515 research outputs found
Identification of androgen response elements in the insulin-like growth factor I upstream promoter
Journal ArticleTestosterone stimulates the expression of IGF-I in cells and tissues that include prostate, muscle and muscle satellite cells, and the uterus. Here, the molecular mechanisms of this effect of testosterone were explored. Testosterone increased IGF-I mRNA levels in HepG2 and LNCaP cells and stimulated the activity of reporter genes controlled by 1.6 kb of the upstream promoter of the human IGF-I gene. An androgen-responsive region that was located between -1320 and -1420 bases upstream of the first codon was identified by truncation studies. The androgen-responsive region was found to contain two sequences resembling known androgen receptor (AR)-binding sites from the Pem1 gene. Reporter genes incorporating these sequences were strongly stimulated by androgens. Each of the androgen-responsive elements (AREs) bound recombinant AR-DNA-binding domain in gel-shift experiments; binding was greatly enhanced by sequences flanking the apparent AR-binding half-sites. Testosterone induced recruitment of AR to sequences of genomic DNA containing these AREs. The two AREs were activated 5-fold more by AR than glucocorticoid receptor. Collectively, these findings indicate the presence of two AREs within the IGF-I upstream promoter that act in cis to activate IGF-I expression. These AREs seem likely to contribute to the up-regulation of the IGF-I gene in prostate tissues, HepG2 cells, and potentially other tissues
Protein phosphatase 5 modulates SMAD3 function in the transforming growth factor-beta pathway
THE EFFECT OF PHYSICAL THERAPY IN THE REHABILITATION OF PATIENTS WITH COMMUNICATION ADAPTATION DISORDER
Fabric-evoked prickle of fabrics made from single fibres using axial fibre-compression-bending analyzer
Fabrics made from cotton, cashmere, flax, hemp, ramie, jute, and wool fibres, have been used to investigate and analyze the prickle comfort properties of fabrics worn as garments. Physical properties include single-fibre critical load, compression and bending modules, which greatly affect the fabric physiological comfort. The fibres are tested using a ‘fibre axial compression-bending analyzer’. The behavior mechanisms of single-needle fibre are also analyzed, evaluated, and explained using fibres critical load, fineness, and protruding length. Physical and neuro-physiological basis for prickle sensation force from single-needle fibre depends on its bending modulus and axial compressive behavior. This experimental work shows that the bending modulus of ramie, jute, and wool fibre is significantly high as compared to other fibres. Thus, high prickle values of ramie, jute and wool fibres make them more uncomfortable due to the cross-section parameters and bending modulus of the single fibre needle. It is observed that the prickle feeling comes from the axial-compressive behavior and the number of effective fibre needles protruding from worn fabric surface. Therefore, prickle sensation aroused during skin–fabric contact is mostly related to the fibre and surface roughness characteristics of fabrics, and the effect of the fabric material on prickle is found to be more
The influence of viscous liquid to the propagation of torsional wave in pipes
This paper deals with the torsional waves propagating in a pipe contacting with viscous liquid. The expression describing the movement of viscous liquid near the pipe is presented. Both the pipe is filled with and immersed in the liquid are considered and both the isotropic and transversely isotropic pipes are investigated. Numerical calculations were carried out to investigate the influence of viscosity of liquid on the dispersion and attenuation curves. The first torsional wave mode is investigated individually by varying the viscosity and the density of the liquid. It is concluded that the viscosity of the liquid has little influence on the dispersion curves, while its main effect is the attenuation. When the frequency and the thickness of the pipe are not large, the attenuation ratio between the two cases of pipe immersed in liquid and pipe filled with liquid is approximately a constant, which is determined by the ratio of inner radius and the thickness
Agent-based Simulation of Online Trading
AbstractIt is evident that sustained cooperation among online traders is absolutely essential for ensuring the success of electronic markets. This research tries to explore the underlying relationship between reputation engineering system and cooperation level by employing ‘Agent Based Simulation Modeling’ approach. It attempts to establish a trust based reputation system and analyze its effect on the sustainability of mutual cooperation between online traders by taking into account key factors such as level of gullibility of online traders and the weight of influence given to their past behavior. The simulation result reveals the correlation between the Smoothing Constant and the Probability of Imitation. The maximum permissible probability of imitation to maintain full cooperation decreases with the increase in the smoothing constant. The mean trader profit decreases as the smoothing constant increases
Robust saliency detection via regularized random walks ranking
In the field of saliency detection, many graph-based algorithms heavily depend on the accuracy of the pre-processed superpixel segmentation, which leads to significant sacrifice of detail information from the input image. In this paper, we propose a novel bottom-up saliency detection approach that takes advantage of both region-based features and image details. To provide more accurate saliency estimations, we first optimize the image boundary selection by the proposed erroneous boundary removal. By taking the image details and region-based estimations into account, we then propose the regularized random walks ranking to formulate pixel-wised saliency maps from the superpixel-based background and foreground saliency estimations. Experiment results on two public datasets indicate the significantly improved accuracy and robustness of the proposed algorithm in comparison with 12 state-of-the-art saliency detection approaches
Prostate segmentation in MR images using ensemble deep convolutional neural networks
The automated segmentation of the prostate gland from MR images is increasingly used for clinical diagnosis. Since deep learning demonstrates superior performance in computer vision applications, we propose a coarse-to-fine segmentation strategy using ensemble deep convolutional neural networks (DCNNs) to address prostate segmentation in MR images. First, we use registration-based coarse segmentation on pre-processed prostate MR images to define the potential boundary region. We then train four DCNNs as voxel-based classifiers and classify the voxel in the potential region is a prostate voxel when at least three DCNNs made that decision. Finally, we use boundary refinement to eliminate the outliers and smooth the boundary. We evaluated our approach on the MICCAI PROMIS12 challenge dataset and our experimental results verify the effectiveness of the proposed algorithms
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