A multichannel Deep Belief Network for the classification of EEG data

© Springer International Publishing Switzerland 2015. Deep learning, and in particular Deep Belief Network (DBN), has recently witnessed increased attention from researchers as a new classification platform. It has been successfully applied to a number of classification problems, such as image classification, speech recognition and natural language processing. However, deep learning has not been fully explored in electroencephalogram (EEG) classification. We propose in this paper three implementations of DBNs to classify multichannel EEG data based on different channel fusion levels. In order to evaluate the proposed method, we used EEG data that has been recorded to study the modulatory effect of transcranial direct current stimulation. One of the proposed DBNs produced very promising results when compared to three well-established classifiers; which are Support Vec- tor Machine (SVM), Linear Discriminant Analysis (LDA) and Extreme Learning Machine (ELM)

Estimating the Quality of Electroconvulsive Therapy Induced Seizures Using Decision Tree and Fuzzy Inference System Classifiers

© 2018 IEEE. Electroconvulsive therapy (ECT) is an effective and widely used treatment for major depressive disorder, in which a brief electric current is passed through the brain to trigger a brief seizure. This study aims to identify seizure quality rating by utilizing a set of seizure parameters. We used 750 ECT EEG recordings in this experiment. Four seizure related parameters, (time of slowing, regularity, stereotypy and post-ictal suppression) are used as inputs to two classifiers, decision tree and fuzzy inference system (FIS), to predict seizure quality ratings. The two classifiers produced encouraging results with error rate of 0.31 and 0.25 for FIS and decision tree, respectively. The classification results show that the four seizure parameters provide relevant information about the rating of seizure quality. Automatic scoring of seizure quality may be beneficial to clinicians working in this field

Estimating the Quality of Electroconvulsive Therapy Induced Seizures Using Decision Tree and Fuzzy Inference System Classifiers

Electroconvulsive therapy (ECT) is an effective and widely used treatment for major depressive disorder, in which a brief electric current is passed through the brain to trigger a brief seizure. This study aims to identify seizure quality rating by utilizing a set of seizure parameters. We used 750 ECT EEG recordings in this experiment. Four seizure related parameters, (time of slowing, regularity, stereotypy and post-ictal suppression) are used as inputs to two classifiers, decision tree and fuzzy inference system (FIS), to predict seizure quality ratings. The two classifiers produced encouraging results with error rate of 0.31 and 0.25 for FIS and decision tree, respectively. The classification results show that the four seizure parameters provide relevant information about the rating of seizure quality. Automatic scoring of seizure quality may be beneficial to clinicians working in this field

Changes in urinary metabolomic profile during relapsing renal vasculitis

Current biomarkers of renal disease in systemic vasculitis lack predictive value and are insensitive to early damage. To identify novel biomarkers of renal vasculitis flare, we analysed the longitudinal urinary metabolomic profile of a rat model of anti-neutrophil cytoplasmic antibody (ANCA) vasculitis. Wistar-Kyoto (WKY) rats were immunised with human myeloperoxidase (MPO). Urine was obtained at regular intervals for 181 days, after which relapse was induced by re-challenge with MPO. Urinary metabolites were assessed in an unbiased fashion using nuclear magnetic resonance (NMR) spectroscopy, and analysed using partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLS-R). At 56 days post-immunisation, we found that rats with vasculitis had a significantly different urinary metabolite profile than control animals; the observed PLS-DA clusters dissipated between 56 and 181 days, and re-emerged with relapse. The metabolites most altered in rats with active or relapsing vasculitis were trimethylamine N-oxide (TMAO), citrate and 2-oxoglutarate. Myo-inositol was also moderately predictive. The key urine metabolites identified in rats were confirmed in a large cohort of patients using liquid chromatography-mass spectrometry (LC-MS). Hypocitraturia and elevated urinary myo-inositol remained associated with active disease, with the urine myo-inositol:citrate ratio being tightly correlated with active renal vasculitis

Proceedings of the CSE 2017 Annual PGR Symposium (CSE-PGSym17)

Welcome to the Proceedings of the second Annual Postgraduate Research Symposium of the School of Computing, Science and Engineering (CSE-PGSym 2017). After the success of the first symposium, the school is delighted to run its second symposium which is being held in The Old Fire Station on 17th March 2017. The symposium is organised by the Salford Innovation Research Centre (SIRC) to provide a forum for the PGR community in the school to share their research work, engage with their peers and staff and stimulate new ideas. In line with SIRC’s strategy, the symposium aims to bring together researchers from the six groups that make up the centre to engage in multidisciplinary discussions and collaborations. It also aims to contribute to the creation of a collaborative environment within the Research Centre and the Groups and share information and explore new ideas. This is also aligned with the University’s ICZ (Industrial Collaboration Zone) programme for creating cultural, physical and virtual environments for collaboration, innovation and learning

SPARC 2017 retrospect & prospects : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2017 SPARC conference. This year we not only celebrate the work of our PGRs but also the 50th anniversary of Salford as a University, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 130 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to exploit this great opportunity to engage with researchers working in different subject areas to your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

SPARC 2018 Internationalisation and collaboration : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2018 SPARC conference. This year we not only celebrate the work of our PGRs but also the launch of our Doctoral School, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 100 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Leishmania amazonensis Arginase Compartmentalization in the Glycosome Is Important for Parasite Infectivity

In Leishmania, de novo polyamine synthesis is initiated by the cleavage of L-arginine to urea and L-ornithine by the action of arginase (ARG, E.C. 3.5.3.1). Previous studies in L. major and L. mexicana showed that ARG is essential for in vitro growth in the absence of polyamines and needed for full infectivity in animal infections. The ARG protein is normally found within the parasite glycosome, and here we examined whether this localization is required for survival and infectivity. First, the localization of L. amazonensis ARG in the glycosome was confirmed in both the promastigote and amastigote stages. As in other species, arg− L. amazonensis required putrescine for growth and presented an attenuated infectivity. Restoration of a wild type ARG to the arg− mutant restored ARG expression, growth and infectivity. In contrast, restoration of a cytosol-targeted ARG lacking the glycosomal SKL targeting sequence (argΔSKL) restored growth but failed to restore infectivity. Further study showed that the ARGΔSKL protein was found in the cytosol as expected, but at very low levels. Our results indicate that the proper compartmentalization of L. amazonensis arginase in the glycosome is important for enzyme activity and optimal infectivity. Our conjecture is that parasite arginase participates in a complex equilibrium that defines the fate of L-arginine and that its proper subcellular location may be essential for this physiological orchestration

Maternal Malaria Induces a Procoagulant and Antifibrinolytic State That Is Embryotoxic but Responsive to Anticoagulant Therapy

Low birth weight and fetal loss are commonly attributed to malaria in endemic areas, but the cellular and molecular mechanisms that underlie these poor birth outcomes are incompletely understood. Increasing evidence suggests that dysregulated hemostasis is important in malaria pathogenesis, but its role in placental malaria (PM), characterized by intervillous sequestration of Plasmodium falciparum, proinflammatory responses, and excessive fibrin deposition is not known. To address this question, markers of coagulation and fibrinolysis were assessed in placentae from malaria-exposed primigravid women. PM was associated with significantly elevated placental monocyte and proinflammatory marker levels, enhanced perivillous fibrin deposition, and increased markers of activated coagulation and suppressed fibrinolysis in placental plasma. Submicroscopic PM was not proinflammatory but tended to be procoagulant and antifibrinolytic. Birth weight trended downward in association with placental parasitemia and high fibrin score. To directly assess the importance of coagulation in malaria-induced compromise of pregnancy, Plasmodium chabaudi AS-infected pregnant C57BL/6 mice were treated with the anticoagulant, low molecular weight heparin. Treatment rescued pregnancy at midgestation, with substantially decreased rates of active abortion and reduced placental and embryonic hemorrhage and necrosis relative to untreated animals. Together, the results suggest that dysregulated hemostasis may represent a novel therapeutic target in malaria-compromised pregnancies