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https://www.readbyqxmd.com/read/28712031/human-skeletal-muscle-type-1-fibre-distribution-and-response-of-stress-sensing-proteins-along-the-titin-molecule-after-submaximal-exhaustive-exercise
#1
Satu O A Koskinen, Heikki Kyröläinen, Riina Flink, Harri P Selänne, Sheila S Gagnon, Juha P Ahtiainen, Bradley C Nindl, Maarit Lehti
Early responses of stress-sensing proteins, muscle LIM protein (MLP), ankyrin repeat proteins (Ankrd1/CARP and Ankrd2/Arpp) and muscle-specific RING finger proteins (MuRF1 and MuRF2), along the titin molecule were investigated in the present experiment after submaximal exhaustive exercise. Ten healthy men performed continuous drop jumping unilaterally on a sledge apparatus with a submaximal height until complete exhaustion. Five stress-sensing proteins were analysed by mRNA measurements from biopsies obtained immediately and 3 h after the exercise from exercised vastus lateralis muscle while control biopsies were obtained from non-exercised legs before the exercise...
July 15, 2017: Histochemistry and Cell Biology
https://www.readbyqxmd.com/read/28706255/mitsugumin-29-regulates-t-tubule-architecture-in-the-failing-heart
#2
Robert N Correll, Jeffrey M Lynch, Tobias G Schips, Vikram Prasad, Allen J York, Michelle A Sargent, Didier X P Brochet, Jianjie Ma, Jeffery D Molkentin
Transverse tubules (t-tubules) are uniquely-adapted membrane invaginations in cardiac myocytes that facilitate the synchronous release of Ca(2+) from internal stores and subsequent myofilament contraction, although these structures become disorganized and rarefied in heart failure. We previously observed that mitsugumin 29 (Mg29), an important t-tubule organizing protein in skeletal muscle, was induced in the mouse heart for the first time during dilated cardiomyopathy with heart failure. Here we generated cardiac-specific transgenic mice expressing Mg29 to model this observed induction in the failing heart...
July 13, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28693533/classification-complexity-in-myoelectric-pattern-recognition
#3
Niclas Nilsson, Bo Håkansson, Max Ortiz-Catalan
BACKGROUND: Limb prosthetics, exoskeletons, and neurorehabilitation devices can be intuitively controlled using myoelectric pattern recognition (MPR) to decode the subject's intended movement. In conventional MPR, descriptive electromyography (EMG) features representing the intended movement are fed into a classification algorithm. The separability of the different movements in the feature space significantly affects the classification complexity. Classification complexity estimating algorithms (CCEAs) were studied in this work in order to improve feature selection, predict MPR performance, and inform on faulty data acquisition...
July 10, 2017: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/28688489/a-pca-aided-cross-covariance-scheme-for-discriminative-feature-extraction-from-eeg-signals
#4
Roozbeh Zarei, Jing He, Siuly Siuly, Yanchun Zhang
BACKGROUND AND OBJECTIVES: Feature extraction of EEG signals plays a significant role in Brain-computer interface (BCI) as it can significantly affect the performance and the computational time of the system. The main aim of the current work is to introduce an innovative algorithm for acquiring reliable discriminating features from EEG signals to improve classification performances and to reduce the time complexity. METHODS: This study develops a robust feature extraction method combining the principal component analysis (PCA) and the cross-covariance technique (CCOV) for the extraction of discriminatory information from the mental states based on EEG signals in BCI applications...
July 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28665297/respiratory-signal-prediction-based-on-adaptive-boosting-and-multi-layer-perceptron-neural-network
#5
Wenzheng Sun, Mingyan Jiang, Lei Ren, Jun Dang, Tao You, Fang-Fang Yin
To improve the prediction accuracy of respiratory signals using adaptive boosting and multi-layer perceptron neural network (ADMLP-NN) for gated treatment of moving target in radiation therapy. The respiratory signals acquired using a Real-time Position Management (RPM) device from 138 previous 4DCT scans were retrospectively used in this study. The ADMLP-NN was composed of several artificial neural networks (ANNs) which were used as weaker predictors to compose a stronger predictor. The respiratory signal was initially smoothed using a Savitzky-Golay finite impulse response smoothing filter (S-G filter)...
June 30, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28664374/multiple-linear-regression-and-artificial-neural-networks-for-delta-endotoxin-and-protease-yields-modelling-of-bacillus-thuringiensis
#6
Karim Ennouri, Rayda Ben Ayed, Mohamed Ali Triki, Ennio Ottaviani, Maura Mazzarello, Fathi Hertelli, Nabil Zouari
The aim of the present work was to develop a model that supplies accurate predictions of the yields of delta-endotoxins and proteases produced by B. thuringiensis var. kurstaki HD-1. Using available medium ingredients as variables, a mathematical method, based on Plackett-Burman design (PB), was employed to analyze and compare data generated by the Bootstrap method and processed by multiple linear regressions (MLR) and artificial neural networks (ANN) including multilayer perceptron (MLP) and radial basis function (RBF) models...
July 2017: 3 Biotech
https://www.readbyqxmd.com/read/28662115/a-two-step-approach-for-fluidized-bed-granulation-in-pharmaceutical-processing-assessing-different-models-for-design-and-control
#7
Liangshan Ming, Zhe Li, Fei Wu, Ruofei Du, Yi Feng
Various modeling techniques were used to understand fluidized bed granulation using a two-step approach. First, Plackett-Burman design (PBD) was used to identify the high-risk factors. Then, Box-Behnken design (BBD) was used to analyze and optimize those high-risk factors. The relationship between the high-risk input variables (inlet air temperature X1, binder solution rate X3, and binder-to-powder ratio X5) and quality attributes (flowability Y1, temperature Y2, moisture content Y3, aggregation index Y4, and compactability Y5) of the process was investigated using response surface model (RSM), partial least squares method (PLS) and artificial neural network of multilayer perceptron (MLP)...
2017: PloS One
https://www.readbyqxmd.com/read/28635647/virulence-genes-of-s-aureus-from-dairy-cow-mastitis-and-contagiousness-risk
#8
Giada Magro, Stefano Biffani, Giulietta Minozzi, Ralf Ehricht, Stefan Monecke, Mario Luini, Renata Piccinini
Staphylococcus aureus (S. aureus) is a major agent of dairy cow intramammary infections: the different prevalences of mastitis reported might be related to a combination of S. aureus virulence factors beyond host factors. The present study considered 169 isolates from different Italian dairy herds that were classified into four groups based on the prevalence of S. aureus infection at the first testing: low prevalence (LP), medium-low (MLP), medium-high (MHP) and high (HP). We aimed to correlate the presence of virulence genes with the prevalence of intramammary infections in order to develop new strategies for the control of S...
June 21, 2017: Toxins
https://www.readbyqxmd.com/read/28629202/a-novel-extreme-learning-machine-classification-model-for-e-nose-application-based-on-the-multiple-kernel-approach
#9
Yulin Jian, Daoyu Huang, Jia Yan, Kun Lu, Ying Huang, Tailai Wen, Tanyue Zeng, Shijie Zhong, Qilong Xie
A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs)...
June 19, 2017: Sensors
https://www.readbyqxmd.com/read/28617536/effects-of-mulberry-leaf-polysaccharide-on-oxidative-stress-in-pancreatic-%C3%AE-cells-of-type-2-diabetic-rats
#10
C-G Liu, Y-P Ma, X-J Zhang
OBJECTIVE: To explore and discuss the effects and mechanisms of mulberry leaf polysaccharide (MLP) on oxidative stress in pancreatic β-cells of type 2 diabetic rats. MATERIALS AND METHODS: The model of diabetic rats was established by inducing the Sprague-Dawley (SD) rats with high-sugar and high-fat diet for 6 weeks and then giving them streptozotocin (STZ) by single intraperitoneal injection. The mulberry leaf polysaccharide was administered via gavage daily for 8 weeks, and the tissue morphology was observed through electron microscopy...
May 2017: European Review for Medical and Pharmacological Sciences
https://www.readbyqxmd.com/read/28611579/stacked-autoencoders-for-the-p300-component-detection
#11
Lukáš Vařeka, Pavel Mautner
Novel neural network training methods (commonly referred to as deep learning) have emerged in recent years. Using a combination of unsupervised pre-training and subsequent fine-tuning, deep neural networks have become one of the most reliable classification methods. Since deep neural networks are especially powerful for high-dimensional and non-linear feature vectors, electroencephalography (EEG) and event-related potentials (ERPs) are one of the promising applications. Furthermore, to the authors' best knowledge, there are very few papers that study deep neural networks for EEG/ERP data...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28610432/qsar-model-for-prediction-of-the-therapeutic-potency-of-n-benzylpiperidine-derivatives-as-ache-inhibitors
#12
S Bitam, M Hamadache, S Hanini
A new family of AChE inhibitors, N-benzylpiperidines, showed exceptional efficacy in vitro and in vivo, minimal side effects and high selectivity for acetylcholinesterase (AChE). Three regression methods were chosen in this work to develop robust predictive models, namely multiple linear regression (MLR), genetic function approximation (GFA) and multilayer perceptron network (MLP). Ten descriptors were selected for a dataset of 99 molecules, using a genetic algorithm. The best results were obtained for MLP with a 10-6-1 artificial neural network model trained with the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm...
June 14, 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/28535743/acceptability-of-complementary-foods-that-incorporate-moringa-oleifera-leaf-powder-among-infants-and-their-caregivers
#13
Laurene Boateng, Ruth Nyarko, Matilda Asante, Matilda Steiner-Asiedu
BACKGROUND: Moringa Oleifera leaf powder (MLP) is a nutrient-rich and readily available food resource that has the potential to improve the micronutrient quality of complementary foods in developing countries. OBJECTIVE: To investigate the acceptability of complementary foods fortified with MLP. METHODS: Moringa Oleifera leaf powder was fed to infants either as part of a cereal-legume complementary food blend (MCL-35 g) or by sprinkling as a food supplement (MS-5 g) on infant's usual foods...
January 1, 2017: Food and Nutrition Bulletin
https://www.readbyqxmd.com/read/28499398/biomechanical-evaluation-of-a-novel-dualplate-fixation-method-for-proximal-humeral-fractures-without-medial-support
#14
Yu He, Yaoshen Zhang, Yan Wang, Dongsheng Zhou, Fu Wang
BACKGROUND: Comminuted fractures of the proximal humerus are generally treated with the locking plate system, and clinical results are satisfactory. However, unstable support of the medial column results in varus malunion and screw perforation. We designed a novel medial anatomical locking plate (MLP) to directly support the medial column. Theoretically, the combined application of locking plate and MLP (LPMP) would directly provide strong dual-column stability. We hypothesized that the LPMP could provide greater construct stability than the locking plate alone (LP), locking plate combined with a fibular graft (LPSG), and locking plate combined with a distal radius plate (LPDP)...
May 12, 2017: Journal of Orthopaedic Surgery and Research
https://www.readbyqxmd.com/read/28490578/investigating-clinical-issues-by-genotyping-of-medically-important-fungi-why-and-how
#15
REVIEW
Alexandre Alanio, Marie Desnos-Ollivier, Dea Garcia-Hermoso, Stéphane Bretagne
Genotyping studies of medically important fungi have addressed elucidation of outbreaks, nosocomial transmissions, infection routes, and genotype-phenotype correlations, of which secondary resistance has been most intensively investigated. Two methods have emerged because of their high discriminatory power and reproducibility: multilocus sequence typing (MLST) and microsatellite length polymorphism (MLP) using short tandem repeat (STR) markers. MLST relies on single-nucleotide polymorphisms within the coding regions of housekeeping genes...
July 2017: Clinical Microbiology Reviews
https://www.readbyqxmd.com/read/28484935/computational-models-for-the-classification-of-mpges-1-inhibitors-with-fingerprint-descriptors
#16
Zhonghua Xia, Aixia Yan
Human microsomal prostaglandin [Formula: see text] synthase (mPGES)-1 is a promising drug target for inflammation and other diseases with inflammatory symptoms. In this work, we built classification models which were able to classify mPGES-1 inhibitors into two groups: highly active inhibitors and weakly active inhibitors. A dataset of 1910 mPGES-1 inhibitors was separated into a training set and a test set by two methods, by a Kohonen's self-organizing map or by random selection. The molecules were represented by different types of fingerprint descriptors including MACCS keys (MACCS), CDK fingerprints, Estate fingerprints, PubChem fingerprints, substructure fingerprints and 2D atom pairs fingerprint...
May 8, 2017: Molecular Diversity
https://www.readbyqxmd.com/read/28476191/analysis-of-normal-hematopoietic-stem-and-progenitor-cell-contents-in-childhood-acute-leukemia-bone-marrow
#17
Juan Carlos Balandrán, Eduardo Vadillo, David Dozal, Alfonso Reyes-López, Antonio Sandoval-Cabrera, Merle Denisse Laffont-Ortiz, Jessica L Prieto-Chávez, Armando Vilchis-Ordoñez, Henry Quintela-Nuñez Del Prado, Héctor Mayani, Juan Carlos Núñez-Enríquez, Juan Manuel Mejía-Aranguré, Briceida López-Martínez, Elva Jiménez-Hernández, Rosana Pelayo
BACKGROUND AND AIMS: Childhood acute leukemias (AL) are characterized by the excessive production of malignant precursor cells at the expense of effective blood cell development. The dominance of leukemic cells over normal progenitors may result in either direct suppression of functional hematopoiesis or remodeling of microenvironmental niches, contributing to BM failure and AL-associated mortality. We undertook this study to investigate the contents and functional activity of hematopoietic stem/progenitor cells (HSPC) and their relationship to immune cell production and risk status in AL pediatric patients...
November 2016: Archives of Medical Research
https://www.readbyqxmd.com/read/28462208/diagnosis-of-the-ocd-patients-using-drawing-features-of-the-bender-gestalt-shapes
#18
R Boostani, F Asadi, N Mohammadi
BACKGROUND: Since psychological tests such as questionnaire or drawing tests are almost qualitative, their results carry a degree of uncertainty and sometimes subjectivity. The deficiency of all drawing tests is that the assessment is carried out after drawing the objects and lots of information such as pen angle, speed, curvature and pressure are missed through the test. In other words, the psychologists cannot assess their patients while running the tests. One of the famous drawing tests to measure the degree of Obsession Compulsion Disorder (OCD) is the Bender Gestalt, though its reliability is not promising...
March 2017: Journal of Biomedical Physics & Engineering
https://www.readbyqxmd.com/read/28459832/a-shallow-convolutional-neural-network-for-blind-image-sharpness-assessment
#19
Shaode Yu, Shibin Wu, Lei Wang, Fan Jiang, Yaoqin Xie, Leida Li
Blind image quality assessment can be modeled as feature extraction followed by score prediction. It necessitates considerable expertise and efforts to handcraft features for optimal representation of perceptual image quality. This paper addresses blind image sharpness assessment by using a shallow convolutional neural network (CNN). The network takes single feature layer to unearth intrinsic features for image sharpness representation and utilizes multilayer perceptron (MLP) to rate image quality. Different from traditional methods, CNN integrates feature extraction and score prediction into an optimization procedure and retrieves features automatically from raw images...
2017: PloS One
https://www.readbyqxmd.com/read/28459697/early-detection-of-peak-demand-days-of-chronic-respiratory-diseases-emergency-department-visits-using-artificial-neural-networks
#20
Krishan Lal Khatri, Lakshman Tamil
Chronic Respiratory diseases, mainly asthma and Chronic Obstructive Pulmonary Disease (COPD), affect the lives of people by limiting their activities in various aspects. Overcrowding of hospital emergency departments (EDs) due to respiratory diseases in certain weather and environmental pollution conditions results in the degradation of quality of medical care, and even limits its availability. A useful tool for ED managers would be to forecast peak demand days so that they can take steps to improve the availability of medical care...
April 26, 2017: IEEE Journal of Biomedical and Health Informatics
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