鸭血烯酸对艾氏癌生长的抑制作用

鸭血烯酸是由鸭血清中提取的不饱和脂肪酸．在体外实验中具有使艾氏腹水癌细胞膨胀失活的作用．用于治疗艾氏癌患鼠,可抑制其腹水癌和实体瘤的生长．与环磷酰胺（CPA）或氟脲嘧啶（SFU）相比,鸭血烯酸的毒性较低,疗效较高,约20％～40％被治愈的患鼠,可长期存活．     

吡柔比星（吡喃阿霉素）联合化疗治疗恶性淋巴瘤40例分析

观察吡喃阿霉素联合化疗方案治疗恶性淋巴瘤的疗效及毒副反应。方法;对４０例恶性淋巴瘤患者行ＴＨＰ联合化疗,其中６例为霍奇金病,３４例为非霍奇金淋巴瘤。采用ＣＴＯＰ或ＣＴＯＰＥ方案,ＴＨＰ疗程量为６０ｍｇ。ＣＴＯＰＥ方案主要用于病变播散或高度恶性淋巴瘤患者。     

电离辐射引发细胞凋亡的信号通路

电离辐射诱发细胞产生凋亡与细胞的辐射敏感性有关，而辐射的生物学效应则因其引发细胞凋亡的信号通路不同而有差异。辐射诱发凋亡作用过程至少包括SAPK／JNK信号通路及依赖于DNA损伤、依赖于胞质电离损伤和依赖于质膜损伤的四种信号通路。本文就辐射诱发细胞凋亡的信号传导途径进行简介。     

人tumstatin基因的克隆、表达和抗体制备

应用PCR技术从人胎肺cDNA文库中扩增tumstatin基因编码序列,克隆至pET-3c载体构建非融合表达的重组质粒pET-3c-tum,并在大肠杆菌E.coli BL21(DE3)中获得高效表达.表达蛋白经SDS-聚丙烯酰胺凝胶电泳(SDS-PAGE)分离、切胶回收后免疫新西兰大白兔,获得ELISA效价高达1∶1 000的特异性兔抗人tumstatin抗血清.     

慢性充血性心力衰竭过程中的肿瘤坏死因子及其受体

慢性充血性心力衰竭病人血清中TNFα水平升高，当其≥10^-8mol/L时，可能作为内分泌激素，通过与其受体(膜结合型及可溶型)结合，直接损伤心肌纤维，影响心肌细胞凋亡过程，引起或促进心功能不全的发生。TNF途径成为充血心衰发病机制中的新内容。可考虑应用TNFr拮杭剂治疗心衰。     

活菌作为抗肿瘤制剂和肿瘤基因治疗载体的研究

随着细菌生物学和分子生物学的发展，细菌抗癌治疗的应用更为广泛，其可增加化疗药物的敏感性，增强抗癌药物作用，并作为基因治疗的载体，细菌毒素本身就可以用来攻克肿瘤，而最有应用前景的是，经遗传修饰的细菌作为自杀基因载体选择性地破坏肿瘤细胞，保护正常组织不受损坏。文章就活菌作为抗肿瘤制剂和肿瘤基因治疗栽体的研究进展进行综述。     

透明质酸在肿瘤新血管生成中的作用

阐述了透明质酸寡聚糖对上皮细胞作用的过程，即从与细胞表面受体结合到激活信号传导途径，以及表达成蛋白质进行细胞增生和转移。     

循证医学对肿瘤临床实践的指导意义

介绍循证医学产生的背景及其对肿瘤临床的实践意义，肿瘤学循证医学文献检索的几种主要的数据库。     

Advances in identification and application of tumor antigen inducing anti-cancer responses

Tumor antigen is one of the important bases of tumor immunotherapy . With the discovery of novel tumor antigens, interest in specific immunotherapy for treatment of malignancies has increased substantially. Nowadays more and more scientists paid close attention to various tumor antigens with their roles or/and applications in anti-cancer immune responses, immune tolerance, tumor markers,     

Classification of Medical Brain Images

Since brain tumors endanger people‘s living quality and even their lives, the accuracy of classification becomes more important. Conventional classifying techniques are used to deal with thosedatasets with characters and numbers. It is difficult, however, to apply them to datasets that include brain images and medical history (alphanumeric data), especially to guarantee the accuracy.For these datasets, this paper combines the knowledge of medical field and improves the traditional decision tree. The new classification algorithm with the direction of the medical knowledge not only adds the interaction with the doctors, but also enhances the quality of classification. The algorithm has been used on real brain CT images and a precious rule has been gained from the experiments. This oaoer shows that the ahzorithm works well for real CT data.