Volume 2 Issue 2

Authors: Cun Liu; Yanling Zheng; Yuanliu He; Hongxia Xu; Juan Su; Xiaohong Zhou; Lili Zhang; Changchun Liu

Abstract: The objective of this paper is to evaluate the value of ultrasound strain and strain rate imaging in evaluating the motorial characteristics of the early stage of the CCA in patients with type 2 diabetes mellitus (DM2). Fifty patients without vascular complications with type 2 diabetes and fifty healthy volunteers underwent carotid ultrasound are selected as objects in the examinationsandthe dynamic image was analyzedby the off-line software (syngo Velocity Vector Imaging technology [VVI], Siemens).The results show that Vmax of anterior wall, anterolateral wall and posterolateral wall were higher than those of posterior wall, posteromedial wall, and anteromedial wall (P<0.05). VTTP, Vmax, Smax, and SRmax of corresponding segments had significant differences in study group and control group (P<0.05). From the results, it could be concluded that Velocity Vector Imaging can be used to evaluate the change of common carotid elasticity in early stage of AS in patients with type 2 diabetes.

Keywords: Ultrasonography; Velocity Vector Imaging; Speckle Tracking; Common Carotid; Atherosclerosis; Diabetes Mellitus


Authors: Subarna Chatterjee; Ajoy Kumar Ray; Rezaul Karim; Arindam Biswas

Abstract: Doppler ultrasound is an important non-invasive diagnostic tool for identifying breast diseases. Ultrasound utilizes spectral Doppler techniques for quantitative evaluation of blood flow velocities, and these measurements play a crucial role in the diagnosis. In this paper, we describe a computer vision approach to automate the Doppler malignancy estimation. We present a technique for segmenting blood vessels in ultrasound color Doppler images based on image processing techniques. The technique decomposes a complex object representing either two or more vessels artificially linked together or a main vessel with its branches. We segment out the blood vessels in ultrasound color Doppler images and count the number of vessels to detect breast malignancy. MATLAB has been used to simulate the algorithm and the results obtained are presented in this paper. The result represents distinct vessels that can be used in further object recognition and quantification applications.

Keywords: Breast Cancer; Color Doppler; Sono-mammography; Ultrasound


Authors: Hirosuke Oku; Hironori Iwasaki; Masashi Inafuku; Takayoshi Toda; Takafumi Okabe; Natthanan Nukitrangsan

Abstract: Aim of the studyis to evaluate the anti-diabetic activity of PJT.This study examined its anti-obesity activity in obese-diabetic animal model of C57BL/6J Ham Slc-ob/obmice.Bydividing animals into control and ethanol extract of PJT groups, body weight gain, tissue weight, biochemical parameters in serum, liver, fecal lipid concentrations and gene expression in the tissues were compared between control and PJT extract groups after been fed with the basal low-fat diet supplemented with or without PJT extract for four weeks.The resultsshow that supplementation of the diet with ethanol extract of PJT significantly reducedwhite adipose tissue (WAT), serum triglyceride (TG), total cholesterol (TC) andadipocyte size. The ethanol extractsalso significantly increase insulin sensitivity, fecalexcretion of TG, TC, and decreased that of bile acid. The ethanol extract of PJT modulated the obesity related genes in liver, adipose tissues of ob/ob mice: upregulationof PBEF1, PPARα, and downregulation of FAS genes in the liver; upregulation of RORC,DGAT1, FXRα, PPARγ genes in the adipose tissue; increased expression of CPT1α,UCP2 and GLUT4 genes in muscle.In conclusion,it issuggested that ethanol extract of PJT exerted anti-diabeticactivitythrough the modulation of obesity-related lipid parameters in obese-diabeticanimal model.

Keywords: Anti-obesity; C57BL/6J Ham Slc-ob/ob Mice; Lipid Metabolism; GeneExpression; Ethanol Extract of Peucedanum japonicum Thunb


Authors: Alexander Trofimov; Anatoly Karpenko; Serge Chernetsov

Abstract: The paper considers the problem of constructing neural network-based blood glucose control system, consisting of connected neural networks of different architectures, NARX neural networks and TDNN. The principle underlying the model training and the results of experimental studies on real patient data are described.

Keywords: Neural Network; Blood Glucose Control System; Type I Diabetes; IDDM; Control System