Calorie restriction and endurance exercise share potent anti-inflammatory function in adipose tissues in ameliorating diet-induced obesity and insulin resistance in mice

<p>Abstract</p> <p>Background</p> <p>Calorie restriction (CR) and endurance exercise are known to attenuate obesity and improve the metabolic syndrome. The aim of this study was to directly compare the effects of CR and endurance exercise in a mouse model of diet-induced obesity and insulin resistance.</p> <p>Methods</p> <p>Adult male C57BL/6N mice were randomly assigned and subjected to one of the six interventions for 8 weeks: low-fat diet (LC, 10% fat), low-fat diet with 30% calorie restriction (LR), high-fat diet (HC, 60% fat), high-fat diet with 30% calorie restriction (HR), high-fat diet with voluntary running exercise (HE), and high-fat diet with a combination of 30% calorie restriction and exercise (HRE). The impacts of the interventions were assessed by comprehensive metabolic analyses and pro-inflammatory cytokine gene expression.</p> <p>Results</p> <p>Endurance exercise significantly attenuated high-fat diet-induced obesity. CR dramatically prevented high-fat diet-induced metabolic abnormalities. A combination of CR and endurance exercise further reduced obesity and insulin resistance under the condition of high-fat diet. CR and endurance exercise each potently suppressed the expression of inflammatory cytokines in white adipose tissues with additive effects when combined, but the effects of diet and exercise interventions in the liver were moderate to minimal.</p> <p>Conclusions</p> <p>CR and endurance exercise share a potent anti-inflammatory function in adipose tissues in ameliorating diet-induced obesity and insulin resistance.</p

Transmission effects of foreign exchange reserves on price level: Evidence from China

We investigate the transmission effects of foreign exchange reserves on price level in China by utilizing a nonparametric model. First of all, we employ VAR co-integration analysis to obtain the number of lagged periods in every stage. And then we estimate the elasticity of foreign exchange reserves to money supply and the elasticity of money supply to consumer price index respectively with nonparametric estimations. Finally we use the results from nonparametric estimations to calculate the cross elasticity of foreign exchange reserves to consumer price index. We find that an increase in foreign exchange reserves will lead to an increase in money supply, which in turn will result in an increase in price level. (C) 2012 Elsevier B.V. All rights reserved

Quantitative Ultrasonic Characterization of Metal Matrix Composite Fiber/Matrix Interfacial Failure

The transverse properties of unidirectional titanium matrix composites (TMCs) are dominated by the fiber/matrix interfacial properties, residual stresses and the matrix mechanical response. Nimmer et al. [1] have pioneered the research on the role of the interface when the composites are under transverse loading. In their work, a characteristic “knee” has been observed in the transverse tensile stress-strain curve of a Ti-6A1-4V/SCS-6 composite. This “knee” occurs well below the stress level at which the matrix yields extensively. The comparisons of experimental results with finite element modeling indicate that the “knee” is due to the failure of a weak interface under the transverse loading.</p

ANALYSIS OF DYNAMIC CHARACTERISTICS OF THE HIGH-SPEED GEAR SHAFT SYSTEM

The inherent characteristics of the high speed shaft and the unbalance response of the high speed shaft seriously affect the operating condition and service life of the high speed gearbox. For the high speed gear shaft,a multi distribution model of the system is established. The natural frequency and the unbalance response of the shaft are analyzed by using the transfer matrix method. The unbalance response of the shaft at different speeds and different eccentric quality is obtained with the same method. The unbalance response of the gear meshing point is investigated through the analysis of the unbalanced response characteristics in various cases,and the working conditions of the gear meshing point are analyzed,and the basis for the design and manufacture of high speed gear box is provided

Digital recognition method of methane sensor based on improved CNN-SVM

The methane sensor material has light reflection, and there are attachments on the display panel, which causes the poor quality of the sensor numerical image collected by the automatic verification system of methane sensor, and the difficulty of character recognition. However, the existing instrument character recognition methods based on machine learning have low recognition rate and slow algorithm running speed. In order to solve the above problems, a digital recognition method of methane sensor based on improved convolutional neural network (CNN) and support vector machine (SVM) is proposed. The numerical image of methane sensor is preprocessed by four steps, including image enhancement, numerical region image extraction, image segmentation and decimal point positioning. And the processed digital images are taken as a custom data set. In order to solve the problem of long running time of the CNN-SVM model, PCA algorithm is used to reduce the dimension of the image characteristics extracted from the CNN fully connected layer, and the most important data characteristics are used to replace the original data as the samples of the SVM classifier for classification and recognition. The verification results on the custom dataset show that the improved CNN-SVM model has higher accuracy and shorter running time than the traditional CNN model and CNN-SVM model. The verification results on the classical MNIST dataset show that considering the precision and real-time requirements, the improved CNN-SVM model has better comprehensive performance than CRNN, SSD, YOLOv3 and Faster R-CNN. A micro high-definition USB camera is used to collect the numerical images of methane sensor. The trained improved CNN-SVM model is transplanted to raspberry pi for image processing and recognition. The results show that the recognition success rate of methane sensor digital recognition method based on improved CNN-SVM is 99%, which is consistent with the simulation analysis results

Hardening of pure metals by high pressure torsion: a physically-based model employing volume averaged defect evolutions

A physically based model to predict the increment of hardness and grain refinement of pure metals due to severe plastic deformation by high-pressure torsion (HPT) is proposed. The model incorporates volume-averaged thermally activated dislocation annihilation and grain boundary formation. Strengthening is caused by dislocations in the grain and by grain boundaries. The model is tested against a database containing all available reliable data on HPT-processed pure metals. It is shown that the model accurately predicts hardening and grain size of the pure metals, irrespective of crystal structure (face-centred cubic, body-centred cubic and hexagonal close packed). Measured dislocation densities also show good correlation with predictions. The influence of stacking fault energy on hardening is very weak (of the order of ?0.03 GPa per 100 J mol?1)

Expression profiles of novel genes and microRNAs involved in lipid deposition in chicken’s adipocyte

<p>With the aim of studying the molecular mechanisms underlying lipid deposition in chickens, the expression profiles of eight novel candidate genes and miRNA involved in lipid deposition were examined in the undifferentiated and differentiated adipocyte at 3d, 5d and 10d after inducing differentiation. The level of expression of gga-miR-30 cluster (gga-miR-30a-5p, miR-30c-5p and miR-30e-5p) and miR-17-92 cluster (gga-miR-17-5p, miR-19a-3b and miR-20a-5p), compared to undifferentiated adipocyte, was significantly up-regulated with differentiated adipocyte; expression of miR-103-3p and miR-92-5p was significantly up-regulated with differentiated adipocyte. Seven genes, <i>ACSL1</i>, <i>CYB5A</i>, <i>SEC23A</i>, <i>BRP44L</i>, <i>PLTP</i>, <i>MGLL</i> and <i>GART</i>, compared to undifferentiated adipocyte, were significantly down-regulated with differentiated adipocyte. Correlation analysis of the detected genes and miRNAs indicated <i>BRP44L</i> may be a target of miR-103-3p and it was negatively correlated with miR-103-3p. <i>CYB5A</i> may be a target of miR-30a-5p and it was negatively correlated with miR-30a-5p. <i>SEC23A</i> may be a target of miR-19a-3p and it was negatively correlated with miR-19a-3p. <i>MGLL</i> may be a target of miR-19a-3p and it was negatively correlated with miR-19a-3p. These findings will improve more integrated information of the miRNA and genes in regulating the quantity of lipid deposition in chicken adipocyte.</p