Is the teaching of skeletal image-interpretation at undergraduate level effective in preparing students for practice?

Poster presentatio

Effects of noise on integration of acoustic and electric hearing within and across ears.

In bimodal listening, cochlear implant (CI) users combine electric hearing (EH) in one ear and acoustic hearing (AH) in the other ear. In electric-acoustic stimulation (EAS), CI users combine EH and AH in the same ear. In quiet, integration of EH and AH has been shown to be better with EAS, but with greater sensitivity to tonotopic mismatch in EH. The goal of the present study was to evaluate how external noise might affect integration of AH and EH within or across ears. Recognition of monosyllabic words was measured for normal-hearing subjects listening to simulations of unimodal (AH or EH alone), EAS, and bimodal listening in quiet and in speech-shaped steady noise (10 dB, 0 dB signal-to-noise ratio). The input/output frequency range for AH was 0.1-0.6 kHz. EH was simulated using an 8-channel noise vocoder. The output frequency range was 1.2-8.0 kHz to simulate a shallow insertion depth. The input frequency range was either matched (1.2-8.0 kHz) or mismatched (0.6-8.0 kHz) to the output frequency range; the mismatched input range maximized the amount of speech information, while the matched input resulted in some speech information loss. In quiet, tonotopic mismatch differently affected EAS and bimodal performance. In noise, EAS and bimodal performance was similarly affected by tonotopic mismatch. The data suggest that tonotopic mismatch may differently affect integration of EH and AH in quiet and in noise

Optimising cervical spine imaging with digital radiography for the trauma patient

This is the author accepted manuscript. The final version is available from the British Institute of Radiology via the DOI in this recor

Spinal cord NR1 serine phosphorylation and NR2B subunit suppression following peripheral inflammation

BACKGROUND: Spinal cord N-methyl-D-aspartate (NMDA) receptors are intimately involved in the development and maintenance of central sensitization. However, the mechanisms mediating the altered function of the NMDA receptors are not well understood. In this study the role of phosphorylation of NR1 splice variants and NR2 subunits was examined following hind paw inflammation in rats. We further examined the level of expression of these proteins following the injury. RESULTS: Lumbar spinal cord NR1 subunits were found to be phosphorylated on serine residues within two hours of the induction of hind paw inflammation with carrageenan. The enhanced NR1 serine phosphorylation reversed within six hours. No phosphorylation on NR1 threonine or tyrosine residues was observed. Likewise, no NR2 subunit phosphorylation was observed on serine, threonine or tyrosine residues. An analysis of NR1 and NR2 protein expression demonstrated no change in the levels of NR1 splice variants or NR2A following the inflammation. However, spinal cord NR2B expression was depressed by the hind paw inflammation. The expression of NR2B remained depressed for more than one week following initiation of the inflammation. CONCLUSION: These data suggest that NR1 serine phosphorylation leads to an initial increase in NMDA receptor activity in the spinal cord following peripheral injury. The suppression of NR2B expression suggests compensation for the enhanced nociceptive activity. These data indicate that spinal cord NMDA receptors are highly dynamic in the development, maintenance and recovery from central sensitization following an injury. Thus, chronic pain therapies targeted to NMDA receptors should be designed for the exact configuration of NMDA receptor subunits and post-translational modifications present during specific stages of the disease

Infection Control: Are We Preparing Our Workforce?

This is the author accepted manuscript. The final version is available from the British Institute of Radiology via the DOI in this recor

Cellular, molecular and functional characterisation of YAC transgenic mouse models of Friedreich Ataxia

Copyright © 2014 Anjomani Virmouni et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This article has been made available through the Brunel Open Access Publishing Fund.Background - Friedreich ataxia (FRDA) is an autosomal recessive neurodegenerative disorder, caused by a GAA repeat expansion mutation within intron 1 of the FXN gene. We have previously established and performed preliminary characterisation of several human FXN yeast artificial chromosome (YAC) transgenic FRDA mouse models containing GAA repeat expansions, Y47R (9 GAA repeats), YG8R (90 and 190 GAA repeats) and YG22R (190 GAA repeats). Methodology/Principal Findings - We now report extended cellular, molecular and functional characterisation of these FXN YAC transgenic mouse models. FXN transgene copy number analysis of the FRDA mice demonstrated that the YG22R and Y47R lines each have a single copy of the FXN transgene while the YG8R line has two copies. Single integration sites of all transgenes were confirmed by fluorescence in situ hybridisation (FISH) analysis of metaphase and interphase chromosomes. We identified significant functional deficits, together with a degree of glucose intolerance and insulin hypersensitivity, in YG8R and YG22R FRDA mice compared to Y47R and wild-type control mice. We also confirmed increased somatic GAA repeat instability in the cerebellum and brain of YG22R and YG8R mice, together with significantly reduced levels of FXN mRNA and protein in the brain and liver of YG8R and YG22R compared to Y47R. Conclusions/Significance - Together these studies provide a detailed characterisation of our GAA repeat expansion-based YAC transgenic FRDA mouse models that will help investigations of FRDA disease mechanisms and therapy.European Union, Ataxia UK and FARA

Rapid, Automated Determination of Reaction Models and Kinetic Parameters

We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and kinetic parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding with minimal user input. An automated flow chemistry platform was employed to initially conduct linear flow-ramp experiments to rapidly map the reaction profile of three processes using transient flow data. Following experimental data acquisition, a computational approach was utilised to discriminate between all possible reaction models as well as identify the correct kinetic parameters for each process. Species that are known to participate in the process (starting materials, intermediates, products) are initially inputted by the user prior to flow ramp experiments, then all possible model candidates are compiled into a model library based on their potential to occur after mass balance assessment. Parallel computational optimisation then evaluates each model by algorithmically altering the kinetic parameters of the model to allow convergence of a simulated kinetic curve to the experimental data provided. Statistical analysis then determines the most likely reaction model based on model simplicity and agreement with experimental data. This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost. The computational approach herein described can be employed using data from any set of experiments and the code is open-source