中国豌豆根瘤侵入线的发育和特征

我们对中国张家川豌豆根瘤发育和衰老过程中的超微结构变化先后进行了详细观察,观察表明,这些根瘤中的侵入线IT与其他已报道的豌豆根瘤有许多不同之处。在此基础上,我们对此又进行了深入研究。现将结果简报如下:豆科根瘤通常是通过侵入线中细菌(B)的释放才能使寄主细胞得以侵染,才能具有固氮作用。因此,侵入线的发育和细菌释放一直是根瘤细胞生物学家深感兴趣的问题之一。因为它形成的快慢,多少、体积的大小及细菌释放速度直接与共生固氮有关,被认为是固氮的关键。     

大豆豆荚与叶片的生理生化及超微结构的关系

本研究运用宏观数据分析、生理指标测定、透射电镜技术,对东农42和东农163两个品种的大豆豆荚进行了研究,发现大豆豆荚发育过程中细胞结构的变化引起了其性质和功能的变化.在豆荚发育的初期,细胞器发育还不完整,细胞核、叶绿体排列紧密,细胞核核质均匀,叶绿体的基粒片层初步形成.随着豆荚进一步发育,其叶绿体充分发育,叶绿体中积累的光合产物增多,光合细胞的活力增强.当大豆豆荚发育成熟时,其液泡较成熟前更大,细胞器被挤到边缘,叶绿体的基粒片层完善,结构清晰.     

根瘤形成过程中刺槐根外层传递细胞的诱发和超微结构观察

通过对接种根瘤菌后的刺槐根段进行透射电镜观察，结果表明：加菌刺槐苗中发生形态变化的根段在不同时期（根毛密集形变、根段膨大、初期小瘤一直到成瘤）根外层细胞的外切向壁上可形成具壁内突的传递细胞。而未加根瘤菌的刺槐苗根段的外层细胞以及加菌但没有形态变化的刺槐功苗根段均未观察到表皮细胞中，也可产生于外皮细胞中，甚至于根毛细胞中。所取加菌刺槐苗形变根段的根外层细胞有些全部由传递细胞组成，有些为传递细胞与非传递细胞相间排列。传递细胞的发育最先是质膜向内突起形成囊状结构，然后细胞壁物质开始沉积，直至壁内突形成。     

大豆花芽分化和发育的扫描电子显微镜观察

以无限型开花大豆品种东农47（Glycine max（L.）Merr.cv.Dongnong47）为实验材料,对其花芽分化和发育的不同时期进行扫描电子显微镜（SEM）观察。实验结果表明大豆花芽分化分为4个主要时期：（1）花原基分化期、萼片原基分化期、花瓣原基和雄蕊雌蕊原基分化期、雄蕊雌蕊结构分化期;（2）大豆花的发育过程中不同轮花器官发育时间上的重叠现象,以及同轮上的同种花器官存在着发育时间及程度上的差异,不符合ABC模型理论;（3）花瓣的发育在早期迟缓,后期才迅速发育,直至高过雄蕊。     

泥螺卵子发生过程中高尔基复合体的变化

应用透射电子显微镜研究了泥螺（Bullacta exarata）卵子发生过程中高尔基复合体的数量和形态结构特点.结果表明,在泥螺卵子发生的四个时期即卵原细胞期、卵黄发生早期、卵黄发生中期和卵黄发生后期,卵母细胞内高尔基复合体经历了一系列的变化.卵原细胞内无典型的高尔基复合体,但具高尔基囊泡;卵黄发生早期,高尔基复合体发达,膜囊数达10多层;卵黄发生中期,高尔基复合体分泌活动加快,产生大量的大小囊泡,囊泡内充满颗粒状物质,最后演变成卵黄颗粒.随着卵母细胞的发育,卵黄颗粒的数量和直径逐渐增加;卵黄发生后期,高尔基复合体开始解体,数量减少.此外,对高尔基复合体在卵子形成过程中的功能、去向及行为变化等问题进行了讨论.     

四棱豆根瘤的结构与功能

四棱豆[Psophocarpus tetragonololbus(L)DC]为热带豆科固氮植物,根系发达结瘤多,用途广,具有较大经济价值。它原产亚洲热带地区,我国引种已有几十年历史。在过去偏重栽培管理及加工利用研究,对共生固氮的基础研究报道甚少。近年来我们开展热带固氮植物特性研究,已取得一些有意义的结果。本文简介四棱豆根瘤细胞结构与固氮功能关系方面的研究结果。一,共生结瘤特征:由接种豇豆族根瘤菌在四棱豆根部形成结瘤固氮。主根和侧根上都见有根瘤,尤其是侧根结瘤为多。当土壤缺水条件下影响结瘤生长数量减少。幼小瘤单生球状。伴随     

精子细胞发育过程中膜结构和核膜孔分布极性化的形态研究 冷冻蚀刻和双复型膜电镜技术

精子细胞变态分为四个时期,即高尔基期,头帽期,顶体期和成熟期,在发育过程中细胞的形态、结构和成分都发生明显的变化,Susi,F.R等研究了高尔基复合体衍化为顶体的过程,Clerment,Y.,党连凯等观察了内质网的形态变化。Friend,S.D.采用冷冻蚀刻技术研究成熟精子的膜极性特点和受精过程中膜结构的变     

冬枣果实韧皮部及其周围薄壁细胞的超微结构观察和功能分析

利用透射电镜技术,对发育过程中的冬枣果实韧皮部及周围薄壁细胞的超微结构进行了观察研究。结果表明,果实发育早期筛管伴胞复合体与周围薄壁细胞之间存在少量胞间连丝,发育中期胞间连丝数量有所增加,筛分子和伴胞间及韧皮薄壁细胞问存在丰富的胞间连丝,显示了从筛管伴胞复合体卸出到周围薄壁细胞的同化物的卸载路径可能发生了变化。果实发育的各个时期伴胞胞质致密,富含线粒体、内质网和高尔基体,液泡化程度不等;果实发育前期,筛分子伴胞复合体与邻近的薄壁细胞质膜存在囊泡结构,果实韧皮部薄壁细胞胞质中含有丰富的线粒体、内质网、高尔基体、多泡体和小囊泡,到后期线粒体开始降解,显示了伴随果实发育薄壁细胞内的物质代谢和运转功能经历了由活跃到下降的过程。     

大豆子叶细胞中变形质体的形成和发育过程

质体是植物细胞中特有的一种细胞器。原质体、白色体、叶绿体和有色体之间的发育有着密切的关系。变形质体是一类不规则形状的原质体,多呈哑铃形、马蹄形或杯状。前人曾在许多植物的多种组织中看到过变形质体。但是关于变形质体的作用和进一步发育趋势目前尚无一致的看法。本文采用常规透射电镜技术观察了大豆子叶细胞中变形质体的形成和发育途径。结果和讨论:开花后19天的大豆子叶细胞中有许多原质体。其中部分原质体呈圆球形(图1)。部分原质体呈哑铃形(图2)、马蹄形(图3)和环形。从三维空间进行分析,马蹄形质体是杯状质体的一个     

地椒叶腺毛发育的扫描电镜观察

利用扫描电子显微镜对地椒不同发育时期叶表面的腺毛进行了观察,结果表明:地椒叶的腺毛有两种类型,头状腺毛和盾状腺毛.头状腺毛由1个基细胞、1个柄细胞和1个头部分泌细胞组成;盾状腺毛由1个基细胞、1个柄细胞和12个头部分泌细胞组成,4个在中央,8个在边缘;两种腺毛均在芽中已经发育完成,发育过程中,头状腺毛几乎没有很大变化,...     

Black Pad Susceptibility of the Electroless Ni Films on the Cu UBM

The occurrence of black pad in the electroless Ni film during the immersion gold process is related to the surface morphology of the Ni(P) film. A nonuniform distribution of the nodule size and curvature is the crucial factor. Large nodules with small surface curvatures had higher P concentration and did not corrode, while small nodules with large surface curvatures had lower P concentration and corroded. Experiments using different types of Cu substrates suggest that the Ni(P) film black pad susceptibility increased with the defect density and/or the residual stress in the underlying substrate. Annealing the Cu substrate before the electroless Ni plating greatly reduced the black pad formation.     

On measuring the change in size of pulmonary nodules

The pulmonary nodule is the most common manifestation of lung cancer, the most deadly of all cancers. Most small pulmonary nodules are benign, however, and currently the growth rate of the nodule provides for one of the most accurate noninvasive methods of determining malignancy. In this paper, we present methods for measuring the change in nodule size from two computed tomography image scans recorded at different times; from this size change the growth rate may be established. The impact of partial voxels for small nodules is evaluated and isotropic resampling is shown to improve measurement accuracy. Methods for nodule location and sizing, pleural segmentation, adaptive thresholding, image registration, and knowledge-based shape matching are presented. The latter three techniques provide for a significant improvement in volume change measurement accuracy by considering both image scans simultaneously. Improvements in segmentation are evaluated by measuring volume changes in benign or slow growing nodules. In the analysis of 50 nodules, the variance in percent volume change was reduced from 11.54% to 9.35% (p = 0.03) through the use of registration, adaptive thresholding, and knowledge-based shape matching.     

Automated segmentation refinement of small lung nodules in CT scans by local shape analysis

One of the most important problems in the segmentation of lung nodules in CT imaging arises from possible attachments occurring between nodules and other lung structures, such as vessels or pleura. In this report, we address the problem of vessels attachments by proposing an automated correction method applied to an initial rough segmentation of the lung nodule. The method is based on a local shape analysis of the initial segmentation making use of 3-D geodesic distance map representations. The correction method has the advantage that it locally refines the nodule segmentation along recognized vessel attachments only, without modifying the nodule boundary elsewhere. The method was tested using a simple initial rough segmentation, obtained by a fixed image thresholding. The validation of the complete segmentation algorithm was carried out on small lung nodules, identified in the ITALUNG screening trial and on small nodules of the lung image database consortium (LIDC) dataset. In fully automated mode, 217/256 (84.8%) lung nodules of ITALUNG and 139/157 (88.5%) individual marks of lung nodules of LIDC were correctly outlined and an excellent reproducibility was also observed. By using an additional interactive mode, based on a controlled manual interaction, 233/256 (91.0%) lung nodules of ITALUNG and 144/157 (91.7%) individual marks of lung nodules of LIDC were overall correctly segmented. The proposed correction method could also be usefully applied to any existent nodule segmentation algorithm for improving the segmentation quality of juxta-vascular nodules.     

Micro- and Nanostructure of Zn Whiskers and Their Coating

To understand the mechanisms at the origin of whisker formation and growth, a Zn-electroplated steel prone to whiskering was studied. Several samples were prepared from different locations of the electroplated plate. Care was taken to extract samples at the root, in the nodule, or away from whiskers. Samples were characterized using electron backscattered diffraction (EBSD). Crystallographic data from EBSD show that recrystallized regions are present at the root of whiskers and in their nodules. These observations support whisker growth models based on recrystallization. In addition, atom probe tomography samples were prepared in the center of whiskers. The distribution of Zn atoms is almost homogeneous and no impurities are present in the whiskers.     

不同工艺制备的人工节瘤的损伤生长特性

在高能激光系统中,反射膜的损伤生长特性和初始损伤一样重要。对薄膜损伤生长特性的研究将有助于探究反射膜损伤机制,从而进一步有效地提高其抗激光损伤能力。使用电子束蒸发（EB）和离子束辅助（IAD）两种工艺制备了1064nm波长下的HfO2/SiO2反射膜,利用四种尺寸的单分散的SiO2小球形成人工节瘤,来研究薄膜镀制工艺和节瘤尺寸对节瘤损伤生长特性的影响。激光损伤测试结果表明:节瘤损伤生长阈值基本随节瘤尺寸的增加而减小。EB工艺制备的反射膜中,四种尺寸节瘤的损伤生长阈值都高于其初始损伤阈值,而IAD工艺制备的反射膜中结果则相反。另外,IAD工艺要比EB工艺制备的反射膜中的节瘤在发生初始损伤后更易于损伤生长,说明薄膜镀制工艺对节瘤的损伤生长速度有一定的影响。     

鼠重组腺病毒介导的骨形成蛋白-9转染大鼠牙囊干细胞的实验研究

目的：探讨鼠重组腺病毒介导的骨形成蛋白9基因转染大鼠牙囊干细胞的可行性及其转染后的成骨作用,以获得可用于牙周骨组织再生工程的基因修饰的种子细胞。方法：取大鼠下颌骨,解剖显微镜下体外分离培养纯化鉴定牙囊干细胞,腺病毒介导的骨形成蛋白9基因转染第三代牙囊干细胞,并设立空白对照组,绿色荧光病毒组（GFP组）。通过观察细胞形态及生长曲线变化,荧光显微镜及RT—PCR检测转染后骨形成蛋白9基因mRNA的表达,碱性磷酸酶及钙茜素红染色测定转染后牙囊干细胞的成骨活性。结果：与未转染对照组比较,转染组细胞转染2周后形成钙化结节,停滞期延长,数量轻度下降,倍增时间延长。牙囊干细胞转染骨形成蛋白9基因后12h后即有荧光表达,转染3,6,9,12d后骨形成蛋白9mRNA均呈阳性表达且逐渐增强,未转染对照组呈阴性。转染组碱性磷酸酶活性随转染时间的延长呈升高趋势,ALP染色及茜素红钙结节染色为阳性：未转染对照组碱性磷酸酶染色及钙茜素红染色均呈弱阳性表达,转染组显著高于未转染组。结论：鼠重组腺病毒介导的RBMP-9基因可以成功地转染大鼠牙囊干细胞,转染后牙囊干细胞高表达骨形成蛋白9,且具有明显的成骨作用。     

Computer-aided diagnosis of solid breast nodules: use of an artificial neural network based on multiple sonographic features

A computer-aided diagnosis (CAD) algorithm identifying breast nodule malignancy using multiple ultrasonography (US) features and artificial neural network (ANN) classifier was developed from a database of 584 histologically confirmed cases containing 300 benign and 284 malignant breast nodules. The features determining whether a breast nodule is benign or malignant were extracted from US images through digital image processing with a relatively simple segmentation algorithm applied to the manually preselected region of interest. An ANN then distinguished malignant nodules in US images based on five morphological features representing the shape, edge characteristics, and darkness of a nodule. The structure of ANN was selected using k-fold cross-validation method with k = 10. The ANN trained with randomly selected half of breast nodule images showed the normalized area under the receiver operating characteristic curve of 0.95. With the trained ANN, 53.3% of biopsies on benign nodules can be avoided with 99.3% sensitivity. Performance of the developed classifier was reexamined with new US mass images in the generalized patient population of total 266 (167 benign and 99 malignant) cases. The developed CAD algorithm has the potential to increase the specificity of US for characterization of breast lesions.     

Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network

Low-dose helical computed tomography (LDCT) is being applied as a modality for lung cancer screening. It may be difficult, however, for radiologists to distinguish malignant from benign nodules in LDCT. Our purpose in this study was to develop a computer-aided diagnostic (CAD) scheme for distinction between benign and malignant nodules in LDCT scans by use of a massive training artificial neural network (MTANN). The MTANN is a trainable, highly nonlinear filter based on an artificial neural network. To distinguish malignant nodules from six different types of benign nodules, we developed multiple MTANNs (multi-MTANN) consisting of six expert MTANNs that are arranged in parallel. Each of the MTANNs was trained by use of input CT images and teaching images containing the estimate of the distribution for the "likelihood of being a malignant nodule," i.e., the teaching image for a malignant nodule contains a two-dimensional Gaussian distribution and that for a benign nodule contains zero. Each MTANN was trained independently with ten typical malignant nodules and ten benign nodules from each of the six types. The outputs of the six MTANNs were combined by use of an integration ANN such that the six types of benign nodules could be distinguished from malignant nodules. After training of the integration ANN, our scheme provided a value related to the "likelihood of malignancy" of a nodule, i.e., a higher value indicates a malignant nodule, and a lower value indicates a benign nodule. Our database consisted of 76 primary lung cancers in 73 patients and 413 benign nodules in 342 patients, which were obtained from a lung cancer screening program on 7847 screenees with LDCT for three years in Nagano, Japan. The performance of our scheme for distinction between benign and malignant nodules was evaluated by use of receiver operating characteristic (ROC) analysis. Our scheme achieved an Az (area under the ROC curve) value of 0.882 in a round-robin test. Our scheme correctly identified 100% (76/76) of malignant nodules as malignant, whereas 48% (200/413) of benign nodules were identified correctly as benign. Therefore, our scheme may be useful in assisting radiologists in the diagnosis of lung nodules in LDCT.     

Local contralateral subtraction based on bilateral symmetry of lung for reduction of false positives in computerized detection of pulmonary nodules

A novel method called local contralateral subtraction has been developed for the removal of normal anatomic structures in chest radiographs based on the symmetry between the left and right lung regions. The method was oriented to the reduction of false positives reported by a computer-aided diagnosis (CAD) scheme for detection of lung nodules in chest radiographs. In our method, two regions of interest (ROIs) are extracted, one from the position where a nodule candidate is located, and the other from the anatomically corresponding location in the opposite lung, which contains similar normal structures. A wavelet-based, multiresolution image registration method is employed for matching the two ROIs, and subtraction is performed. If no structure remains in the subtracted ROI, then the original ROI is identified as negative (i.e., it contains only normal structures); otherwise, it is regarded as positive (i.e., it contains a nodule). A measure that quantifies the remaining structures was developed to distinguish between nodules and false positives. Application of the method to clinical chest radiographs showed that it was effective in eliminating normal anatomic structures and reducing the number of false detections in the CAD scheme for detection of lung nodules.