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广西巴马小型猪动脉粥样硬化模型的制作
引用本文:李艳君,宋少锐,郭亚芬,兰干球,陈宝剑,严雪瑜,吴延军,蒋钦杨.广西巴马小型猪动脉粥样硬化模型的制作[J].中国畜牧兽医,2015,42(7):1770-1776.
作者姓名:李艳君  宋少锐  郭亚芬  兰干球  陈宝剑  严雪瑜  吴延军  蒋钦杨
作者单位:广西大学动物科学技术学院, 南宁 530005
基金项目:广西科技基础条件平台建设(12-97-2)
摘    要:本试验旨在制作广西巴马小型猪动脉粥样硬化模型,初步判断猪发生动脉粥样硬化时的指数值,以期为今后建立相关模型提供依据。试验选取广西巴马小型猪试验组和对照组各10头,通过饲喂高脂高胆固醇饲料建立动脉粥样硬化模型,检测建模过程中血液生化指标,将动脉粥样硬化指数与血管切片作关联分析,初步拟定发生动脉粥样硬化时的指数值。屠宰后血管切片结果显示,试验组有2头广西巴马小型猪发生动脉粥样硬化,对照组均正常。2头广西巴马小型猪的血管切片结果与动脉粥样硬化指数进行关联分析后,初步拟定的动脉粥样硬化指数值在3.8以上,并持续3个月以上。

关 键 词:广西巴马小型猪  动脉粥样硬化模型  动脉粥样硬化指数  
收稿时间:2014-12-18

Preparation of Atherosclerosis Model Using Guangxi Bama Mini-pig
LI Yan-jun,SONG Shao-rui,GUO Ya-fen,LAN Gan-qiu,CHEN Bao-jian,YAN Xue-yu,WU Yan-jun,JIANG Qin-yang.Preparation of Atherosclerosis Model Using Guangxi Bama Mini-pig[J].China Animal Husbandry & Veterinary Medicine,2015,42(7):1770-1776.
Authors:LI Yan-jun  SONG Shao-rui  GUO Ya-fen  LAN Gan-qiu  CHEN Bao-jian  YAN Xue-yu  WU Yan-jun  JIANG Qin-yang
Institution:College of Animal Science and Technology, Guangxi University, Nanning 530005, China
Abstract:The atherosclerosis (AS) model was prepared in Guangxi Bama mini-pig,and the atherosclerosis index (AI) was preliminarily identified in occurrence of AS to provide the basis for the preparation of related models.20 Guangxi Bama mini-pigs were randomly divided into control group and experimental group which were fed with high fat and cholesterol diet to prepare the AS model.Blood biochemical indexes were detected in the process of model preparation and the correlation between AI and the results of vascular slices was analyzed to initially draw up AI of AS.The results of vascular slices showed that the incidence rates of AS of Guangxi Bama mini-pigs in experimental group and control group were 20% and 0,respectively.The association analysis between the results of vascular slices and AI in the pathogenic Guangxi Bama mini-pigs preliminarily suggested that AI was above 3.8 and lasted for more than 3 months during the attack.
Keywords:Guangxi Bama mini-pig  atherosclerosis model  atherosclerosis index  
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