Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis

We genotyped 2,861 cases of primary biliary cirrhosis (PBC) from the UK PBC Consortium and 8,514 UK population controls across 196,524 variants within 186 known autoimmune risk loci. We identified 3 loci newly associated with PBC (at P <5 × 10(-8)), increasing the number of known susceptibility loci to 25. The most associated variant at 19p12 is a low-frequency nonsynonymous SNP in TYK2, further implicating JAK-STAT and cytokine signaling in disease pathogenesis. An additional five loci contained nonsynonymous variants in high linkage disequilibrium (LD; r(2) > 0.8) with the most associated variant at the locus. We found multiple independent common, low-frequency and rare variant association signals at five loci. Of the 26 independent non-human leukocyte antigen (HLA) signals tagged on the Immunochip, 15 have SNPs in B-lymphoblastoid open chromatin regions in high LD (r(2) > 0.8) with the most associated variant. This study shows how data from dense fine-mapping arrays coupled with functional genomic data can be used to identify candidate causal variants for functional follow-up.

Mapping Irreversible Electrochemical Processes on the Nanoscale: Ionic Phenomena in Li Ion Conductive Glass Ceramics

A scanning probe microscopy approach for mapping local irreversible electrochemical processes based on detection of bias-induced frequency shifts of cantilevers in contact with the electrochemically active surface is demonstrated. Using Li ion conductive glass ceramic as a model, we demonstrate near unity transference numbers for ionic transport and establish detection limits for current-based and strain-based detection. The tip-induced electrochemical process is shown to be a first-order transformation and nucleation potential is close to the Li metal reduction potential. Spatial variability of the nucleation bias is explored and linked to the local phase composition. These studies both provide insight into nanoscale ionic phenomena in practical Li-ion electrolyte and also open pathways for probing irreversible electrochemical, bias-induced, and thermal transformations in nanoscale systems.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

A silent witness? Medieval urban landscapes and unfolding their mapping histories

This paper offers a critical reflection on the place of maps in writing medieval urban histories. Using findings from recent research on medieval Swansea, the case is made that mapping provides an interpretative space for exploring alternative narratives about past places. To do so the paper draws upon current critical debates on cartography, particularly the idea that mapping is fluid and iterative, to suggest that Swansea's medieval urban origins are open to a range of alternative interpretations. This approach to mapping differs from that often used by historians to map medieval urban landscapes, where historic maps are simply used as ‘sources’, and the landscapes they represent used as ‘witnesses’ to past events, for creating maps, both through digital and analogue media, instead opens up – or unfolds – a landscape's past. The paper uses past attempts to map medieval Swansea to highlight difficulties in interpreting its urban landscape features, and uses multiple mappings of the medieval townscape, resulting from recent research, to question how far any sources about the past really provide a coherent narrative. Instead, multiple mappings of the medieval urban landscape – reflecting different and competing perspectives – are more attuned with how places were perceived and understood during the Middle Ages.

Sonification as Concurrent Augmented Feedback for Motor Skill Learning and the Importance of Mapping Design

In recent years, sonification of movement has emerged as a viable method for the provision of feedback in motor learning. Despite some experimental validation of its utility, controlled trials to test the usefulness of sonification in a motor learning context are still rare. As such, there are no accepted conventions for dealing with its implementation. This article addresses the question of how continuous movement information should be best presented as sound to be fed back to the learner. It is proposed that to establish effective approaches to using sonification in this context, consideration must be given to the processes that underlie motor learning, in particular the nature of the perceptual information available to the learner for performing the task at hand. Although sonification has much potential in movement performance enhancement, this potential is largely unrealised as of yet, in part due to the lack of a clear framework for sonification mapping: the relationship between movement and sound. By grounding mapping decisions in a firmer understanding of how perceptual information guides learning, and an embodied cognition stance in general, it is hoped that greater advances in use of sonification to enhance motor learning can be achieved.