Genetic Drift Analysis of Recombination

体外研究人脐带血间充质干细胞诱导大鼠枯否细胞M2极化的
开题报告
一、研究背景和意义
枯否细胞（M1）是机体对病原微生物和受损组织的免疫反应产生的效应细胞，有调节免疫应答作用。

但是过度M1极化会产生过度炎症反应，引起组织损伤。

M2极化是枯否细胞分化的另外一个方向，能够缓解炎症反应，所以M2调节因子的应用有望治疗众多炎症性疾病。

目前，体外研究证明了间充质干细胞（MSCs），即包括人脐带血间充质干细胞（UCMSCs）在内的MSCs，可以通过调节免疫反应来治疗多种疾病，包括炎症性疾病。

同时，UCMSCs 自身也具有M2极化的能力。

因此，本研究将重点研究UCMSCs对大鼠枯否细胞M2极化的作用。

二、研究内容和方法
本研究将采用体外实验，主要研究UCMSCs诱导大鼠枯否细胞M2极化的作用，并探讨其机制。

具体步骤如下：
1. 体外培养大鼠枯否细胞
2. 将UCMSCs和大鼠枯否细胞以不同的比例和时间共同培养
3. 分别检测UCMSCs和大鼠枯否细胞的表达谱，以及免疫学特征
4. 检测UCMSCs对大鼠枯否细胞M2极化的影响，并进一步研究其机制
5. 对比加入其他细胞因子对UCMSCs M2极化的影响
三、预期结果和意义
预计本实验可以探究UCMSCs对大鼠枯否细胞M2极化的作用，为今后更好的诊断和治疗炎症性疾病提供新思路。

此外，本研究能够加深对MSCs的免疫学特征、细胞因子激活和分子机制的认识，为深入研究MSCs的临床应用和产品开发提供理论基础。

Agricultural Sciences in China2010, 9(9): 1251-1262September 2010Received 30 October, 2009 Accepted 16 April, 2010Analysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of ChinaLIU Zhi-zhai 1, 2, GUO Rong-hua 2, 3, ZHAO Jiu-ran 4, CAI Yi-lin 1, W ANG Feng-ge 4, CAO Mo-ju 3, W ANG Rong-huan 2, 4, SHI Yun-su 2, SONG Yan-chun 2, WANG Tian-yu 2 and LI Y u 21Maize Research Institute, Southwest University, Chongqing 400716, P.R.China2Institue of Crop Sciences/National Key Facility for Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences,Beijing 100081, P.R.China3Maize Research Institute, Sichuan Agricultural University, Ya’an 625014, P.R.China4Maize Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100089, P.R.ChinaAbstractUnderstanding genetic diversity and population structure of landraces is important in utilization of these germplasm in breeding programs. In the present study, a total of 143 core maize landraces from the South Maize Region (SR) of China,which can represent the general profile of the genetic diversity in the landraces germplasm of SR, were genotyped by 54DNA microsatellite markers. Totally, 517 alleles (ranging from 4 to 22) were detected among these landraces, with an average of 9.57 alleles per locus. The total gene diversity of these core landraces was 0.61, suggesting a rather higher level of genetic diversity. Analysis of population structure based on Bayesian method obtained the samilar result as the phylogeny neighbor-joining (NJ) method. The results indicated that the whole set of 143 core landraces could be clustered into two distinct groups. All landraces from Guangdong, Hainan, and 15 landraces from Jiangxi were clustered into group 1, while those from the other regions of SR formed the group 2. The results from the analysis of genetic diversity showed that both of groups possessed a similar gene diversity, but group 1 possessed relatively lower mean alleles per locus (6.63) and distinct alleles (91) than group 2 (7.94 and 110, respectively). The relatively high richness of total alleles and distinct alleles preserved in the core landraces from SR suggested that all these germplasm could be useful resources in germplasm enhancement and maize breeding in China.Key words :maize, core landraces, genetic diversity, population structureINTRODUCTIONMaize has been grown in China for nearly 500 years since its first introduction into this second biggest pro-duction country in the world. Currently, there are six different maize growing regions throughout the coun-try according to the ecological conditions and farming systems, including three major production regions,i.e., the North Spring Maize Region, the Huang-Huai-Hai Summer Maize Region, and the Southwest MaizeRegion, and three minor regions, i.e., the South Maize Region, the Northwest Maize Region, and the Qingzang Plateau Maize Region. The South Maize Region (SR)is specific because of its importance in origin of Chi-nese maize. It is hypothesized that Chinese maize is introduced mainly from two routes. One is called the land way in which maize was first brought to Tibet from India, then to Sichuan Province in southwestern China. The other way is that maize dispersed via the oceans, first shipped to the coastal areas of southeast China by boats, and then spread all round the country1252LIU Zhi-zhai et al.(Xu 2001; Zhou 2000). SR contains all of the coastal provinces and regions lie in southeastern China.In the long-term cultivation history of maize in south-ern China, numerous landraces have been formed, in which a great amount of genetic variation was observed (Li 1998). Similar to the hybrid swapping in Europe (Reif et al. 2005a), the maize landraces have been al-most replaced by hybrids since the 1950s in China (Li 1998). However, some landraces with good adapta-tions and yield performances are still grown in a few mountainous areas of this region (Liu et al.1999). Through a great effort of collection since the 1950s, 13521 accessions of maize landraces have been cur-rently preserved in China National Genebank (CNG), and a core collection of these landraces was established (Li et al. 2004). In this core collection, a total of 143 maize landrace accessions were collected from the South Maize Region (SR) (Table 1).Since simple sequence repeat ( SSR ) markers were firstly used in human genetics (Litt and Luty 1989), it now has become one of the most widely used markers in the related researches in crops (Melchinger et al. 1998; Enoki et al. 2005), especially in the molecular characterization of genetic resources, e.g., soybean [Glycine max (L.) Merr] (Xie et al. 2005), rice (Orya sativa L.) (Garris et al. 2005), and wheat (Triticum aestivum) (Chao et al. 2007). In maize (Zea mays L.), numerous studies focusing on the genetic diversity and population structure of landraces and inbred lines in many countries and regions worldwide have been pub-lished (Liu et al. 2003; Vegouroux et al. 2005; Reif et al. 2006; Wang et al. 2008). These activities of documenting genetic diversity and population structure of maize genetic resources have facilitated the under-standing of genetic bases of maize landraces, the utili-zation of these resources, and the mining of favorable alleles from landraces. Although some studies on ge-netic diversity of Chinese maize inbred lines were con-ducted (Yu et al. 2007; Wang et al. 2008), the general profile of genetic diversity in Chinese maize landraces is scarce. Especially, there are not any reports on ge-netic diversity of the maize landraces collected from SR, a possibly earliest maize growing area in China. In this paper, a total of 143 landraces from SR listed in the core collection of CNG were genotyped by using SSR markers, with the aim of revealing genetic diver-sity of the landraces from SR (Table 2) of China and examining genetic relationships and population struc-ture of these landraces.MATERIALS AND METHODSPlant materials and DNA extractionTotally, 143 landraces from SR which are listed in the core collection of CNG established by sequential strati-fication method (Liu et al. 2004) were used in the present study. Detailed information of all these landrace accessions is listed in Table 1. For each landrace, DNA sample was extracted by a CTAB method (Saghi-Maroof et al. 1984) from a bulk pool constructed by an equal-amount of leaves materials sampled from 15 random-chosen plants of each landrace according to the proce-dure of Reif et al. (2005b).SSR genotypingA total of 54 simple sequence repeat (SSR) markers covering the entire maize genome were screened to fin-gerprint all of the 143 core landrace accessions (Table 3). 5´ end of the left primer of each locus was tailed by an M13 sequence of 5´-CACGACGTTGTAAAACGAC-3´. PCR amplification was performed in a 15 L reac-tion containing 80 ng of template DNA, 7.5 mmol L-1 of each of the four dNTPs, 1×Taq polymerase buffer, 1.5 mmol L-1 MgCl2, 1 U Taq polymerase (Tiangen Biotech Co. Ltd., Beijing, China), 1.2 mol L-1 of forward primer and universal fluorescent labeled M13 primer, and 0.3 mol L-1 of M13 sequence tailed reverse primer (Schuelke 2000). The amplification was carried out in a 96-well DNA thermal cycler (GeneAmp PCR System 9700, Applied Biosystem, USA). PCR products were size-separated on an ABI Prism 3730XL DNA sequencer (HitachiHigh-Technologies Corporation, Tokyo, Japan) via the software packages of GENEMAPPER and GeneMarker ver. 6 (SoftGenetics, USA).Data analysesAverage number of alleles per locus and average num-ber of group-specific alleles per locus were identifiedAnalysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of China 1253Table 1 The detailed information about the landraces used in the present studyPGS revealed by Structure1) NJ dendragram revealed Group 1 Group 2 by phylogenetic analysis140-150tian 00120005AnH-06Jingde Anhui 0.0060.994Group 2170tian00120006AnH-07Jingde Anhui 0.0050.995Group 2Zixihuangyumi00120007AnH-08Zixi Anhui 0.0020.998Group 2Zixibaihuangzayumi 00120008AnH-09Zixi Anhui 0.0030.997Group 2Baiyulu 00120020AnH-10Yuexi Anhui 0.0060.994Group 2Wuhuazi 00120021AnH-11Yuexi Anhui 0.0030.997Group 2Tongbai 00120035AnH-12Tongling Anhui 0.0060.994Group 2Yangyulu 00120036AnH-13Yuexi Anhui 0.0040.996Group 2Huangli 00120037AnH-14Tunxi Anhui 0.0410.959Group 2Baiyumi 00120038AnH-15Tunxi Anhui 0.0030.997Group 2Dapigu00120039AnH-16Tunxi Anhui 0.0350.965Group 2150tianbaiyumi 00120040AnH-17Xiuning Anhui 0.0020.998Group 2Xiuning60tian 00120042AnH-18Xiuning Anhui 0.0040.996Group 2Wubaogu 00120044AnH-19ShitaiAnhui 0.0020.998Group 2Kuyumi00130001FuJ-01Shanghang Fujian 0.0050.995Group 2Zhongdouyumi 00130003FuJ-02Shanghang Fujian 0.0380.962Group 2Baixinyumi 00130004FuJ-03Liancheng Fujian 0.0040.996Group 2Hongxinyumi 00130005FuJ-04Liancheng Fujian 0.0340.966Group 2Baibaogu 00130008FuJ-05Changding Fujian 0.0030.997Group 2Huangyumi 00130011FuJ-06Jiangyang Fujian 0.0020.998Group 2Huabaomi 00130013FuJ-07Shaowu Fujian 0.0020.998Group 2Huangbaomi 00130014FuJ-08Songxi Fujian 0.0020.998Group 2Huangyumi 00130016FuJ-09Wuyishan Fujian 0.0460.954Group 2Huabaogu 00130019FuJ-10Jian’ou Fujian 0.0060.994Group 2Huangyumi 00130024FuJ-11Guangze Fujian 0.0010.999Group 2Huayumi 00130025FuJ-12Nanping Fujian 0.0040.996Group 2Huangyumi 00130026FuJ-13Nanping Fujian 0.0110.989Group 2Hongbaosu 00130027FuJ-14Longyan Fujian 0.0160.984Group 2Huangfansu 00130029FuJ-15Loangyan Fujian 0.0020.998Group 2Huangbaosu 00130031FuJ-16Zhangping Fujian 0.0060.994Group 2Huangfansu 00130033FuJ-17Zhangping Fujian0.0040.996Group 2Baolieyumi 00190001GuangD-01Guangzhou Guangdong 0.9890.011Group 1Nuomibao (I)00190005GuangD-02Shixing Guangdong 0.9740.026Group 1Nuomibao (II)00190006GuangD-03Shixing Guangdong 0.9790.021Group 1Zasehuabao 00190010GuangD-04Lechang Guangdong 0.9970.003Group 1Zihongmi 00190013GuangD-05Lechang Guangdong 0.9880.012Group 1Jiufengyumi 00190015GuangD-06Lechang Guangdong 0.9950.005Group 1Huangbaosu 00190029GuangD-07MeiGuangdong 0.9970.003Group 1Bailibao 00190032GuangD-08Xingning Guangdong 0.9980.002Group 1Nuobao00190038GuangD-09Xingning Guangdong 0.9980.002Group 1Jinlanghuang 00190048GuangD-10Jiangcheng Guangdong 0.9960.004Group 1Baimizhenzhusu 00190050GuangD-11Yangdong Guangdong 0.9940.006Group 1Huangmizhenzhusu 00190052GuangD-12Yangdong Guangdong 0.9930.007Group 1Baizhenzhu 00190061GuangD-13Yangdong Guangdong 0.9970.003Group 1Baiyumi 00190066GuangD-14Wuchuan Guangdong 0.9880.012Group 1Bendibai 00190067GuangD-15Suixi Guangdong 0.9980.002Group 1Shigubaisu 00190068GuangD-16Gaozhou Guangdong 0.9960.004Group 1Zhenzhusu 00190069GuangD-17Xinyi Guangdong 0.9960.004Group 1Nianyaxixinbai 00190070GuangD-18Huazhou Guangdong 0.9960.004Group 1Huangbaosu 00190074GuangD-19Xinxing Guangdong 0.9950.005Group 1Huangmisu 00190076GuangD-20Luoding Guangdong 0.940.060Group 1Huangmi’ai 00190078GuangD-21Luoding Guangdong 0.9980.002Group 1Bayuemai 00190084GuangD-22Liannan Guangdong 0.9910.009Group 1Baiyumi 00300001HaiN-01Haikou Hainan 0.9960.004Group 1Baiyumi 00300003HaiN-02Sanya Hainan 0.9970.003Group 1Hongyumi 00300004HaiN-03Sanya Hainan 0.9980.002Group 1Baiyumi00300011HaiN-04Tongshi Hainan 0.9990.001Group 1Zhenzhuyumi 00300013HaiN-05Tongshi Hainan 0.9980.002Group 1Zhenzhuyumi 00300015HaiN-06Qiongshan Hainan 0.9960.004Group 1Aiyumi 00300016HaiN-07Qiongshan Hainan 0.9960.004Group 1Huangyumi 00300021HaiN-08Qionghai Hainan 0.9970.003Group 1Y umi 00300025HaiN-09Qionghai Hainan 0.9870.013Group 1Accession name Entry code Analyzing code Origin (county/city)Province/Region1254LIU Zhi-zhai et al .Baiyumi00300032HaiN-10Tunchang Hainan 0.9960.004Group 1Huangyumi 00300051HaiN-11Baisha Hainan 0.9980.002Group 1Baihuangyumi 00300055HaiN-12BaishaHainan 0.9970.003Group 1Machihuangyumi 00300069HaiN-13Changjiang Hainan 0.9900.010Group 1Hongyumi00300073HaiN-14Dongfang Hainan 0.9980.002Group 1Xiaohonghuayumi 00300087HaiN-15Lingshui Hainan 0.9980.002Group 1Baiyumi00300095HaiN-16Qiongzhong Hainan 0.9950.005Group 1Y umi (Baimai)00300101HaiN-17Qiongzhong Hainan 0.9980.002Group 1Y umi (Xuemai)00300103HaiN-18Qiongzhong Hainan 0.9990.001Group 1Huangmaya 00100008JiangS-10Rugao Jiangsu 0.0040.996Group 2Bainian00100012JiangS-11Rugao Jiangsu 0.0080.992Group 2Bayebaiyumi 00100016JiangS-12Rudong Jiangsu 0.0040.996Group 2Chengtuohuang 00100021JiangS-13Qidong Jiangsu 0.0050.995Group 2Xuehuanuo 00100024JiangS-14Qidong Jiangsu 0.0020.998Group 2Laobaiyumi 00100032JiangS-15Qidong Jiangsu 0.0050.995Group 2Laobaiyumi 00100033JiangS-16Qidong Jiangsu 0.0010.999Group 2Huangwuye’er 00100035JiangS-17Hai’an Jiangsu 0.0030.997Group 2Xiangchuanhuang 00100047JiangS-18Nantong Jiangsu 0.0060.994Group 2Huangyingzi 00100094JiangS-19Xinghua Jiangsu 0.0040.996Group 2Xiaojinhuang 00100096JiangS-20Yangzhou Jiangsu 0.0010.999Group 2Liushizi00100106JiangS-21Dongtai Jiangsu 0.0030.997Group 2Kangnandabaizi 00100108JiangS-22Dongtai Jiangsu 0.0020.998Group 2Shanyumi 00140020JiangX-01Dexing Jiangxi 0.9970.003Group 1Y umi00140024JiangX-02Dexing Jiangxi 0.9970.003Group 1Tianhongyumi 00140027JiangX-03Yushan Jiangxi 0.9910.009Group 1Hongganshanyumi 00140028JiangX-04Yushan Jiangxi 0.9980.002Group 1Zaoshuyumi 00140032JiangX-05Qianshan Jiangxi 0.9970.003Group 1Y umi 00140034JiangX-06Wannian Jiangxi 0.9970.003Group 1Y umi 00140038JiangX-07De’an Jiangxi 0.9940.006Group 1Y umi00140045JiangX-08Wuning Jiangxi 0.9740.026Group 1Chihongyumi 00140049JiangX-09Wanzai Jiangxi 0.9920.008Group 1Y umi 00140052JiangX-10Wanzai Jiangxi 0.9930.007Group 1Huayumi 00140060JiangX-11Jing’an Jiangxi 0.9970.003Group 1Baiyumi 00140065JiangX-12Pingxiang Jiangxi 0.9940.006Group 1Huangyumi00140066JiangX-13Pingxiang Jiangxi 0.9680.032Group 1Nuobaosuhuang 00140068JiangX-14Ruijin Jiangxi 0.9950.005Group 1Huangyumi 00140072JiangX-15Xinfeng Jiangxi 0.9960.004Group 1Wuningyumi 00140002JiangX-16Jiujiang Jiangxi 0.0590.941Group 2Tianyumi 00140005JiangX-17Shangrao Jiangxi 0.0020.998Group 2Y umi 00140006JiangX-18Shangrao Jiangxi 0.0310.969Group 2Baiyiumi 00140012JiangX-19Maoyuan Jiangxi 0.0060.994Group 260riyumi 00140016JiangX-20Maoyuan Jiangxi 0.0020.998Group 2Shanyumi 00140019JiangX-21Dexing Jiangxi 0.0050.995Group 2Laorenya 00090002ShangH-01Chongming Shanghai 0.0050.995Group 2Jinmeihuang 00090004ShangH-02Chongming Shanghai 0.0020.998Group 2Zaobaiyumi 00090006ShangH-03Chongming Shanghai 0.0020.998Group 2Chengtuohuang 00090007ShangH-04Chongming Shanghai 0.0780.922Group 2Benyumi (Huang)00090008ShangH-05Shangshi Shanghai 0.0020.998Group 2Bendiyumi 00090010ShangH-06Shangshi Shanghai 0.0040.996Group 2Baigengyumi 00090011ShangH-07Jiading Shanghai 0.0020.998Group 2Huangnuoyumi 00090012ShangH-08Jiading Shanghai 0.0040.996Group 2Huangdubaiyumi 00090013ShangH-09Jiading Shanghai 0.0440.956Group 2Bainuoyumi 00090014ShangH-10Chuansha Shanghai 0.0010.999Group 2Laorenya 00090015ShangH-11Shangshi Shanghai 0.0100.990Group 2Xiaojinhuang 00090016ShangH-12Shangshi Shanghai 0.0050.995Group 2Gengbaidayumi 00090017ShangH-13Shangshi Shanghai 0.0020.998Group 2Nongmeiyihao 00090018ShangH-14Shangshi Shanghai 0.0540.946Group 2Chuanshazinuo 00090020ShangH-15Chuansha Shanghai 0.0550.945Group 2Baoanshanyumi 00110004ZheJ-01Jiangshan Zhejiang 0.0130.987Group 2Changtaixizi 00110005ZheJ-02Jiangshan Zhejiang 0.0020.998Group 2Shanyumibaizi 00110007ZheJ-03Jiangshan Zhejiang 0.0020.998Group 2Kaihuajinyinbao 00110017ZheJ-04Kaihua Zhejiang 0.0100.990Group 2Table 1 (Continued from the preceding page)PGS revealed by Structure 1) NJ dendragram revealed Group1 Group2 by phylogenetic analysisAccession name Entry code Analyzing code Origin (county/city)Province/RegoinAnalysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of China 1255Liputianzi00110038ZheJ-05Jinhua Zhejiang 0.0020.998Group 2Jinhuaqiuyumi 00110040ZheJ-06Jinhua Zhejiang 0.0050.995Group 2Pujiang80ri 00110069ZheJ-07Pujiang Zhejiang 0.0210.979Group 2Dalihuang 00110076ZheJ-08Yongkang Zhejiang 0.0140.986Group 2Ziyumi00110077ZheJ-09Yongkang Zhejiang 0.0020.998Group 2Baiyanhandipinzhong 00110078ZheJ-10Yongkang Zhejiang 0.0030.997Group 2Duosuiyumi00110081ZheJ-11Wuyi Zhejiang 0.0020.998Group 2Chun’an80huang 00110084ZheJ-12Chun’an Zhejiang 0.0020.998Group 2120ribaiyumi 00110090ZheJ-13Chun’an Zhejiang 0.0020.998Group 2Lin’anliugu 00110111ZheJ-14Lin’an Zhejiang 0.0030.997Group 2Qianhuangyumi00110114ZheJ-15Lin’an Zhejiang 0.0030.997Group 2Fenshuishuitianyumi 00110118ZheJ-16Tonglu Zhejiang 0.0410.959Group 2Kuihualiugu 00110119ZheJ-17Tonglu Zhejiang 0.0030.997Group 2Danbaihuang 00110122ZheJ-18Tonglu Zhejiang 0.0020.998Group 2Hongxinma 00110124ZheJ-19Jiande Zhejiang 0.0030.997Group 2Shanyumi 00110136ZheJ-20Suichang Zhejiang 0.0030.997Group 2Bai60ri 00110143ZheJ-21Lishui Zhejiang 0.0050.995Group 2Zeibutou 00110195ZheJ-22Xianju Zhejiang 0.0020.998Group 2Kelilao00110197ZheJ-23Pan’an Zhejiang 0.0600.940Group 21)The figures refered to the proportion of membership that each landrace possessed.Table 1 (Continued from the preceding page)PGS revealed by Structure 1) NJ dendragram revealed Group 1 Group 2 by phylogenetic analysisAccession name Entry code Analyzing code Origin (county/city)Province/Regoin Table 2 Construction of two phylogenetic groups (SSR-clustered groups) and their correlation with geographical locationsGeographical location SSR-clustered groupChi-square testGroup 1Group 2Total Guangdong 2222 χ2 = 124.89Hainan 1818P < 0.0001Jiangxi 15621Anhui 1414Fujian 1717Jiangsu 1313Shanghai 1515Zhejiang 2323Total5588143by the software of Excel MicroSatellite toolkit (Park 2001). Average number of alleles per locus was calcu-lated by the formula rAA rj j¦1, with the standarddeviation of1)()(12¦ r A AA rj jV , where A j was thenumber of distinct alleles at locus j , and r was the num-ber of loci (Park 2001).Unbiased gene diversity also known as expected heterozygosity, observed heterozygosity for each lo-cus and average gene diversity across the 54 SSR loci,as well as model-based groupings inferred by Struc-ture ver. 2.2, were calculated by the softwarePowerMarker ver.3.25 (Liu et al . 2005). Unbiased gene diversity for each locus was calculated by˅˄¦ 2ˆ1122ˆi x n n h , where 2ˆˆ2ˆ2¦¦z ji ijij i X X x ,and ij X ˆwas the frequency of genotype A i A jin the sample, and n was the number of individuals sampled.The average gene diversity across 54 loci was cal-culated as described by Nei (1987) as follows:rh H rj j ¦1ˆ, with the variance ,whereThe average observed heterozygosity across the en-tire loci was calculated as described by (Hedrick 1983)as follows: r jrj obsobs n h h ¦1, with the standard deviationrn h obs obsobs 1V1256LIU Zhi-zhai et al.Phylogenetic analysis and population genetic structureRelationships among all of the 143 accessions collected from SR were evaluated by using the unweighted pair group method with neighbor-joining (NJ) based on the log transformation of the proportion of shared alleles distance (InSPAD) via PowerMarker ver. 3.25 (FukunagaTable 3 The PIC of each locus and the number of alleles detected by 54 SSRsLocus Bin Repeat motif PIC No. of alleles Description 2)bnlg1007y51) 1.02AG0.7815Probe siteumc1122 1.06GGT0.639Probe siteumc1147y41) 1.07CA0.2615Probe sitephi961001) 2.00ACCT0.298Probe siteumc1185 2.03GC0.7215ole1 (oleosin 1)phi127 2.08AGAC0.577Probe siteumc1736y21) 2.09GCA T0.677Probe sitephi453121 3.01ACC0.7111Probe sitephi374118 3.03ACC0.477Probe sitephi053k21) 3.05A TAC0.7910Probe sitenc004 4.03AG0.4812adh2 (alcohol dehydrogenase 2)bnlg490y41) 4.04T A0.5217Probe sitephi079 4.05AGATG0.495gpc1(glyceraldehyde-3-phosphate dehydrogenase 1) bnlg1784 4.07AG0.6210Probe siteumc1574 4.09GCC0.719sbp2 (SBP-domain protein 2)umc1940y51) 4.09GCA0.4713Probe siteumc1050 4.11AA T0.7810cat3 (catalase 3)nc130 5.00AGC0.5610Probe siteumc2112y31) 5.02GA0.7014Probe sitephi109188 5.03AAAG0.719Probe siteumc1860 5.04A T0.325Probe sitephi085 5.07AACGC0.537gln4 (glutamine synthetase 4)phi331888 5.07AAG0.5811Probe siteumc1153 5.09TCA0.7310Probe sitephi075 6.00CT0.758fdx1 (ferredoxin 1)bnlg249k21) 6.01AG0.7314Probe sitephi389203 6.03AGC0.416Probe sitephi299852y21) 6.07AGC0.7112Probe siteumc1545y21)7.00AAGA0.7610hsp3(heat shock protein 3)phi1127.01AG0.5310o2 (opaque endosperm 2)phi4207018.00CCG0.469Probe siteumc13598.00TC0.7814Probe siteumc11398.01GAC0.479Probe siteumc13048.02TCGA0.335Probe sitephi1158.03A TAC0.465act1(actin1)umc22128.05ACG0.455Probe siteumc11218.05AGAT0.484Probe sitephi0808.08AGGAG0.646gst1 (glutathione-S-transferase 1)phi233376y11)8.09CCG0.598Probe sitebnlg12729.00AG0.8922Probe siteumc20849.01CTAG0.498Probe sitebnlg1520k11)9.01AG0.5913Probe sitephi0659.03CACCT0.519pep1(phosphoenolpyruvate carboxylase 1)umc1492y131)9.04GCT0.2514Probe siteumc1231k41)9.05GA0.2210Probe sitephi1084119.06AGCT0.495Probe sitephi4488809.06AAG0.7610Probe siteumc16759.07CGCC0.677Probe sitephi041y61)10.00AGCC0.417Probe siteumc1432y61)10.02AG0.7512Probe siteumc136710.03CGA0.6410Probe siteumc201610.03ACAT0.517pao1 (polyamine oxidase 1)phi06210.04ACG0.337mgs1 (male-gametophyte specific 1)phi07110.04GGA0.515hsp90 (heat shock protein, 90 kDa)1) These primers were provided by Beijing Academy of Agricultural and Forestry Sciences (Beijing, China).2) Searched from Analysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of China1257et al. 2005). The unrooted phylogenetic tree was finally schematized with the software MEGA (molecular evolu-tionary genetics analysis) ver. 3.1 (Kumar et al. 2004). Additionally, a chi-square test was used to reveal the correlation between the geographical origins and SSR-clustered groups through FREQ procedure implemented in SAS ver. 9.0 (2002, SAS Institute, Inc.).In order to reveal the population genetic structure (PGS) of 143 landrace accessions, a Bayesian approach was firstly applied to determine the number of groups (K) that these materials should be assigned by the soft-ware BAPS (Bayesian Analysis of Population Structure) ver.5.1. By using BAPS, a fixed-K clustering proce-dure was applied, and with each separate K, the num-ber of runs was set to 100, and the value of log (mL) was averaged to determine the appropriate K value (Corander et al. 2003; Corander and Tang 2007). Since the number of groups were determined, a model-based clustering analysis was used to assign all of the acces-sions into the corresponding groups by an admixture model and a correlated allele frequency via software Structure ver.2.2 (Pritchard et al. 2000; Falush et al. 2007), and for the given K value determined by BAPS, three independent runs were carried out by setting both the burn-in period and replication number 100000. The threshold probability assigned individuals into groupswas set by 0.8 (Liu et al. 2003). The PGS result carried out by Structure was visualized via Distruct program ver. 1.1 (Rosenberg 2004).RESULTSGenetic diversityA total of 517 alleles were detected by the whole set of54 SSRs covering the entire maize genome through all of the 143 maize landraces, with an average of 9.57 alleles per locus and ranged from 4 (umc1121) to 22 (bnlg1272) (Table 3). Among all the alleles detected, the number of distinct alleles accounted for 132 (25.53%), with an av-erage of 2.44 alleles per locus. The distinct alleles dif-fered significantly among the landraces from different provinces/regions, and the landraces from Guangdong, Fujian, Zhejiang, and Shanghai possessed more distinct alleles than those from the other provinces/regions, while those from southern Anhui possessed the lowest distinct alleles, only counting for 3.28% of the total (Table 4).Table 4 The genetic diversity within eight provinces/regions and groups revealed by 54 SSRsProvince/Region Sample size Allele no.1)Distinct allele no.Gene diversity (expected heterozygosity)Observed heterozygosity Anhui14 4.28 (4.19) 69 (72.4)0.51 (0.54)0.58 (0.58)Fujian17 4.93 (4.58 80 (79.3)0.56 (0.60)0.63 (0.62)Guangdong22 5.48 (4.67) 88 (80.4)0.57 (0.59)0.59 (0.58)Hainan18 4.65 (4.26) 79 (75.9)0.53 (0.57)0.55 (0.59)Jiangsu13 4.24 700.500.55Jiangxi21 4.96 (4.35) 72 (68.7)0.56 (0.60)0.68 (0.68)Shanghai15 5.07 (4.89) 90 (91.4)0.55 (0.60)0.55 (0.55)Zhejiang23 5.04 (4.24) 85 (74)0.53 (0.550.60 (0.61)Total/average1439.571320.610.60GroupGroup 155 6.63 (6.40) 91 (89.5)0.57 (0.58)0.62 (0.62)Group 2887.94 (6.72)110 (104.3)0.57 (0.57)0.59 (0.58)Total/Average1439.571320.610.60Provinces/Regions within a groupGroup 1Total55 6.69 (6.40) 910.57 (0.58)0.62 (0.62)Guangdong22 5.48 (4.99) 86 (90.1)0.57 (0.60)0.59 (0.58)Hainan18 4.65 (4.38) 79 (73.9)0.53 (0.56)0.55 (0.59)Jiangxi15 4.30 680.540.69Group 2Total887.97 (6.72)110 (104.3)0.57 (0.57)0.59 (0.58)Anhui14 4.28 (3.22) 69 (63.2)0.51 (0.54)0.58 (0.57)Fujian17 4.93 (3.58) 78 (76.6)0.56 (0.60)0.63 (0.61)Jiangsu13 4.24 (3.22) 71 (64.3)0.50 (0.54)0.55 (0.54)Jiangxi6 3.07 520.460.65Shanghai15 5.07 (3.20) 91 (84.1)0.55 (0.60)0.55 (0.54)Zhejiang23 5.04 (3.20) 83 (61.7)0.53 (0.54)0.60 (0.58)1258LIU Zhi-zhai et al.Among the 54 loci used in the study, 16 (or 29.63%) were dinucleotide repeat SSRs, which were defined as type class I-I, the other 38 loci were SSRs with a longer repeat motifs, and two with unknown repeat motifs, all these 38 loci were defined as the class of I-II. In addition, 15 were located within certain functional genes (defined as class II-I) and the rest were defined as class II-II. The results of comparison indicated that the av-erage number of alleles per locus captured by class I-I and II-II were 12.88 and 10.05, respectively, which were significantly higher than that by type I-II and II-I (8.18 and 8.38, respectively). The gene diversity re-vealed by class I-I (0.63) and II-I (0.63) were some-what higher than by class I-II (0.60) and II-II (0.60) (Table 5).Genetic relationships of the core landraces Overall, 143 landraces were clustered into two groups by using neighbor-joining (NJ) method based on InSPAD. All the landraces from provinces of Guangdong and Hainan and 15 of 21 from Jiangxi were clustered together to form group 1, and the other 88 landraces from the other provinces/regions formed group 2 (Fig.-B). The geographical origins of all these 143 landraces with the clustering results were schematized in Fig.-D. Revealed by the chi-square test, the phylogenetic results (SSR-clustered groups) of all the 143 landraces from provinces/regions showed a significant correlation with their geographical origin (χ2=124.89, P<0.0001, Table 2).Revealed by the phylogenetic analysis based on the InSPAD, the minimum distance was observed as 0.1671 between two landraces, i.e., Tianhongyumi (JiangX-03) and Hongganshanyumi (JiangX-04) collected from Jiangxi Province, and the maximum was between two landraces of Huangbaosu (FuJ-16) and Hongyumi (HaiN-14) collected from provinces of Fujian and Hainan, respectively, with the distance of 1.3863 (data not shown). Two landraces (JiangX-01 and JiangX-21) collected from the same location of Dexing County (Table 1) possessing the same names as Shanyumi were separated to different groups, i.e., JiangX-01 to group1, while JiangX-21 to group 2 (Table 1). Besides, JiangX-01 and JiangX-21 showed a rather distant distance of 0.9808 (data not shown). These results indicated that JiangX-01 and JiangX-21 possibly had different ances-tral origins.Population structureA Bayesian method was used to detect the number of groups (K value) of the whole set of landraces from SR with a fixed-K clustering procedure implemented in BAPS software ver. 5.1. The result showed that all of the 143 landraces could also be assigned into two groups (Fig.-A). Then, a model-based clustering method was applied to carry out the PGS of all the landraces via Structure ver. 2.2 by setting K=2. This method as-signed individuals to groups based on the membership probability, thus the threshold probability 0.80 was set for the individuals’ assignment (Liu et al. 2003). Accordingly, all of the 143 landraces were divided into two distinct model-based groups (Fig.-C). The landraces from Guangdong, Hainan, and 15 landraces from Jiangxi formed one group, while the rest 6 landraces from the marginal countries of northern Jiangxi and those from the other provinces formed an-other group (Table 1, Fig.-D). The PGS revealed by the model-based approach via Structure was perfectly consistent with the relationships resulted from the phy-logenetic analysis via PowerMarker (Table 1).DISCUSSIONThe SR includes eight provinces, i.e., southern Jiangsu and Anhui, Shanghai, Zhejiang, Fujian, Jiangxi, Guangdong, and Hainan (Fig.-C), with the annual maize growing area of about 1 million ha (less than 5% of theTable 5 The genetic diversity detected with different types of SSR markersType of locus No. of alleles Gene diversity Expected heterozygosity PIC Class I-I12.880.630.650.60 Class I-II8.180.600.580.55 Class II-I8.330.630.630.58。

光化学诱导大鼠脑缺血的定量分析张杰文;索爱琴;卢芬;李玮;朱良付【期刊名称】《医药论坛杂志》【年(卷),期】2006(27)19【摘要】目的研究大鼠脑缺血后损伤体积和水含量的变化。

方法给大鼠尾静脉注射孟加拉玫瑰红，经颅骨用激光黄色连续光束照射鼠脑15min产生部位、大小固定的梗死灶，对梗死灶进行定量分析。

先行独立分组，在脑缺血后选择1、4、24、72、168h共5个不同时间点，检测损伤体积的变化和脑组织的水含量。

结果诱导缺血后在1～24h内损伤体积迅速扩大135．2％，而在24～168h内则缩小，168h时检测发现损伤较1h时缺血体积大的多，而与4h时差不多。

结论组织损害的最大程度在该模型中是在前4h后达到最大，而4h损伤的扩大是与脑的含水量有密切关系。

【总页数】4页(P11-14)【关键词】光化学;脑缺血动物模型;定量分析;大鼠【作者】张杰文;索爱琴;卢芬;李玮;朱良付【作者单位】河南省人民医院神经内科【正文语种】中文【中图分类】R-332【相关文献】1.降纤酶对血栓形成和光化学诱导大鼠脑缺血的影响 [J], 武小玲;王振金;尹岭;刘育英;赵秀梅2.异亚丙基莽草酸对光化学损伤诱导的脑缺血模型大鼠学习记忆能力的影响 [J], 王晶;张硕峰;周宁家;李振;甄诚;高文秀;孙建宁;郭亚健3.脑络通方对光化学诱导脑缺血大鼠脑内bFGF影响的实验研究 [J], 郑一;高玉红;张梅奎;张笑明;汪茜;张学文;尹岭4.一氧化氮与光化学法诱导大鼠脑缺血早期损伤的关系和绞股蓝总皂苷对脑缺血损伤的保护作用 [J], 谢志忠;朱炳阳;唐小卿;廖端芳;余麟因版权原因，仅展示原文概要，查看原文内容请购买。

肿瘤内皮标记物1通过丝裂原活化蛋白激酶途径介导内皮细胞对血管新生及对心力衰竭心肌重塑徐婷;黄薇;杨力;余浩【期刊名称】《实用医学杂志》【年(卷),期】2024(40)6【摘要】目的基于肿瘤内皮标记物1(TEM1)介导的丝裂原活化蛋白激酶(MAPKs)途径,探讨内皮细胞对血管新生及对心力衰竭心肌重塑的作用。

方法将小鼠随机分成4组,包括假手术组、MI组、MI+sh-NC组和MI+sh-TEM1组。

在心肌梗死(MI)后第7天通过免疫荧光染色检测梗死边缘区EndMT的变化,第28天通过超声心动图评估小鼠的心脏功能。

小鼠主动脉内皮细胞(MAECs)分为3组:对照组、Vector组和rTEM1组。

此外,用MAPK抑制剂SB203580预处理MAECs,用rTEM1处理细胞48 h。

通过Western blot评估内皮细胞中EndMT和MAPKs 信号通路的变化。

结果在梗死边缘区的心肌中,TEM1水平在MI后第1天轻微增加,在第7天显著达到峰值,然后在第28天降低。

与Vector组相比,rTEM1组MAECs中VE-Cadherin蛋白表达显著下降(P <0.05),和α-SMA、波形蛋白蛋白水平、相对迁移距离、侵袭细胞数和形成分支数量显著增加(P <0.05)。

SB203580逆转了由rTEM1诱导MAECs的这些变化。

与MI组相比,MI+sh-TEM1组中的CD31+Vimentin+共染色水平显著降低(P <0.01)。

在第28天,MI+sh-TEM1组小鼠的LVEF和LVFS均较MI组显著增强(P <0.05)。

与MI 组相比,MI+sh-TEM1组小鼠的内皮细胞中p-P38/P38和p-JNK/JNK蛋白表达降低。

结论 TEM1诱导的EndMT和血管生成参与了MI诱导心肌重塑的发病机制,其作用机制与MAPKs信号通路激活有关。

【总页数】7页(P780-786)【作者】徐婷;黄薇;杨力;余浩【作者单位】武汉市第一医院(武汉市中西医结合医院)心血管内科【正文语种】中文【中图分类】R542.22【相关文献】1.血府逐瘀汤促急性心肌缺血大鼠心肌血管新生及对血管内皮细胞生长因子的影响2.肿瘤抑素Tum5对人脐静脉血管内皮细胞血管生成活性以及碱烧伤诱导大鼠角膜新生血管的抑制作用3.可降解材料纤维蛋白胶介导血管内皮细胞生长因子对心肌梗死组织血管再生的影响4.血清血管内皮细胞生长因子C(VEGF-C)是晚期宫颈癌的特异性生物标记物:VEGF-C与胰岛素样生长因子Ⅱ(IGF-Ⅱ)、IGF结合蛋白3(IGF-BP3)及血管内皮细胞生长因子B(VEGF-B)的关系5.吴茱萸碱介导miR-223-3p对心肌微血管内皮细胞增殖、迁移和血管生成的影响因版权原因，仅展示原文概要，查看原文内容请购买。

人血管内皮生长因子受体2胞外段在毕赤氏巴斯德酵母中的表达(英文)左秋;田聆;侯健梅;王永生;文艳君;李炯;魏于全【期刊名称】《四川大学学报：医学版》【年(卷),期】2006(37)1【摘要】目的探讨在毕赤氏巴斯德酵母(PICHIA PASTORIS)中高效表达有真核蛋白结构的人血管内皮生长因子受体2胞外段(HEVEGFR-2)的可行性。

方法从重组质粒PORF-HEVEGFR-2经PCR获全长HEVEGFR-2 DNA,构建重组毕赤氏巴斯德酵母分泌性表达载体,电转化PICHIA PASTORIS X-33。

用抗药性表型和甲醇诱导筛选出重组HEVEGFR-2蛋白表达阳性的转化子(X-33.HEVEGFR-2)。

结果SDS-PAGE显示。

获分子量约108 KDA的重组HEVEGFR-2蛋白。

约占X-33-HEVEGFR-2分泌性表达蛋白总量的45%。

该重组蛋白在表达上清中的质量浓度达80 MG/L。

其HEVEGFR-2部分分子量约106 KDA。

WESTERNBLOT证实,该蛋白能特异地与大鼠抗小鼠VEGFR-2单克隆抗体结合。

结论毕赤氏巴斯德酵母能高效表达有真核蛋白结构的人血管内皮生长因子受体2胞外段蛋白全段。

【总页数】4页(P1-4)【关键词】人血管内皮生长因子受体2;毕赤氏巴斯德酵母;基因表达【作者】左秋;田聆;侯健梅;王永生;文艳君;李炯;魏于全【作者单位】四川大学人类疾病生物治疗国家重点实验室肿瘤生物治疗研究室【正文语种】中文【中图分类】R818.74;R392【相关文献】1.人血管内皮细胞生长因子受体Flt-1胞外区cDNA在毕赤酵母中的表达和鉴定[J], 马骊;张智清;周小明;曾革非;陈爱君;姚立红;王小宁2.人血管内皮细胞生长抑制因子在巴斯德毕赤酵母中的分泌表达 [J], 刘麟;陈宇光;谈立松;唐亮;张颉3.克氏原螯虾i-型溶菌酶在巴斯德毕赤酵母中的高效胞外表达及其抑菌活性 [J], 水燕; 管政兵; 叶俊贤; 史永红; 刘国锋; 徐增洪4.异种同源表皮生长因子受体EGFR胞外段在毕赤巴斯德酵母中的表达 [J], 方芳;李炯;文艳君;田聆;魏于全5.鹌鹑血管内皮生长因子受体Quek1胞外段第2～4区cDNA在毕赤酵母中的表达和鉴定 [J], 刁鹏;文艳君;王永生;杜小波;周行;魏于全因版权原因，仅展示原文概要，查看原文内容请购买。

溶血性贫血动物模型制作步骤及方法溶血性贫血是由于红细胞破坏增多、增速，超过造血代偿能力时所发生的一组贫血。

红细胞的平均寿命为15～20d，红细胞破坏速度远远超过骨髓的代偿潜力时，则出现贫血。

溶血性贫血发病的基本问题是红细胞寿命缩短，易于破坏。

主要通过以下三方面的机制：红细胞膜的异常变化；血红蛋白的异常；机械性因素。

1乙酰苯肼诱发的溶血性贫血大鼠模型(1)复制方法体重为180～250g的雄性大鼠，大鼠常规饲养，自由饮水和进食。

分别于造模的1, 4, 7日经腹腔注射2％乙酰苯肼(Acetylphenylhydrazine, APH)生理盐水溶液，初次注射剂量为1ml/100g体重，第2、3次剂量减半为0.5ml/100g体重。

注射乙酰苯肼后，每天上午经大鼠尾静脉取血作血红蛋白测定，并进行血红细胞计数和白细胞计数。

通过不同方法分别作网织红细胞、海氏小体(Heina body)、中性粒细胞、碱性磷酸酶(AKP)、酸性磷酸酶(ACP)、ATP 酶、琥珀酸脱氢酶(SKH)及葡萄糖-6-磷酸酶(G-6- P)染色。

(2)模型特点注射APH后第3日，模型大鼠开始出现疲乏无力，行动迟缓，嗜睡、喘息；面、眼、耳、尾苍白，体温偏低等临床表现。

肉眼观察可见肝、脾均肿大，脾肿大尤为明显，呈暗红色。

血液学观察指标：血红蛋白和红细胞呈进行性下降，网织红细胞、海氏小体和白细胞总数显著增多(显示出贫血性血象)。

注射APH 1周后，模型动物血红蛋白可下降为40～70g/L；红细胞降为(200～400)×1000000000/L；白细胞降为(30～39)×1000000000/L；网织红细胞则升为85％～95％，海氏小体升至30％～38％(正常为0)。

血细胞组织化学染色观察显示中性粒细胞AKP、ACP、ATP酶、SDH和G-6-P酶均出现不同程度异常。

(3)比较医学乙酰苯肼可引起骨髓造血干细胞生长发生变化，促使其从骨髓向脾脏转移，而在代偿期出现骨髓血细胞增多。

粒细胞集落刺激因子与血管性痴呆大鼠海马凋亡相关蛋白李肖云;兰希发;王玉琳;刘晶【期刊名称】《中国组织工程研究》【年(卷),期】2012(016)036【摘要】背景：研究表明粒细胞集落刺激因子在保护神经元免受各种因素所致的神经元变性和死亡中发挥重要作用。

目的：观察粒细胞集落刺激因子对血管性痴呆大鼠海马组织神经细胞凋亡及Bcl-2、Bax蛋白表达的影响。

方法：采用永久性双侧颈总动脉结扎法建立SD大鼠血管性痴呆模型,以未进行血管结扎的大鼠作为假手术组。

造模成功后,治疗组大鼠每日皮下注射粒细胞集落刺激因子50μg/kg,假手术组和模型组注射等量的生理盐水。

分别于造模后7,14,28d取大鼠海马组织用于检测。

结果与结论：Morris水迷宫结果显示,模型组大鼠逃避潜伏期明显延长（P 〈0.01）,而治疗组各时间点大鼠逃避潜伏期较模型组缩短（P〈0.01）;TUNEL及免疫组织化学结果显示,与模型组比较,治疗组各时间点大鼠海马TUNEL及Bax阳性细胞吸光度值明显减小（P〈0.01）,Bcl-2阳性细胞吸光度值明显增加（P 〈0.01）。

说明粒细胞集落刺激因子可提高血管性痴呆大鼠海马Bcl-2蛋白的表达,抑制Bax蛋白的表达,减少神经细胞凋亡,改善大鼠的学习记忆功能。

【总页数】7页(P6741-6747)【作者】李肖云;兰希发;王玉琳;刘晶【作者单位】【正文语种】中文【中图分类】R394.2【相关文献】1.自噬对血管性痴呆大鼠海马CA1区生长相关蛋白-43及微管相关蛋白-2表达的影响 [J], 张文彦;刘金霞;刘斌;邓春颖;张晋霞;马原源;毛文静;李世英;吕超男2.血管性痴呆大鼠海马CA1区凋亡相关蛋白Bcl-2和Bax的表达 [J], 袁敏;刘贵江;刘斌3.粒细胞集落刺激因子与血管性痴呆大鼠海马凋亡相关蛋白 [J], 李肖云;兰希发;王玉琳;刘晶4.粒细胞集落刺激因子对血管性痴呆大鼠海马神经细胞凋亡的影响 [J], 李肖云;兰希发5.电针对血管性痴呆大鼠海马神经元凋亡相关蛋白Bcl-2、Bax和HO-1的影响[J], 李敏;徐国峰因版权原因，仅展示原文概要，查看原文内容请购买。

《毒理学基础》重点大全：先说一句，六，七，八，十二章是本书重点中的重点。

注意详细看课本。

一.名词解析：1.毒理学（toxicology）：的传统定义是研究外源化学物对生物体损害作用的学科，现代毒理学已发展为所有外源因素对生物系统的损害作用，生物学机制，安全性评价与危险性分析的学科。

2.最大耐受剂量（maximal tolerance dose）：指化学物质不引起受试对象出现死亡的最高剂量3.自由基(free radical)：是独立游离存在的带有不成对电子的分子、原子和离子，它主要由化合物的共价键发生均裂而产生。

4.易感生物学标志（biomarker of susceptibility）：是关于个体对外源化学物的生物易感性的指标即反应机体先天具有或后天获得的对暴露外源物质产生反应能力的指标。

5.半减期（half life）：外源化学物的血浆浓度下降一半所需要的时间，它是衡量机体消除化学物能力的一个重要参数。

6.癌基因（Oncogene）：一类在自然或试验条件下，具有诱发恶性转化的潜在基因。

7.急性毒性(acute toxicity)：是指机体（实验动物或人）一次或24小时内接触多次一定剂量外源化合物后在短期内所产生的毒作用及死亡。

包括一般行为、大体形态变化及死亡效应。

8.基准剂量BMD\benchmark dose：是依据动物试验剂量-反应关系的结果，用一定的统计学模式求得的引起一定比例动物出现阳性反应剂量的95%可信限区间的下限值。

9.生物转化（Biotransformation）：又称代谢转化，指外源化学物在体内经历酶促反应或非酶促反应而形成的代谢产物的过程。

10.代谢酶遗传多态性：不同种属，不同个体内的同一种代谢酶的基因编码不同，从而导致了其功能的不同，这就是代谢酶遗传多态性11.危险度（risk）：又称危险或危险性，指在特定条件下，因接触某种水平的化学毒物而造成机体损伤、发生疾病，甚至死亡的预期概率。

两组份途径出现在真核细胞中
范宗理;Kosh.,DE
【期刊名称】《世界科学》
【年(卷),期】1994(000)011
【摘要】两组份途径出现在真核细胞中ＤａｎｉｅｌＥ．ＫｏｓｈｌａｎｄＪｒ著范宗理译可把两种生物学原理，简称为“重复性原理”和“多样性原理”。

遵循“重复性原理”的自然特性，通过选择简单机构或模件作为复杂系统的组件，其后再在另外系统中反复利用这些组件。

多样性原理，...
【总页数】1页(P6)
【作者】范宗理;Kosh.,DE
【作者单位】不详;不详
【正文语种】中文
【中图分类】Q24
【相关文献】
1.HPLC法测定复方麝香草酚滴耳液中两种组份的含量 [J], 何益锋;刘义钊
2.倍率减差法同时测定复方替硝唑含漱液中两组份的含量 [J], 张霞;刘向东
3.紫外分光光度法测定复方长压啶搽剂中两组份的含量 [J], 陈勇川;罗东;唐先哲
4.反相高效液相色谱法同时测定双唑泰栓中两组份的含量 [J], 吕经兰
5.RP-HPLC法同时测定洛斯宝活血素口服液中两组份的含量 [J], 赵雪梅
因版权原因，仅展示原文概要，查看原文内容请购买。

非等位基因概述非等位基因是指同一基因座上的不同等位基因。

等位基因是指在某个给定的基因座上，可以存在多种不同的变体。

每个个体继承了一对等位基因，一对等位基因可能会导致不同的表型表达。

非等位基因的存在使得遗传学研究更加复杂，因为不同的等位基因会对个体的表型产生不同的影响。

背景在生物学中，基因座是指染色体上一个特定的位置，该位置上的基因决定了某个特征的表达方式。

每个基因座上可以有多种不同的等位基因。

等位基因是指在某个特定基因座上的不同基因变体。

每个个体都会继承一对等位基因，通过这对等位基因的不同组合，决定了个体的表型。

然而，并非所有基因座上的等位基因都具有相同的表现型。

非等位基因的影响非等位基因的存在导致不同等位基因会对个体表型产生不同的影响。

有些非等位基因会表现出显性效应，也就是说，当个体继承了一个突变的等位基因时，即使同时继承了一个正常的等位基因，但显性效应会使得突变的等位基因的表型表达得到体现。

相反，有些非等位基因会表现出隐性效应，当个体继承了两个突变的等位基因时，才会表现出突变的表型。

除了显性和隐性效应之外，非等位基因还可能发生两种其他类型的表型效应。

一种是共显效应，当个体继承了两个不同的突变等位基因时，在表型表达上会表现出一种新的特征，这个特征并不是单个突变等位基因所能导致的。

另一种是部分显性效应，当个体继承了两个不同的突变等位基因时，表型表达将介于两个单独突变等位基因的表型之间。

重组和非等位基因重组是指两个不同的染色体交换部分基因序列的过程。

在重组的过程中，非等位基因可能会发生改变，导致新的等位基因组合形成。

这一过程使得非等位基因的表型效应更加复杂，因为新的等位基因可能将不同基因座的效应组合起来。

非等位基因的重要性非等位基因对生物的适应性和多样性起着重要作用。

通过对等位基因的各种组合的研究，人们可以更好地理解基因与表型之间的关系，并揭示遗传变异对物种适应环境的重要性。

总结非等位基因是指同一基因座上的不同等位基因。

What is a species? How do new species come into existence? These questions are some of the most enduring in biology and remain controversial today. Under many commonly accepted species definitions, speciation can be viewed as the process by which two identical populations diverge genetically to the point at which their subsequent merger would not be possi-ble.Species are therefore both genetically distinct and independent.Although distinctness is often observ-able (in morphology,for example),independence usually is not.How do species evolve to become phenotypically distinct? What are the underlying genes? What forces drive their divergence between species? Some insights into these questions might come from studying genes that cause reduced fitness in hybrids that are intermedi-ate in phenotype between two species.The fitness reduction can range from ecological maladaptation or behavioural aberration to inviability or sterility.The loci that underlie such reductions in fitness might be considered ‘speciation genes’,which are important in driving the nascent species to become independent genetic entities.Below,we review recent progress in the characterization of speciation genes.Operationally,species are often delineated by distinct phenotypes,such as distinct plumage in birds.It was the introduction of the concept of reproductive isolation (RI) that redirected the emphasis to the independent nature of species1–4.According to Mayr3,species are “groups of interbreeding natural populations that are reproductively isolated from other such groups”3.RI therefore refers to the independence of gene pools,among which new mutations and allele frequency changes are not shared.A central question about RI is whether this independence,or non-sharing,should apply to every locus in the genome.Those who argue for the primacy of RI in specia-tion1,3are essentially arguing for a ‘whole-genome’con-cept5(see BOX 1).If we apply the concept of RI to only a portion of the genome,where would we draw the line? Does it make sense to say that 75% of the genome is reproductively isolated? Indeed,in this NEO-DARWINIAN view of RI,genetic changes between species are seen to be so strongly CO-ADAPTED that few genes can be inte-grated into the genome of another species.So,almost all regions in the genome are either part of such a ‘cohesive’network or are closely linked to an element in such a network.In either case,gene flow across nascent species boundaries is effectively eliminated6.By contrast,the alternative is a genic view of specia-tion,as explained in FIG.1(see also REFS 5,7).Although rarely recognized as such,these different perspectives on the genetic architecture of species differences are the gen-esis of the long-running debate on the geographical mode of speciation;that is,whether speciation most commonly occurs when the diverging populations are in allopatry,parapatry or sympatry (see BOX 1).The central issue is whether two populations can evolve into good species while they continue to exchange genes during the process.Under the whole-genome view that gives pri-macy to RI in speciation3,gene flow between diverging populations would have such negative effects on those populations that strict geographical barriers would have to be the prelude to speciation.The alternative genicGENES AND SPECIATIONChung-I Wu* and Chau-Ti Ting‡It is only in the past five years that studies of speciation have truly entered the molecular era.Recent molecular analyses of a handful of genes that are involved in maintaining reproductiveisolation between species (speciation genes) have provided some striking insights. In particular, itseems that despite being strongly influenced by positive selection, speciation genes are oftennon-essential, having functions that are only loosely coupled to reproductive isolation. Molecularstudies might also resolve the long-running debate on the relative importance of allopatric andparapatric modes of speciation.*Department of Ecology andEvolution,University ofChicago,Chicago,Illinois 60637,USA.‡Department of Life Science,National Tsing HuaUniversity,Hsinchu,T aiwan 300,Republic of China.Correspondence to C.-I W.e-mail: ciwu@doi:10.1038/nrg1269double-bond in a long chain of saturated hydrocarbons.Two independent studies have identified the gene that controls the (5,9)/(7,11) difference to be a desaturase gene,desat2(REFS 48,49).Although CHs often act as con-tact pheromones between sexes,they have also been implicated in ecological adaptations,such as heat or starvation tolerance 50.The desat2gene apparently diverts the synthesis of 7,11-heptacosadiene into the 5,9-type.The loss of the promoter in the desat2gene therefore results in the 7,11-type among the M flies.This observation raises the interesting possibility that loss of function of a gene has a role in this particular case of nascent speciation.The geographical distribution of the two desat2variants (predominantly desat2+in Africa and desat20elsewhere)indicates that this strong differentiation must be main-tained by differential selective pressure.An excess of high-frequency nucleotide mutations highlighted the influence of positive selection on the desat2polymor-phism 49.Greenberg et al.17,50were able to show,by gene knock-out,that the loss of the desat2gene (as in non-African M flies) results in an increase in cold tolerance and a decrease in starvation tolerance.It is plausible that,in the colder climate,a non-functional desat2would spread through the cosmopolitan populations.So,this seems to be a case of ecological adaptation and differentiation.An interesting aspect of the Z–M differentiation is the unidirectional sexual isolation between these forms 51.Zimbabwe females,in the presence of Z and M males,do not mate with M males.(Note that the observation by itself does not indicate male or female choice.) We know that at least seven or eight genes control female or male mating behaviour,respect-ively 13,14.So,the question is whether desat2is one of the loci that governs Z females’mating characteris-tics (for example,reduced attractiveness to M males).CH differences have been known to govern females’attractiveness in interspecific crosses 52.However,it was widely thought that desat2was not involved in female attractiveness in the Z–M system because Caribbean flies,which carry the African desat2 allele,behave like M flies.Nevertheless,recent observations have shown that,within three African populations,the presence of the African desat2allele correlates nearly perfectly with Z-femaleness 53.One possible interpretation of this pattern is that desat2 governs female attractiveness to M males and that the Caribbean population is an anomaly that results from recent admixture between African and North American flies.Although this interpretation seems to contradict the widely-accepted view that D.melanogaster males might not be discriminatory when choosing a mate 54,new work indicates that M males might not court Z females as ardently as they court M females,espe-cially when the females are not highly receptive (C.-T.T.and C.-I W.,unpublished observations).If this is the case,the desat2gene might be playing a double role in this nascent speciation through differentiation in eco-logical adaptation and,secondarily,through mating preference.that rescued hybrid viability was a P -element insertion in its 5′region that resulted in a reduction in the amount of wild-type transcript.For Hmr to be consid-ered a true ‘speciation gene’,it would be necessary to show that the D.simulans and D.melanogaster alleles are functionally divergent in their rescue effect of hybrid viability.A recent transgenic study indicates that this might indeed be the case (D.Barbash,personal communication).Hybrid inviability in Drosophila species (Nup96).Complementation mapping (FIG.2b)has been used to analyse hybrid inviability between D.melanogaster and D.simulans .High-resolution mapping has allowed a spe-ciation gene,Nup96,to be cloned and characterized 22.The Nup96allele from D.simulans causes inviability in the F 1hybrids if the copy from D.melanogaster is absent.Nup96,which has homologues in yeast,worm and human genomes,encodes a subunit of a nuclear-pore complex,which transports macromolecules between the nucleus and cytoplasm 46and is therefore essential for viability in flies.An excess of non-synonymous substitutions in Nup96between D.melanogaster and D.simulans relative to non-synonymous polymorphisms within these species (calibrated against synonymous changes with the MCDONALD AND KREITMAN TEST ) indicated that this gene is under positive selection.With the sequences from D.mauritiana and D.yakuba ,it was possible to map putative adaptive changes onto an evolutionary tree.Presgraves et al.22concluded that the adaptive changes occurred in the distant past,a suggestion that is corrob-orated by the analysis of the extant polymorphisms in D.melanogaster and D.simulans .Had some adaptive changes occurred recently,a reduction in the amount of neutral polymorphism,which might also be accom-panied by a skew towards very low- and/or very high-frequency variants,would have been expected.Neither was observed in Nup96.Not only were Presgraves et al.22able to map the Nup96gene,but they were also able to locate the interact-ing locus in the DM model of hybrid incompatibility to the X chromosome.They did this by switching the source of the X chromosome in the hybrid males.One question to be addressed in the future is whether there are multiple loci on the X chromosome that interact with Nup96.Ecological/behavioural races in Drosophila melanogaster (desat-2).The final example of a proven speciation gene (under our broad definition;see BOX 1) provides a glimpse of the molecular genetics of ecological,and pos-sibly behavioural,isolation.D.melanogaster from central-southern Africa around Zimbabwe and those from the rest of the world (referred to as the Z and M types,respectively) have evolved to become different ecologi-cal/behavioural races.The females of African and cosmopolitan D.melanogaster carry different forms of a specific type of non-volatile CONTACT PHEROMONES .These two forms — the 5,9-heptacosadiene and 7,11-heptacosadiene forms of the 27-carbon cuticular hydrocarbons (CH)47— differ in the position of aMCDONALD AND KREITMAN TESTA test that contrasts interspecific divergence against intraspecific polymorphism.It is a powerful test to detect excess of non-synonymous substitutions between species.CONTACT PHEROMONESChemical signals that aretransmitted through the direct physical contact of two individuals.Contactpheromones in Drosophila are often sexual signals.reflective of the entire genome.So,it is the range of genes that are involved during incipient speciation that holds the greatest interest.In all five cases,there is sub-stantial divergence in DNA sequences and,among sev-eral of them,in expression as well.In at least four of the five cases,positive selection has driven the divergence.The results are relevant to the debate on whether RI might have evolved neutrally in the absence of adaptive forces.We propose that,for a gene to diverge in function,it needs to be released from its old functional niche.The release would then allow the diverging species to use the gene differently.We shall refer to this hypothesis as the genetic ‘niche-release’hypothesis.There might be two different ways for a gene to experience niche release —environmental change and gene duplication.Divergence in desat2is an example of gene divergence that has occurred as a result of environmental change that took place when the flies migrated out of Africa,whereas OdsH and Xmrk are both the result of gene duplica-tion.(Note that this present hypothesis is different from a previous model on gene duplication and RI 72.)Whichever mechanism is involved,a gene under niche release should be more likely to be functionally dispens-able.Operationally,functional dispensability means that the deletion of the gene would not lead to lethality,sterility or other forms of severe fitness reduction.Such dispensable genes might be prone to diverge in function,often becoming non-functional.Under this definition,both OdsH and desat2are dispensable.In the classical DM model,the emphasis has always been on the incompatibility interaction (the green double-headed arrow in BOX 2),but we might ask a deeper question — whether the process of divergence (the black double-headed arrows) and the resultant inter-action are related and,if so,how they are related.Such a linkage seems obvious for Xmrk-2and Nup96.For exam-ple,in the former,the dark spots,when unregulated,become melanomas.On the other hand,it might not be surprising to find some RI genes for which the normal function and the RI phenotype are only weakly coupled,or even completely unrelated.For example,the deletion of OdsH has a subtle effect on male fertility but,in the appropriate genetic background,the presence or absence of the allele from D.mauritiana determines full fertility versus (nearly) normal fertility.Similarly,the normal function of desat2might be cold tolerance but a corre-lated response is the change in CH,or the ‘perfume’on the females.In either case,the RI phenotype is out of the range of what might have been predicted on the basis of the normal function/phenotype of the speciation gene.In the past five years of limited molecular analysis on speciation,we have learned the identities of several speciation genes.Their biological functions show the molecular bases of species differentiation.These stud-ies should re-focus our attention to the genic basis of speciation.The tenet of speciation study,namely the concept of RI,is fundamentally a whole-genome concept and should be revisited after we have a more comprehensive understanding of genes and their roles in speciation.simplest kind of allopatric speciation.There is a class of models that overlay allopatry on species with a deep population structure.Such models,which are interme-diate between allopatric and parapatric ones,deserve further study.Another recent study also addressed the question of parapatric speciation from a different angle 68.The authors observed that the K A/K SRATIOS between human and chimpanzee are higher for genes on rearranged chromosomes than on collinear ones,in agreement with the parapatric model 68.However,a separate analysis showed that the K a /K s pattern is observable,with nearly identical values,between human and orangutan or human and macaque 69.So,although the observations in this study are meaningful in other respects,given the positive result from the ‘negative control’,the interpretation of parapatric speciation cannot be supported 68,70.Strictly speaking,the discussion in this section is rel-evant to animal studies only.Plant literature is replete with references to hybridization and introgression dur-ing speciation.‘Hybridization speciation’,in which a third species is formed by mixing the genetic materials from two parental species 71,is another important demonstration.What might be the basis of these dis-crepant views between animal and plant literature? It is possible that plant genomes are more modular,such that mixing components from different sources can still make a well-fit plant.If that is true,‘allopatric genealogy’(FIG.3a,b)in plants should often be rejected using the type of analysis described above.Implications and perspectivesSpeciation is not an easy subject.However,the myth that speciation is ‘the mystery of mysteries’or that it is both ‘unknown and unknowable’has not helped us to understand the subject.The perceived difficulties with the topic stem largely from a lack of knowledge at the fundamental genic level.For example,how could we hope to understand post-mating isolation when the phenotype that defines the class of genes that we are interested in does not even contain a hint of the original function for which each of these genes evolved? The five cases discussed above represent all those we could find that fulfil the criteria of a ‘speciation gene’.Nevertheless,even from this limited set,which is based mainly on one taxonomic group (four of them are from Drosophila ),the range of the molecular identity,as well as the under-lying principle,is broad.Three of the five cases are related to transcriptional regulation (Xmrk ,OdsH and Hmr ),supporting the common postulate that species divergence is regulatory in nature.Moreover,in desat2,which is not a regulatory gene,the change during INCIPIENT SPECIATION is nevertheless in the regulatory region.The nature of speciation genes is also likely to be a function of the age of the speciation event.The range of genes underlying RI between highly differentiated species,such as D.melanogaster and D.simulans ,might be different from that between incipient species.As the divergence increases,more genes might contribute to RI and the range might become broader and more evenlyK A /K S RATIOSRatios of non-synonymous substitutions to synonymous substitutions per site.INCIPIENT SPECIATIONThe initial stage of species formation during which reproductive isolation is only partial.。

高分辨率溶解曲线在4种皮肤癣菌快速鉴定中的初步应用刘红芳;吴宜泉;刘应辉;谢振谋;陈阳霞;黄进梅;曾维英【期刊名称】《皮肤性病诊疗学杂志》【年(卷),期】2018(025)003【摘要】目的:建立准确、快速鉴定红色毛癣菌、指(趾)间毛癣菌、犬小孢子菌、堇色毛癣菌等4种常见皮肤癣菌的高分辨率溶解曲线(HRM)的方法.方法:根据目的基因序列及参考文献合成基因扩增引物,应用4HRM方法鉴定4种常见皮肤癣菌,并利用rDNA ITS测序验证其准确性.结果:4种皮肤癣菌表现出不同的HRM曲线及Tm值,后续rDNA ITS测序证实了HRM溶解曲线鉴别不同种皮肤癣菌的准确性.结论:本研究采用PCR-HRM分析方法,获得4个常见皮肤癣菌的不同溶解曲线,可用于临床该类皮肤癣菌感染的初步鉴定.【总页数】5页(P123-127)【作者】刘红芳;吴宜泉;刘应辉;谢振谋;陈阳霞;黄进梅;曾维英【作者单位】南方医科大学皮肤病医院,广东广州510091;南方医科大学皮肤病医院,广东广州510091;南方医科大学皮肤病医院,广东广州510091;南方医科大学皮肤病医院,广东广州510091;南方医科大学皮肤病医院,广东广州510091;南方医科大学皮肤病医院,广东广州510091;南方医科大学皮肤病医院,广东广州510091【正文语种】中文【中图分类】R756【相关文献】1.聚合酶链反应-高分辨率溶解曲线技术在常见沙门菌分型中的应用研究 [J], 盛翔宇;张智杰;薛文成;周连庆;梁雪妮;刘蒙蒙;孟冬娅2.应用荧光定量PCR-探针熔解曲线法快速鉴定分枝杆菌菌种方法的建立及初步评价 [J], 张俊仙;王杰;孙伟民;梁艳;阳幼荣;王兰;殷铭俊;吴雪琼3.基于高分辨率溶解曲线分析鉴别食品中的3种李斯特氏菌 [J], 岳苑;周梦诗;徐娟;李睿;何利华;赵飞;张建中;龚杰4.高分辨率熔解曲线分析技术检测 EGFR 基因突变方法的建立及其初步临床应用[J], 王卓;井昶雯;曹海霞;马蓉;吴建中5.高分辨率熔解曲线分析技术检测BRAF基因V600E突变方法的建立及初步临床应用 [J], 汤俊明;刘奇;王学才;乔国洪因版权原因，仅展示原文概要，查看原文内容请购买。

文章编号 : 1007 - 8738 (2003) 02 - 109 - 03活体染料 CFDA 2SE 在淋巴细胞增殖研究中的应用肇静娴 , 曾耀英 , 何贤辉 , 王 南 , 狄静芳 , 曾 山 (暨南大学组织移植与免疫中心教育部重点实验室 , 广东 广州 510632)Application of vital dye CFDA 2SE to study lymphocytic proliferationZHA O J ing 2xian , ZEN G Yao 2ying , HE Xian 2hui , W A N G N an , D I J in g 2f a n g , ZEN G S hanKey Laborotary of Ministry of Education for Tissue Transplantation and Immu nolog y , Jinan University , Gu angzhou 510632 , C hinaAb stractAIM : To explore the application value of vital d ye C FDA 2SE to study of lymphocytic proliferation. ME T HODS : C FDA 2SE staining , fluorescence antibod y labeling , flow cytometry and related software were used to detect the fluorescence intensity and analysis the pro 2 liferation kinetics of lymphocytes and their subsets after stimulation with polyclonal stimulators. RE SULT S : Lymphocytes divided after stimulation of PDB + ionomycin or C onA for 48 h , manifesting the serial halving of fluorescence intensity. CsA inhibited the prolifera 2 tive effect of ConA on lymphocyte s and no CFSE fluore scence halving were seen. Proliferation of C D4 + T cells and CD8 + T cells were asynchronous after ConA stimulation for 48 h , which becam e more obvious at the time of 72 h. Proliferation 2relate d index s got ten from ModFit TM software sho wed that the prolifera 2 tive effect of ConA on C D8 + T cells was stronger than that on CD4 + T cells. CONCL USIO N : CFDA 2SE staining combined with fluore scent antibody labelin g and cytometry wer e powerful tools for analysis of lymphocytic proliferation. K eywords : CFDA 2SE ; lymphocyte ; proliferation摘要目的 : 探讨活体染料 CFDA 2SE 在淋巴细胞增殖研究中的应用价值 。

中性粒细胞相关实验方法常用中性粒细胞分离方法（外周血、骨髓提取均可）（一）Percoll非连续密度梯度离心法（张灿老师课题组使用方法）优点：Percoll的主要成分是硅石胶，对中性粒细胞的化成成分和活性无影响。

回收率高，存活率高。

缺点：可能会有部分红细胞分离不干净，影响不大。

（二）Ficoll-Hypaque密度梯度离心法优点：回收率高和percoll差不多。

缺点：由于Ficoll结构中的长链烃组成具有LPS样作用，因此在分离过程中，会对中性粒细胞有激活作用。

（三）Dextran作用下红细胞自然沉降法优点：能够完全分离红细胞缺点：回收率最低（四）裂解红细胞法优点：能够完全分离红细胞缺点：回收率低纯度、回收率和存活率检测方法纯度：瑞吉染色存活：台盼蓝计数回收：分离后（计数）/分离前（血常规检测）Percoll非连续密度梯度离心法（张灿老师实验室的方法）和培养备注：使用外周血或骨髓提取都是可以的，一般来说，外周血每1ml能够提取1*10^6 cell，数量比较少，如果骨髓提取，一只小鼠约能提取1*10^7 cell。

外周血和骨髓提取除了来源不一样，分离方式是相同的。

1.试剂耗材：percoll原液（pharmacia or sigma）10*PBS RPIM1640培养基2.溶液配制（1）用percoll原液和10*PBS按照9:1的比例（v/v）配成混合液，定义为100%percoll。

（2）用1*PBS和100%percoll 配置55%和65%的percoll。

（溶液配制均在无菌环境下操作）3.分离步骤（1）小鼠酒精浸泡消毒。

（2）小鼠颈椎脱臼处死，立即切下其后肢的胫骨和股骨，并分离除去所有组织、皮肤。

将胫骨和股骨浸泡在不含有血清的RPIM1640培养基中。

（3）剪短胫骨股骨两端，用1ml注射器想胫骨股骨中吹灌不含有血清的RPIM1640培养基重悬得到骨髓细胞重悬液，一直吹到骨片泛白为止。

（4）将含有骨细胞的RPIM1640培养基4000rpm离心3分钟。

非致病性分枝杆菌多糖促红系祖细胞生长的研究
胡丽华;谢晓宝;李崇渔
【期刊名称】《中华生物医学工程杂志》
【年(卷),期】1996(000)004
【摘要】使用无血清培养体系观察非致病性分枝杆菌多糖(MPS)对正常人红系祖细胞CFU—E形成的作用MPS及MPS与rhIL-3瑕台呈浓度依赖性促CFU—E形成，而MPS与rhGM—csF联合，则降低后者的CFU—E产率．结论：单一MPS 以及MPs与rhIL-3联合能有效促进正常人CFU—E形成．
【总页数】1页(P269)
【作者】胡丽华;谢晓宝;李崇渔
【作者单位】常州市第一人民医院血液科，常州213003;同济医科大学协和医院输血科，武汉430022;同济医科大学血液病学研究所，武汉430022
【正文语种】中文
【中图分类】R378
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1.非结核分枝杆菌及其致病性的研究进展 [J], 钱爱东;陈菲菲;王春芳
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3.贝达喹啉、氯法齐明和德拉马尼对常见致病性非结核分枝杆菌体外抑菌活性及耐药机制的研究进展 [J], 孙晴;黄海荣;王桂荣
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5.分枝杆菌多糖促人LAK细胞增殖及对喉癌HEP－2细胞杀伤活性的研究 [J], 王津津;诸小侬;陈靖;陈仁;韩德民
因版权原因，仅展示原文概要，查看原文内容请购买。