三种肿瘤标准物在食管癌早期诊断中的价值

目的:探讨血清肿瘤标记物癌胚抗原(CEA)、神经元特异性烯醇化酶(NSE)、细胞角蛋白19片段抗原(CY-FRA21-1)联合检测在食管癌早期诊断中的应用价值,旨在为食管癌的诊治提供理论参考.方法:采用酶联免疫法(ELISA)测定67例食管癌患者、60例正常健康者的三种肿瘤标志物(CEA、NSE、CYFRA21-1)水平.结果:食管癌组3种血清标志物的水平显著高于对照组(P<0.05);CEA、NSE、CYFRA21-1在食管癌诊断中的均具有较高的特异性,但敏感性均较低.而3种肿瘤标志物联合检测在食管癌诊断中有较高的敏感性和特异性,分别为74.63%和85.07%.结论:血清3种项肿瘤标志物(CEA、NSE、CYFRA21-1)联合检测可以提高食管癌诊断的敏感性,对食管癌的早期诊断和鉴别具有重要的临床价值.     

一个肿瘤侵入模型的定性分析

本文研究由Gatenby和Gawlinski提出的一个肿瘤侵入模型.该模型是一个强耦合的退缩型反应扩散方程组.本文在α12为零,0≤α21＜1的情况下,对该模型进行严格的数学分析.所获结果包括两个方面:(1)解的整体存在性.主要应用了逼近方法,H.Amann关于一般拟线性方程和这类方程与常微分方程耦合而成的广义抛物型方程组解的存在性理论,以及积分估计技术.如何建立解的积分估计是获得这个问题解的整体存在性的关键. (2)解的渐近性态.该模型有EP1,EP2,EP3和EP4四个稳态解,其中EP1和EP2两个平凡稳态解在任何情况下都不稳定.通过构造Lyapunov函数,我们证明了,在一定条件下EP3全局渐近稳定,从而时变解在时间趋于无穷时将趋于EP3,而在相反的条件下EP4全局渐近稳定,从而时变解在时间趋于无穷时将趋于EP4     

Analysis of a Free Boundary Problem Modeling Multi- Layer Tumor Growth in Presence of Inhibitor

In this paper we study well-posedness and asymptotic behavior of solution of a free boundary problem modeling the growth of multi-layer tumors under the action of an external inhibitor. We first prove that this problem is locally well-posed in little Holder spaces. Next we investigate asymptotic behavior of the solution. By making delicate analysis of spectrum of the linearization of the stationary free boundary problem and using the linearized stability theorem, we prove that if the surface tension coefficient γ is larger than γ^＊ 〉 0 the fiat stationary solution is asymptotically stable provided that the constant c representing the ratio between the nutrient diffusion time and the tumor-cell doubling time is sufficient small.     

Adhesion behavior of endothelial progenitor cells to endothelial cells in simple shear flow

The adhesion of endothelial progenitor cells(EPCs) on endothelial cells(ECs) is one of the critical physiological processes for the regenesis of vascular vessels and the prevention of serious cardiovascular diseases.Here,the rolling and adhesion behavior of EPCs on ECs was studied numerically.A two-dimensional numerical model was developed based on the immersed boundary method for simulating the rolling and adhesion of cells in a channel flow.The binding force arising from the catch bond of a receptor and ligand pair was modeled with stochastic Monte Carlo method and Hookean spring model.The effect of tumor necrosis factor alpha(TNF-α) on the expression of the number of adhesion molecules in ECs was analyzed experimentally.A flow chamber system with CCD camera was set up to observe the top view of the rolling of EPCs on the substrate cultivated with ECs.Numerical results prove that the adhesion of EPC on ECs is closely related to membrane stiff-ness of the cell and shear rate of the flow.It also suggests that the adhesion force between EPC and EC by P-selectin glycoprotein ligand-1 only is not strong enough to bond the cell onto vessel walls unless contributions of other catch bond are considered.Experimental results demonstrate that TNF-α enhanced the expressions of VCAM,ICAM,P-selectin and E-selectin in ECs,which supports the numerical results that the rolling velocity of EPC on TNF-α treated EC substrate decreases obviously compared with its velocity on the untreated one.It is found that because the adhesion is affected by both the rolling velocity and the deformability of the cell,an optimal stiffness of EPC may exist at a given shear rate of flow for achieving maximum adhesion rates.     

基于遗传算法-支持向量机的兔肝VX2肿瘤光谱鉴别

兔肝VX２肿瘤是一种快速生长的肿瘤模型,可以在多种器官如肝、肺、直肠等快速生长,常用于肿瘤研究。采用可见-近红外高光谱技术对四只兔子的兔肝VX２肿瘤和正常组织进行活体和离体的反射光谱检测,然后采用支持向量机分别实现了二分类(正常肝组织和肝VX2肿瘤组织)和四分类(未出血活体正常肝组织、未出血活体VX2肿瘤组织、出血离体正常肝组织和出血离体肝VX2肿瘤组织)。根据其光谱反射曲线的特征,选择了400～1 800 nm区间的数据为特征变量。为进一步提高分类准确率,分别采用5折交叉验证和遗传算法对支持向量机的核函数参数g和惩罚因子c进行了优化。其中5折交叉验证优化参数和分类结果为：二分类优化的惩罚参数c为4,核函数参数g为0.125 0,其校正集和预测集的准确率都达到了100%;四分类中优化出的参数c为8,g为0.121 1,其校正集和预测集的准确率分别达到了99.242 4%和93.333%。遗传算法优化参数和结果为：二分类中优化的参数c为0.845 6,g为0.062 5,其校正集和预测集的准确率同样都达到了100%;四分类中优化的参数c为5.5307,g为0.068 5,其校正集和预测集的准确率分别达到了99.242 4%和100%。结果显示两种优化方法都取得了很好的效果,遗传算法优化参数对四分类的分类更为精确。为进一步提升算法速度,采用间隔选取变量的方法来不断减少特征变量,最终每隔100 nm谱段选择一个变量,共选择14个谱段作为特征变量。采用遗传算法优化支持向量机参数并对其分类进行了研究,结果表明：二分类和四分类的校正集和预测集结果准确率均为99.242 4%,而且运行时间分别为11.4和20.0 s, 与选择全波段的运行时间：340.3和491.0 s相比, 说明多光谱技术可以进行肝VX2肿瘤组织和正常肝组织的鉴别,且分类准确率可达99%以上,而且运行时间缩短了很多。为未来多光谱技术在未来临床肿瘤诊断中实现肿瘤组织的快速实时在线检测和分类奠定了基础,显示出巨大的应用潜力。     

基于自适应核学习相关向量机的乳腺X线图像微钙化点簇处理方法研究

采用自适应核学习相关向量机方法, 结合形态学滤波和Kallergi分簇标准, 研究了乳腺X线图像中微钙化点簇的处理. 首先将微钙化点检测看作一个监督学习问题, 然后应用自适应核学习相关向量机作为分类器判断图像中每一个位置是否为微钙化点并采用形态学处理滤除干扰噪声, 最后对获得的微钙化点采用Kallergi标准进行分簇. 为提高运算速度, 在微钙化点检测时将整个图像分解为多个子图像并行运算, 实现了一种基于自适应核学习相关向量机的微钙化点簇快速处理方法. 实验结果和分析表明, 自适应核学习相关向量机方法算法性能优于相关向量机方法, 特别是实现的快速方法能进一步降低微钙化点簇的处理时间. 关键词： 乳腺X线图像 微钙化点簇 相关向量机 自适应核学习     

噻胺酮麻醉剂对鼠S180肿瘤31P MRS的影响

对实验动物肿瘤进行活体³¹P MRS研究首要的是有效地固定动物.本文初步研究了用噻胺酮麻醉后的小鼠S180肿瘤在麻醉过程中³¹P MRS随时间的变异性.研究发现噻胺酮是一个安全系数高、起效快、麻醉过程适宜且对肿瘤的³¹P MRS无显著影响的麻醉药.因而噻胺酮适用于连续测定³¹P MRS的需要.     

中红外光纤技术用于腮腺肿瘤诊断的研究

采用傅里叶变换红外光谱法与中红外光导纤维联用技术对１１例肿瘤，７例正常腮腺和１例舍格伦综合症的红外光谱进行了对比研究。结果发现正常腮腺和舍格伦综合症的红外光谱很相似，而与肿瘤的光谱存在着明显差别，同时也观察到良性与恶性肿瘤的光谱在若干波段处也有所不同．     

一个关于肿瘤治疗的自由边界问题的数学分析

§1Introduction Avarietyofpartialdifferentialequationmodelsfortumorgrowthortherapyhave beendevelopedinthelastthreedecades[see2,3,16-18,21-26].Mostofthosemodelsare informoffreeboundaryproblems,andareverydiversified.Rigorousmathematical analysisofsuchfreeboundaryproblemshasdrawngreatinterest,andmanyinteresting resultshavebeenestablished[4-15].Inthispaperwedealwithamathematicalmodeldescribingtumorchemotherapy.In thismodelthetumorisviewedasdenselypacked,radially-symmetricsphereofradiusR(t)contain…