R21 in Matrix-M adjuvant in UK malaria-naive adult men and non-pregnant women aged 18-45 years: an open-label, partially blinded, phase 1-2a controlled human malaria infection study.

Background: R21 is a novel malaria vaccine, composed of a fusion protein of the malaria circumsporozoite protein and hepatitis B surface antigen. Following favourable safety and immunogenicity in a phase 1 study, we aimed to assess the efficacy of R21 administered with Matrix-M (R21/MM) against clinical malaria in adults from the UK who were malaria naive in a controlled human malaria infection study.

Methods: In this open-label, partially blinded, phase 1-2A controlled human malaria infection study undertaken in Oxford, Southampton, and London, UK, we tested five novel vaccination regimens of R21/MM.

Label-free, non-contact determination of resting membrane potential using dielectrophoresis.

Measurement of cellular resting membrane potential (RMP) is important in understanding ion channels and their role in regulation of cell function across a wide range of cell types. However, methods available for the measurement of RMP (including patch clamp, microelectrodes, and potential-sensitive fluorophores) are expensive, slow, open to operator bias, and often result in cell destruction. We present non-contact, label-free membrane potential estimation which uses dielectrophoresis to determine the cytoplasm conductivity slope as a function of medium conductivity.

Absence of differential protection from extinction in human causal learning.

Elemental models of associative learning typically employ a common prediction-error term. Following a conditioning trial, they predict that the change in the strength of an association between a cue and an outcome is dependent upon how well the outcome was predicted. When multiple cues are present, they each contribute to that prediction.

Continuous flow synthesis enabling reaction discovery.

This article defines the role that continuous flow chemistry can have in new reaction discovery, thereby creating molecular assembly opportunities beyond our current capabilities. Most notably the focus is based upon photochemical, electrochemical and temperature sensitive processes where continuous flow methods and machine assisted processing can have significant impact on chemical reactivity patterns. These flow chemical platforms are ideally placed to exploit future innovation in data acquisition, feed-back and control through artificial intelligence (AI) and machine learning (ML) techniques.