A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesion from five Macaca fasicularis monkeys. The proposed classifier is based on a CNN using filtered segmented EMG signals from the pre- and post-lesion periods as inputs, while the kNN is designed using four hand-crafted EMG features. The results suggest that the CNN provides a promising classification technique for TSCI, compared to conventional machine learning classification. The kNN with hand-crafted EMG features classified the pre- and post-lesion EMG data with an F-measure of 89.7% and 92.7% for the left- and right-side muscles, respectively, while the CNN with the EMG segments classified the data with an F-measure of 89.8% and 96.9% for the left- and right-side muscles, respectively. Finally, the proposed deep learning classification model (CNN), with its learning ability of high-level features using EMG segments as inputs, shows high potential and promising results for use as a TSCI classification system. Future studies can confirm this finding by considering more subjects

Mucosal antibody responses to vaccines targeting SIV protease cleavage sites or full-length Gag and Env proteins in Mauritian cynomolgus macaques.

HIV mutates rapidly and infects CD4+ T cells, especially when they are activated. A vaccine targeting conserved, essential viral elements while limiting CD4+ T cell activation could be effective. Learning from natural immunity observed in a group of highly HIV-1 exposed seronegative Kenyan female sex workers, we are testing a novel candidate HIV vaccine targeting the 12 viral protease cleavage sites (PCSs) (the PCS vaccine), in comparison with a vaccine targeting full-length Gag and Env (the Gag/Env vaccine) in a Mauritian cynomolgus macaque/SIV model. In this study we evaluated these vaccines for induction of mucosal antibodies to SIV immunogens at the female genital tract. Bio-Plex and Western blot analyses of cervicovaginal lavage samples showed that both the PCS and Gag/Env vaccines can elicit mucosal IgG antibody responses to SIV immunogens. Significantly higher increase of anti-PCS antibodies was induced by the PCS vaccine than by the Gag/Env vaccine (p<0.0001). The effect of the mucosal antibody responses in protection from repeated low dose pathogenic SIVmac251 challenges is being evaluated

Decolonising imperial heroes:Britain and France

The heroes of the British and French empires stood at the vanguard of the vibrant cultures of imperialism that emerged in Europe in the second half of the nineteenth century. Yet imperial heroes did not disappear after 1945 as British and French flags were lowered around the world. On the contrary, their reputations underwent a variety of metamorphoses in both the former metropoles and the former colonies. The introduction to this special issue of the Journal of Imperial and Commonwealth History presents an overview of the changing history and historiography of imperial heroes half a century after the end of empire