gastritis in a mouse H. pylori SS1 infection model. Following infection, MAIT cells accumulated to high numbers in the gastric mucosa of wild-type C57BL/6 mice, and this was even more pronounced in MAIT TCR transgenic mice or in C57BL/6 mice where MAIT cells were preprimed by Ag exposure or prior infection. Gastric MAIT cells possessed an effector memory Tc1/Tc17 phenotype, and were associated with accelerated gastritis characterized by augmented recruitment of neutrophils, macrophages, dendritic cells, eosinophils, and non-MAIT T cells and by marked gastric atrophy. Similarly treated MR1−/− mice, which lack MAIT cells, showed significantly less gastric pathology. Thus, we demonstrate the pathogenic potential of MAIT cells in Helicobacter-associated immunopathology, with implications for other chronic bacterial infections

The Transcriptome of Trichuris suis – First Molecular Insights into a Parasite with Curative Properties for Key Immune Diseases of Humans

Iatrogenic infection of humans with Trichuris suis (a parasitic nematode of swine) is being evaluated or promoted as a biological, curative treatment of immune diseases, such as inflammatory bowel disease (IBD) and ulcerative colitis, in humans. Although it is understood that short-term T. suis infection in people with such diseases usually induces a modified Th2-immune response, nothing is known about the molecules in the parasite that induce this response.As a first step toward filling the gaps in our knowledge of the molecular biology of T. suis, we characterised the transcriptome of the adult stage of this nematode employing next-generation sequencing and bioinformatic techniques. A total of ∼65,000,000 reads were generated and assembled into ∼20,000 contiguous sequences ( = contigs); ∼17,000 peptides were predicted and classified based on homology searches, protein motifs and gene ontology and biological pathway mapping.These analyses provided interesting insights into a number of molecular groups, particularly predicted excreted/secreted molecules (n = 1,288), likely to be involved in the parasite-host interactions, and also various molecules (n = 120) linked to chemokine, T-cell receptor and TGF-β signalling as well as leukocyte transendothelial migration and natural killer cell-mediated cytotoxicity, which are likely to be immuno-regulatory or -modulatory in the infected host. This information provides a conceptual framework within which to test the immunobiological basis for the curative effect of T. suis infection in humans against some immune diseases. Importantly, the T. suis transcriptome characterised herein provides a curated resource for detailed studies of the immuno-molecular biology of this parasite, and will underpin future genomic and proteomic explorations

Measuring the Manipulation of T Helper Immune Responses by <i>Schistosoma mansoni</i>

Schistosoma mansoni uses different mechanisms to escape its host’s immunity. Understanding the ability of memory T cells to withstand this pathogen’s manipulation is important for the development of effective vaccines against this immunomodulatory pathogen. In this study, ovalbumin (OVA) transgenic S. mansoni is used as a tool to investigate whether fully differentiated Th1, Th2 and Th17 cells are able to withstand pathogen manipulation. Naïve T cells from OT-II T cell receptor transgenic mice with a specificity for OVA were differentiated into Th1, Th2, and Th17 polarised memory cells in vitro. These cells were adoptively transferred into recipient mice to investigate whether these polarised immune memory T cells are resilient in the face of pathogen-mediated manipulation. After transferring memory cells, mice were challenged with OVA-transduced S. mansoni eggs as well as wild-type controls. The in vitro differentiated Th1, Th2 and Th17 memory cells continued to produce the same cytokines when challenged by OVA-expressing S. mansoni eggs as to these they produced when transferred in vivo, suggesting that the Th phenotypes of the memory T cells remains unaltered in the face of stimulation by S. mansoni. The ability of memory T cells to remain resilient to manipulation by the parasite suggests that vaccines might be able to produce immune memory responses able to withstand S. mansoni immune manipulation and hence protect the host from infection

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm