抗氧化修饰低密度脂蛋白单克隆抗体的制备及其初步应用

用氧化修饰脂蛋白（ａ）对Ｂａｌｂ／ｃ小鼠免疫．利用淋巴细胞杂交瘤技术制备了鼠抗人氧化修饰低密度脂蛋白（ｏｘｉｄａｔｉｖｅｌｙｍｏｄｉｆｉｅｄｌｏｗｄｅｎｓｉｔｙｌｉｐｏｐｒｏｔｅｉｎ，ｏｘＬＤＬ）单克隆抗体细胞株．以单克隆抗体包被建立了酶联免疫吸附（ＥＬＩＳＡ）双抗夹心法．用此法对１０例冠心病患者、６例其他心脏病患者、１０例正常健康人血浆中ｏｘＬＤＬ的含量进行了测定．结果表明，冠心病患者血浆中ｏｘＬＤＬ水平明显高于其他心脏病组和正常对照组．本实验所建立的方法对诊断冠心病患者血浆中的ｏｘＬＤＬ具有重要意义     

基于人工免疫的新型入侵检测系统研究

分析研究了人工免疫原理在网络入侵检测中应用的可行性,结合人工免疫模型和数据挖掘技术建立了一个网络入侵检测系统模型。对抗体生成过程中的关键算法进行了描述。为克服在抗体生成阶段由于采用遗传算子导致时空效率不佳的缺陷,将数据流分割成字符串集合,根据数理统计原理,讨论了分割参数和检测器数目的选定,使它在通用性、鲁棒性上具有优势。     

基于免疫算法和神经网络的新型抗体网络

构建了基于免疫算法和神经网络的新型抗体网络入侵检测系统,系统与网络入侵检测功能相结合,应用于大型网络的入侵检测任务,具有良好的可扩充性;重点讨论了新型抗体网络原理,引进BP神经网络自学习能力,对已有的抗体网络模型进行改进;通过对网络数据集的测试表明,该算法相对于传统抗体网络,其检测效率得到了明显的改善。     

小鹅瘟病毒荧光抗体试验的建立与应用

将小鹅瘟病毒(GPV)分离毒接种成年健康家兔,获得兔抗GPV高免血清,由此制备兔抗GPV荧光抗体.采用直接荧光抗体试验对人工感染鹅胚、雏鹅及自然病例进行检测.结果表明:该方法可以用于病毒抗原的检测,快速准确且肠的含毒量高于肝脏.     

CagA阳性幽门螺杆菌感染与消化性溃疡、胃炎相关性512例临床分析

目的：探讨CagA阳性Hp感染与消化性溃疡、胃炎等胃及十二指肠疾病的关系.方法采用ELISA法对Hp阳性(13 C-呼气试验为阳性)、胃黏膜快速尿素酶联免疫法阳性的512例胃十二指肠疾病患者及80例对照者(健康体检：13 C-呼气试验为阴性、胃黏膜快速尿素酶联免疫法阴性)行血清CagA抗体检测.512例胃十二指肠疾病患者中慢性浅表性胃炎(CSG)184例,慢性萎缩性胃炎(CAG)120例,十二指肠球溃疡(DU)100例,胃溃疡(GU)108例.结果 CagA抗体阳性检出率对照组为30%,慢性浅表性胃炎组阳性率为61.96%,慢性萎缩性胃炎组阳性率为63.33,十二指肠溃疡组阳性率为68.00%,胃溃疡组阳性率为74.07%.胃十二指肠疾病患者CagA阳性总检出率为66.02%,与对照组比较,差异具有统计学意义(P<0.05).结论胃十二指肠疾病Hp阳性感染者中CagA抗体阳性总检出率明显高于对照组,提示CagA抗体阳性感染与胃十二指肠疾病密切相关;两组胃炎患者CagA抗体阳性检出率明显高于对照组,提示CagA抗体阳性感染与胃炎密切相关;胃十二指肠溃疡患者CagA抗体阳性检出率明显高于对照组,提示CagA抗体阳性感染与消化性溃疡密切相关.     

基因工程单链抗体及其应用分析

在基因工程理论基础上,对单链抗体基因的获取、构建、表达及其在医疗方面的应用进行了分析,为单链抗体在食品、农业等领域的应用奠定理论基础。     

Independence and Dependence in Aging

No abstract available for this article.     

受人工免疫启发的脚本病毒检测模型

为了检测日益增多的脚本病毒变种,提出了一种基于人工免疫原理的脚本病毒检测模型。该模型借鉴了人工免疫的自体耐受和克隆选择机制,将脚本代码提呈为抗原,用抗体模拟病毒检测环境下的检测器,按照免疫学习机制对抗体进行分类,模拟了否定选择算法,避免抗体识别正常抗原,利用抗体的自学习机制发现有害的变种抗原,通过对成熟抗体和记忆抗体进行演化,建立了抗体的动态产生与淘汰机制,从而降低误检率。仿真实验表明,该模型能有效检测脚本病毒变种,为脚本病毒的检测提供了一条新途径。     

Fitting Bayesian multiple random effects models

Bayesian random effects models may be fitted using Gibbs sampling, but the Gibbs sampler can be slow mixing due to what might be regarded as lack of model identifiability. This slow mixing substantially increases the number of iterations required during Gibbs sampling. We present an analysis of data on immunity after Rubella vaccinations which results in a slow-mixing Gibbs sampler. We show that this problem of slow mixing can be resolved by transforming the random effects and then, if desired, expressing their joint prior distribution as a sequence of univariate conditional distributions. The resulting analysis shows that the decline in antibodies after Rubella vaccination is relatively shallow compared to the decline in antibodies which has been shown after Hepatitis B vaccination.     

Estimation of conditional cumulative incidence functions under generalized semiparametric regression models with missing covariates,with application to analysis of biomarker correlates in vaccine trials

This article presents generalized semiparametric regression models for conditional cumulative incidence functions with competing risks data when covariates are missing by sampling design or happenstance. A doubly robust augmented inverse probability weighted (AIPW) complete-case approach to estimation and inference is investigated. This approach modifies IPW complete-case estimating equations by exploiting the key features in the relationship between the missing covariates and the phase-one data to improve efficiency. An iterative numerical procedure is derived to solve the nonlinear estimating equations. The asymptotic properties of the proposed estimators are established. A simulation study examining the finite-sample performances of the proposed estimators shows that the AIPW estimators are more efficient than the IPW estimators. The developed method is applied to the RV144 HIV-1 vaccine efficacy trial to investigate vaccine-induced IgG binding antibodies to HIV-1 as correlates of acquisition of HIV-1 infection while taking account of whether the HIV-1 sequences are near or far from the HIV-1 sequences represented in the vaccine construct.