Liver-Resident Memory CD8+ T Cells Form a Front-Line Defense against Malaria Liver-Stage Infection.

In recent years, various intervention strategies have reduced malaria morbidity and mortality, but further improvements probably depend upon development of a broadly protective vaccine. To better understand immune requirement for protection, we examined liver-stage immunity after vaccination with irradiated sporozoites, an effective though logistically difficult vaccine. We identified a population of memory CD8+ T cells that expressed the gene signature of tissue-resident memory T (Trm) cells and remained permanently within the liver, where they patrolled the sinusoids. Exploring the requirements for liver Trm cell induction, we showed that by combining dendritic cell-targeted priming with liver inflammation and antigen recognition on hepatocytes, high frequencies of Trm cells could be induced and these cells were essential for protection against malaria sporozoite challenge. Our study highlights the immune potential of liver Trm cells and provides approaches for their selective transfer, expansion, or depletion, which may be harnessed to control liver infections or autoimmunity.

On an analogue signal processing circuit in the Nematode C. elegans.

In this work we will work on analogue signal processing in the neural circuit of C. elegans which is able to detect the analogue signals from the environment and produce locomotive behaviours which are in accordance with experiments. The signals in C. elegans are processed in a purely analogue procedure, since no action potential has been recorded in its neural activity. We aim to show how signal processing can be executed in analogue domain in a living creature. In order to do that we will model two different behaviours of C. elegans which are generated in the same network of neurons, klinotaxis behaviour and isothermal tracking. We will implement a Genetic Algorithm to find appropriate sets of parameters of the model. Our contribution is to show how relatively straight forward differential equations can lead to relatively complex and different behaviours.

C. elegans locomotion analysis using algorithmic information theory.

This article investigates the use of algorithmic information theory to analyse C. elegans datasets. The ability of complexity measures to detect similarity in animals' behaviours is demonstrated and their strengths are compared to methods such as histograms. Introduced quantities are illustrated on a couple of real two-dimensional C. elegans datasets to investigate the thermotaxis and chemotaxis behaviours.