EEG-based driver fatigue detection using hybrid deep generic model

© 2016 IEEE. Classification of electroencephalography (EEG)-based application is one of the important process for biomedical engineering. Driver fatigue is a major case of traffic accidents worldwide and considered as a significant problem in recent decades. In this paper, a hybrid deep generic model (DGM)-based support vector machine is proposed for accurate detection of driver fatigue. Traditionally, a probabilistic DGM with deep architecture is quite good at learning invariant features, but it is not always optimal for classification due to its trainable parameters are in the middle layer. Alternatively, Support Vector Machine (SVM) itself is unable to learn complicated invariance, but produces good decision surface when applied to well-behaved features. Consolidating unsupervised high-level feature extraction techniques, DGM and SVM classification makes the integrated framework stronger and enhance mutually in feature extraction and classification. The experimental results showed that the proposed DBN-based driver fatigue monitoring system achieves better testing accuracy of 73.29 % with 91.10 % sensitivity and 55.48 % specificity. In short, the proposed hybrid DGM-based SVM is an effective method for the detection of driver fatigue in EEG

Improving EEG-based driver fatigue classification using sparse-deep belief networks

© 2017 Chai, Ling, San, Naik, Nguyen, Tran, Craig and Nguyen. This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively

Multi-factor service design: identification and consideration of multiple factors of the service in its design process

Service design is a multidisciplinary area that helps innovate services by bringing new ideas to customers through a design-thinking approach. Services are affected by multiple factors, which should be considered in designing services. In this paper, we propose the multi-factor service design (MFSD) method, which helps consider the multi-factor nature of service in the service design process. The MFSD method has been developed through and used in five service design studies with industry and government. The method addresses the multi-factor nature of service for systematic service design by providing the following guidelines: (1) identify key factors that affect the customer value creation of the service in question (in short, value creation factors), (2) define the design space of the service based on the value creation factors, and (3) design services and represent them based on the factors. We provide real stories and examples from the five service design studies to illustrate the MFSD method and demonstrate its utility. This study will contribute to the design of modern complex services that are affected by varied factors

Dbx1-Expressing Cells Are Necessary for the Survival of the Mammalian Anterior Neural and Craniofacial Structures

Development of the vertebrate forebrain and craniofacial structures are intimately linked processes, the coordinated growth of these tissues being required to ensure normal head formation. In this study, we identify five small subsets of progenitors expressing the transcription factor dbx1 in the cephalic region of developing mouse embryos at E8.5. Using genetic tracing we show that dbx1-expressing cells and their progeny have a modest contribution to the forebrain and face tissues. However, their genetic ablation triggers extensive and non cell-autonomous apoptosis as well as a decrease in proliferation in surrounding tissues, resulting in the progressive loss of most of the forebrain and frontonasal structures. Targeted ablation of the different subsets reveals that the very first dbx1-expressing progenitors are critically required for the survival of anterior neural tissues, the production and/or migration of cephalic neural crest cells and, ultimately, forebrain formation. In addition, we find that the other subsets, generated at slightly later stages, each play a specific function during head development and that their coordinated activity is required for accurate craniofacial morphogenesis. Our results demonstrate that dbx1-expressing cells have a unique function during head development, notably by controlling cell survival in a non cell-autonomous manner

TSPYL2 Is Important for G1 Checkpoint Maintenance upon DNA Damage

Nucleosome assembly proteins play important roles in chromatin remodeling, which determines gene expression, cell proliferation and terminal differentiation. Testis specific protein, Y-encoded-like 2 (TSPYL2) is a nucleosome assembly protein expressed in neuronal precursors and mature neurons. Previous studies have shown that TSPYL2 binds cyclin B and inhibits cell proliferation in cultured cells suggesting a role in cell cycle regulation. To investigate the physiological significance of TSPYL2 in the control of cell cycle, we generated mice with targeted disruption of Tspyl2. These mutant mice appear grossly normal, have normal life span and do not exhibit increased tumor incidence. To define the role of TSPYL2 in DNA repair, checkpoint arrest and apoptosis, primary embryonic fibroblasts and thymocytes from Tspyl2 deficient mice were isolated and examined under unperturbed and stressed conditions. We show that mutant fibroblasts are impaired in G1 arrest under the situation of DNA damage induced by gamma irradiation. This is mainly attributed to the defective activation of p21 transcription despite proper p53 protein accumulation, suggesting that TSPYL2 is additionally required for p21 induction. TSPYL2 serves a biological role in maintaining the G1 checkpoint under stress condition

Genome-Wide Analysis Reveals a Complex Pattern of Genomic Imprinting in Mice

Parent-of-origin–dependent gene expression resulting from genomic imprinting plays an important role in modulating complex traits ranging from developmental processes to cognitive abilities and associated disorders. However, while gene-targeting techniques have allowed for the identification of imprinted loci, very little is known about the contribution of imprinting to quantitative variation in complex traits. Most studies, furthermore, assume a simple pattern of imprinting, resulting in either paternal or maternal gene expression; yet, more complex patterns of effects also exist. As a result, the distribution and number of different imprinting patterns across the genome remain largely unexplored. We address these unresolved issues using a genome-wide scan for imprinted quantitative trait loci (iQTL) affecting body weight and growth in mice using a novel three-generation design. We identified ten iQTL that display much more complex and diverse effect patterns than previously assumed, including four loci with effects similar to the callipyge mutation found in sheep. Three loci display a new phenotypic pattern that we refer to as bipolar dominance, where the two heterozygotes are different from each other while the two homozygotes are identical to each other. Our study furthermore detected a paternally expressed iQTL on Chromosome 7 in a region containing a known imprinting cluster with many paternally expressed genes. Surprisingly, the effects of the iQTL were mostly restricted to traits expressed after weaning. Our results imply that the quantitative effects of an imprinted allele at a locus depend both on its parent of origin and the allele it is paired with. Our findings also show that the imprinting pattern of a locus can be variable over ontogenetic time and, in contrast to current views, may often be stronger at later stages in life

MicroRNA-34a is a potent tumor suppressor molecule in vivo in neuroblastoma

<p>ABSTRACT</p> <p>Background</p> <p>Neuroblastoma is a paediatric cancer which originates from precursor cells of the sympathetic nervous system and accounts for 15% of childhood cancer mortalities. With regards to the role of miRNAs in neuroblastoma, miR-34a, mapping to a chromosome 1p36 region that is commonly deleted, has been found to act as a tumor suppressor through targeting of numerous genes associated with cell proliferation and apoptosis.</p> <p>Methods</p> <p>A synthetic miR-34a (or negative control) precursor molecule was transfected into NB1691^lucand SK-N-AS^lucneuroblastoma cells. Quantitative PCR was used to verify increased miR-34a levels in NB1691^lucand SK-N-AS^luccell lines prior to <it>in vitro </it>and <it>in vivo </it>analysis. <it>In vitro </it>analysis of the effects of miR-34a over expression on cell growth, cell cycle and phosphoprotein activation in signal transduction pathways was performed. Neuroblastoma cells over expressing miR-34a were injected retroperitoneally into immunocompromised CB17-SCID mice and tumor burden was assessed over a 21 day period by measuring bioluminescence (photons/sec/cm²).</p> <p>Results</p> <p>Over expression of miR-34a in both NB1691^lucand SK-N-AS^lucneuroblastoma cell lines led to a significant decrease in cell number relative to premiR-negative control treated cells over a 72 hour period. Flow cytometry results indicated that miR-34a induced cell cycle arrest and subsequent apoptosis activation. Phosphoprotein analysis highlighted key elements involved in signal transduction, whose activation was dysregulated as a result of miR-34a introduction into cells. As a potential mechanism of miR-34a action on phosphoprotein levels, we demonstrate that miR-34a over-expression results in a significant reduction of <it>MAP3K9 </it>mRNA and protein levels. Although <it>MAP3K9 </it>is a predicted target of miR-34a, direct targeting could not be validated with luciferase reporter assays. Despite this fact, any functional effects of reduced MAP3K9 expression as a result of miR-34a would be expected to be similar regardless of the mechanism involved. Most notably, <it>in vivo </it>studies showed that tumor growth was significantly repressed after exogenous miR-34a administration in retroperitoneal neuroblastoma tumors.</p> <p>Conclusion</p> <p>We demonstrate for the first time that miR-34a significantly reduces tumor growth in an <it>in vivo </it>orthotopic murine model of neuroblastoma and identified novel effects that miR-34a has on phospho-activation of key proteins involved with apoptosis.</p

Tetanus toxin Hc fragment induces the formation of ceramide platforms and protects neuronal cells against oxidative stress

Tetanus toxin (TeTx) is the protein, synthesized by the anaerobic bacteria Clostridium tetani, which causes tetanus disease. TeTx gains entry into target cells by means of its interaction with lipid rafts, which are membrane domains enriched in sphingomyelin and cholesterol. However, the exact mechanism of host membrane binding remains to be fully established. In the present study we used the recombinant carboxyl terminal fragment from TeTx (Hc-TeTx), the domain responsible for target neuron binding, showing that Hc-TeTx induces a moderate but rapid and sustained increase in the ceramide/sphingomyelin ratio in primary cultures of cerebellar granule neurons and in NGF-differentiated PC12 cells, as well as induces the formation of ceramide platforms in the plasma membrane. The mentioned increase is due to the promotion of neutral sphingomyelinase activity and not to the de novo synthesis, since GW4869, a specific neutral sphingomyelinase inhibitor, prevents neutral sphingomyelinase activity increase and formation of ceramide platforms. Moreover, neutral sphingomyelinase inhibition with GW4869 prevents Hc-TeTx-triggered signaling (Akt phosphorylation), as well as the protective effect of Hc-TeTx on PC12 cells subjected to oxidative stress, while siRNA directed against nSM2 prevents protection by Hc-TeTx of NSC-34 cells against oxidative insult. Finally, neutral sphingomyelinase activity seems not to be related with the internalization of Hc-TeTx into PC12 cells. Thus, the presented data shed light on the mechanisms triggered by TeTx after membrane binding, which could be related with the events leading to the neuroprotective action exerted by the Hc-TeTx fragment