BAME underrepresentation in UK universities: a view from the humanities

Significant divisions have emerged out of the political turmoil of the past three years or so. Yet, out of this unrest has come an increased attention to the virulent racism and racial injustices that still exist in UK society and overseas. In the UK, a number of reports have facilitated more nuanced and evidence-based discussions on BAME underrepresentation, the achievement gap, and the racism experienced by BAME students and staff in universities. This article will summarise the findings of these reports and reflect on their impact for the humanities

Tunable Transient Decay Times in Nonlinear Systems: Application to Magnetic Precession

The dynamical motion of the magnetization plays a key role in the properties of magnetic materials. If the magnetization is initially away from the equilibrium direction in a magnetic nanoparticle, it will precess at a natural frequency and, with some damping present, will decay to the equilibrium position in a short lifetime. Here we investigate a simple but important situation where a magnetic nanoparticle is driven non-resonantly by an oscillating magnetic field, not at the natural frequency. We find a surprising result that the lifetime of the transient motion is strongly tunable, by factors of over 10,000, by varying the amplitude of the driving field.Comment: EPL Preprin

The properties of human disease mutations at protein interfaces

The assembly of proteins into complexes and their interactions with other biomolecules are often vital for their biological function. While it is known that mutations at protein interfaces have a high potential to be damaging and cause human genetic disease, there has been relatively little consideration for how this varies between different types of interfaces. Here we investigate the properties of human pathogenic and putatively benign missense variants at homomeric (isologous and heterologous), heteromeric, DNA, RNA and other ligand interfaces, and at different regions in proteins with respect to those interfaces. We find that different types of interfaces vary greatly in their propensity to be associated with pathogenic mutations, with homomeric heterologous and DNA interfaces being particularly enriched in disease. We also find that residues that do not directly participate in an interface, but are close in three-dimensional space, show a significant disease enrichment. Finally, we observe that mutations at different types of interfaces tend to have distinct property changes when undergoing amino acid substitutions associated with disease, and that this is linked to substantial variability in their identification by computational variant effect predictors

Interpreting protein variant effects with computational predictors and deep mutational scanning

Computational predictors of genetic variant effect have advanced rapidly in recent years. These programs provide clinical and research laboratories with a rapid and scalable method to assess the likely impacts of novel variants. However, it can be difficult to know to what extent we can trust their results. To benchmark their performance, predictors are often tested against large datasets of known pathogenic and benign variants. These benchmarking data may overlap with the data used to train some supervised predictors, which leads to data re-use or circularity, resulting in inflated performance estimates for those predictors. Furthermore, new predictors are usually found by their authors to be superior to all previous predictors, which suggests some degree of computational bias in their benchmarking. Large-scale functional assays known as deep mutational scans provide one possible solution to this problem, providing independent datasets of variant effect measurements. In this Review, we discuss some of the key advances in predictor methodology, current benchmarking strategies and how data derived from deep mutational scans can be used to overcome the issue of data circularity. We also discuss the ability of such functional assays to directly predict clinical impacts of mutations and how this might affect the future need for variant effect predictors

An attention modulated associative network.

We present an elemental model of associative learning that describes interactions between stimulus elements as a process of competitive normalization. Building on the assumptions laid out in Harris (2006), stimuli are represented as an array of elements that compete for attention according to the strength of their input. Elements form associations among each other according to temporal correlations in their activation but restricted by their connectivity. The model moves beyond its predecessor by specifying excitatory, inhibitory, and attention processes for each element in real time and describing their interaction as a form of suppressive gain control. Attention is formalized in this model as a network of mutually inhibitory units that moderate the activation of stimulus elements by controlling the level to which the elements are suppressed by their own inhibitory processes. The model is applied to a range of complex discriminations and related phenomena that have been taken as evidence for configural-learning processes.Australian Research Council: DP077115

Functional properties of in vitro excitatory cortical neurons derived from human pluripotent stem cells

The in vitro derivation of regionally defined human neuron types from patient‐derived stem cells is now established as a resource to investigate human development and disease. Characterization of such neurons initially focused on the expression of developmentally regulated transcription factors and neural markers, in conjunction with the development of protocols to direct and chart the fate of differentiated neurons. However, crucial to the understanding and exploitation of this technology is to determine the degree to which neurons recapitulate the key functional features exhibited by their native counterparts, essential for determining their usefulness in modelling human physiology and disease in vitro. Here, we review the emerging data concerning functional properties of human pluripotent stem cell‐derived excitatory cortical neurons, in the context of both maturation and regional specificity. [Image: see text

Evidence for multiple processes contributing to the Perruchet effect: Response priming and associative learning.

The Perruchet effect constitutes a robust demonstration that it is possible to dissociate conditioned responding and expectancy in a random partial reinforcement design across a variety of human associative learning paradigms. This dissociation has been interpreted as providing evidence for multiple processes supporting learning, with expectancy driven by cognitive processes that lead to a Gambler's fallacy, and the pattern of conditioned responding (CRs) the result of an associative learning process. An alternative explanation is that the pattern of CRs is the result of exposure to the unconditioned stimulus (US). In three human eyeblink conditioning experiments we examined these competing explanations of the Perruchet effect by employing a differential conditioning design and varying the degree to which the two conditioned stimuli (CS) were discriminable. Across all of these experiments there was evidence for a component of the CRs being strongly influenced by recent reinforcement, in a way that was not demonstrably influenced by manipulations of CS discriminability, which suggests a response priming mechanism contributes to the Perruchet effect. However, the complete pattern of results and an analysis of the results from previously published studies are also consistent with there being an associative contribution to the effect.This research was supported by grant DP1096437 from the Australian Research Council to G. Weidemann, an ESRC Doctoral Training Grant to A. McAndrew and I. P.L. McLaren, and an EPS Study visit grant awarded to A. McAndrew