基质金属蛋白酶在牙周病发展中的作用

基质金属蛋白酶(Matrix Metalloproteinases,MMP)是一组含Zn2+的能够降解细胞外基质的蛋白酶,通常在中性条件下发挥活性,有Ca2+参与时活性最大,本文就MMPs与牙周炎关系的研究进展综述如下。     

基质金属蛋白酶在骨巨细胞瘤中的研究现状

骨巨细胞瘤(Giant cell tumor of bone,GCT)是骨的良性肿瘤,但具有局部高侵袭性、高复发率,甚至肺转移,在WHO新分类中被描述为"侵袭性的潜在恶性病变".目前尚无确切的组织学指标能反映其生物学行为,随着对基质金属蛋白酶(matrix metalloproteinase,MMP)的结构、功能、表达...     

人牙髓中MMP-2与MMP-9受正畸力作用影响的初步分析

目的：采用免疫组织化学方法,研究接受正畸力作用影响的人牙髓中MMP-2和MMP-9的表达。方法：选取接受正畸治疗的患者10名,于正畸治疗前确定应拔除的正畸牙,对其一侧选用常规正畸加力,另一侧健康同名牙不施加任何正畸力,作为同源对照,加力1d后至7d内拔除该正畸牙,各20颗,共40颗,分为加力组和对照组;选取临床诊断有牙髓炎症且无保留价值的第3磨牙20例,分为炎症组;对标本进行处理后制成切片,采用SP法,对其中MMP-2和MMP-9的表达进行图像分析和半定量分析。结果：对照组、加力组和炎症组牙髓均可见MMP-2和MMP-9的表达;在接受正畸力的牙髓组织,成牙本质细胞和牙髓成纤维细胞可见MMP-2和MMP-9表达,加力组牙髓中两者为表达增强,并且其表达强于同源对照正常的牙髓,但弱于炎症牙髓,三组差异具有统计学意义（P〈0.05）。结论：MMP-2和MMP-9在人牙髓中主要表达于成牙本质细胞和牙髓成纤维细胞的胞质中;生理条件下两者的水平较低,在接受正畸治疗时,由于受正畸力影响,牙髓处于应激状态,两者表达增强,应引起口腔医师的高度重视。     

金属基座对微带天线特性的影响

针对放置于柱形金属基座的普通圆极化微带天线,利用HFSS仿真分析了金属基座厚度对天线的驻波、增益、轴比等特性的影响,结果表明柱形基座的厚度变化不会对驻波产生显著影响,对增益会产生一定影响.但对轴比会产生比较显著的影响,通过选择合适的基座厚度可以在一定程度上改善天线的增益特性和轴比特性,同时进行了实验验证,该结果可以为实际设计微带天线提供参考依据.     

美托洛尔对舒张性心力衰竭兔神经内分泌系统的影响

目的研究美托洛尔对舒张性心力衰竭兔神经内分泌系统的影响。方法雄性新西兰兔30只随机分为3组：手术组在右侧肾动脉上1cm处行腹主动脉缩窄术;手术治疗组从术后第1天起应用美托洛尔治疗;假手术组作为对照组。术后观察心衰的临床表现,定期复查超声心动图,并监测全身和心肌局部AngⅡ、ET-1、NE和NT—proBNP变化。结果手术治疗组的心衰发生率明显低于手术组,心室结构和功能达到显著改善,血清AngⅡ（25．57vs38．16,P〈0．01）、ET-1（21．14vs35．96,P〈0．01）和血清与心肌NE（97．90vs128．51,P〈0．01;11．77vs17．28,P〈0．05）、NT—proBNP（221．92vs305．76,P〈0．01;24．33vs30．53,P〈0．05）显著降低。结论美托洛尔可有效抑制DHF兔的全身和心肌局部神经内分泌系统激活.     

相对湿度对AFM针尖阳极氧化金属薄膜的影响

AFM针尖诱导氧化加工的金属(Ti、Al、Nb等)纳米氧化线是实现金属-半导体纳米器件的基础，由大气湿度决定的金属膜表面水吸附层的厚度，对控制阳极诱导氧化加工的结果起重要作用。实验研究了大气湿度对Ti氧化线高度、宽度和纵横比的影响，结果表明进行氧化加工Ti膜的较好的湿度范围为30％～50％。     

超短波对兔牙移动影响的超微结构研究

本文采用超短波作用于兔牙上,并设立对照组,通过透射电镜观察其对牙周组织细胞的影响。结果发现,超短波可增加牙槽骨张力侧的成骨细胞及压力侧的破骨细胞量,但两组参与改建的细胞超微结构无显著性差异。作者认为,超短波能加快牙移动速度,且对组织细胞无不良影响。     

半导体激光血管内照射对健康兔红细胞变形能力的影响

本研究以健康兔为对象,随机分为照射组和对照组,用半导体激光（波长650nm）进行血管内照射,采用新的激光衍射法,用红细胞变形仪进行检测红细胞变形指数,研究半导体激光血管内照射对红细胞变形能力的影响。结果表明：半导体激光血管内照射能改善红细胞膜的粘弹性,有利于提高红细胞的变形能力。这从另一角度证明弱激光血管内照射能降低血粘度,改善微循环。     

基于行列式随机循环的压缩感知测量矩阵研究

压缩感知理论,从信号的自身特性出发,通过变换作用域和线性投影实现对信号的采样和压缩。测量矩阵是该理论中获得最优测量,实现精确重构的关键。本文在介绍常用测量矩阵的基础上,重点研究了结构化测量矩阵。鉴于测量矩阵设计的最重要的原则是降低矩阵元素间的相干性,本文借鉴循环矩阵和广义轮换矩阵的优点,提出了采用均匀随机数对结构化测量矩阵进行随机循环的构造方法。仿真实验表明新矩阵在信号重建上具有更好的性能。     

光轴任意取向单轴晶体的非正入射工作状态：非正交Jones矩阵

当光线斜入射到光轴任意取向的单轴晶体上时，采用ｏ，ｅ两光线的光矢量本征振动方向为一组非正交基矢。在这组特殊基矢上建立了Ｊｏｎｅｓ矩阵，得到了单轴晶体光学传输特性的较为严格的描述。     

矩阵理论在图形变换中的应用

基于给定的各种三维物体模型,研究这些模型进行平移、旋转、缩放等变换的理论依据是什么,其中要借助线性代数中的矩阵理论来进行分析,为此矩阵理论是研究此问题的数学基础.     

Some empirical advances in matrix completion

Solving the matrix completion problem via rank minimization is NP hard. Recent studies have shown that this problem can be addressed as a convex nuclear-norm minimization problem, albeit at an increase in the required number of samples. This paper proposes a non-convex optimization problem (a variant of convex nuclear-norm minimization) for the solution of matrix completion. It also develops a fast numerical algorithm to solve the optimization. This empirical study shows that significant improvement can be achieved by the proposed method compared to the previous ones.The number of required samples is also dependent on the type of sampling scheme used. This work shows that blue-noise sampling schemes yield more accurate matrix completion results compared to the popular uniform random sampling.     

用矩阵形式的电路方程分析多层特斯拉线圈

论文引介一种用解析几何原理分析有载二端口网络主要电气量与负载关系的方法。根据二端口网络解析表达式和复变函数映射原理，在复平面绘制一张几何图形。当负载阻抗等参数改变时，会引起该图形某些线段与圆弧的变化，从而直观地观察二端口网络主要电气量的联动变化趋势。该方法具有直观、全局和动态的特点，可以促进解析几何与复变函数在电路分析中的应用。     

神经网络与Zernike矩在字符识别中的应用研究

本文介绍了Zernike矩的理论,并将其与神经网络相结合,运用于字符图形的识别中去.并从理论和实验两个方面证实Zernike矩的识别效果优于空间几何矩.     

Underdetermined blind separation of non-disjoint signals in time-frequency domain based on matrix diagonalization

To estimate precisely the mixing matrix and extract the source signals in underdetermined case is a challenging problem, especially when the source signals are non-disjointed in time-frequency (TF) domain. The conventional algorithms such as subspace-based achieve blind source separation exploiting the sparsity of the original signals and the mixtures must satisfy the assumption that the number of sources that contribute their energy at any TF point is strictly less than that of sensors. This paper proposes a new method considering the uncorrelated property of the sources in the practical field which relaxes the sparsity condition of sources in TF domain. The method shows that the number of the sources that exist in any TF neighborhood simultaneously equals to that of sensors. We can identify the active sources and estimate their corresponding TF values in any TF neighborhood by matrix diagonalization. Moreover, this paper proposes a method for estimating the mixing matrix by classifying the eigenvectors corresponded to the single source TF neighborhoods. The simulation results show the proposed algorithm separates the sources with higher signal-to-interference ratio compared to other conventional algorithms.     

Bax基因在人颈动脉粥样硬化斑块中的表达

目的研究Bax基因在稳定和不稳定粥样斑块中的表达及临床意义。方法颈动脉内膜剥脱术标本25例,由病理学分成稳定性(14例)和不稳定性(11例)两组,对照组正常动脉取自肝移植供者的腹主动脉及其分支(6例);进行免疫组化,原位杂交和原位凋亡DNA缺口末端标记法(TUNEL)测定Bax凋亡基因表达。结果稳定性斑块Bax阳性表达免疫组化5例,原位杂交5例,TUNEL阳性4例;不稳定性斑块Bax阳性表达免疫组化10例,原位杂交11例,TUNEL阳性表达9例,表达显著高于稳定性斑块(P<0.01);免疫组化和原位杂交阳性细胞半定量计数在稳定性斑块中分别为8.63±2.62和10.32±3.12,在不稳定性斑块分别为122±21.64和152±23.35,高于稳定性斑块(P<0.01);对照组无表达。结论Bax高表达是影响粥样斑块稳定性的分子病理学基础和脑卒中发生率的因素之一,在不同时期控制其表达可为基因治疗颈动脉粥样硬化提供靶点。     

Projected gradient descent based on soft thresholding in matrix completion

Matrix completion is the extension of compressed sensing. In compressed sensing, we solve the underdetermined equations using sparsity prior of the unknown signals. However, in matrix com- pletion, we solve the underdetermined equations based on sparsity prior in singular values set of the unknown matrix, which also calls low-rank prior of the unknown matrix. This paper firstly introduces basic concept of matrix completion, analyses the matrix suitably used in matrix completion, and shows that such matrix should satisfy two conditions： low rank and incoherence property. Then the paper provides three reconstruction algorithms commonly used in matrix completion： singular value thresholding algorithm, singular value projection, and atomic decomposition for minimum rank ap- proximation, puts forward their shortcoming to know the rank of original matrix. The Projected Gradient Descent based on Soft Thresholding （STPGD）, proposed in this paper predicts the rank of unknown matrix using soft thresholding, and iteratives based on projected gradient descent, thus it could estimate the rank of unknown matrix exactly with low computational complexity, this is verified by numerical experiments. We also analyze the convergence and computational complexity of the STPGD algorithm, point out this algorithm is guaranteed to converge, and analyse the number of it- erations needed to reach reconstruction error. Compared the computational complexity of the STPGD algorithm to other algorithms, we draw the conclusion that the STPGD algorithm not only reduces the computational complexity, but also improves the precision of the reconstruction solution.