自动识别技术在昆虫分类鉴别研究中的应用

昆虫的自动识别是重要的新兴研究领域,它以直接、快速、方便等优点日益受到人们的青睐。昆虫是世界上最大的生物类群,鉴定工作费时耗力,然而分类专家又在逐渐减少。近年来,昆虫自动识别技术的发展为解决这一矛盾提供了乐观的方案。众多分类学家不断探索自动识别的方法和理论,并开发出了一批识别软件。本文介绍自动识别的原理,分类讨论自动识别的技术和方法,并分析提出面临的困难和应对策略。     

Immunocytochemical identification of laticifers

Summary sensitive immunocytochemical method for the identification of laticifers has been developed. Frozen sections of various laticifer-bearing plant material, mounted on slides, were first flooded with the IgG fraction of rabbit anti-latex antiserum, prepared using whole latex ofAsclepias syriaca, then flooded with fluorescein-conjugated IgG fraction goat anti-rabbit IgG to visualize laticifers. Positive fluorescence was observed for laticifers in shoots and embryos ofA. syriaca andStapelia bella and embryos ofA. tuberosa. Laticifers did not fluoresce in shoots ofA. tuberosa andEuphorbia tirucalli, in embryos ofE. marginata, or in petioles ofMusa paradisiaca andCichorium intybus. Controls prepared with uninjected rabbit serum were negative (no fluorescence).     

红梅汤薄层色谱鉴别研究

目的建立红梅汤制剂主要药材红梅叶、锡叶藤的鉴别方法。方法采用薄层色谱法对红梅汤制剂中的红梅叶、锡叶藤进行鉴别。结果在确定的条件下,红梅汤中红梅叶、锡叶藤药材的薄层色谱分离效果良好,斑点清晰,重现性好。结论该方法简便可靠,分离度较好,可用于红梅汤的质量控制。     

昆虫远程鉴定方法

介绍了利用数码显微镜用摄像仪、计算机网络传输图像的远程鉴定技术在昆虫鉴定方面尝试 ,认为该远程鉴定技术在昆虫的鉴定或复核方面有开发前景     

Evidence-ranked motif identification

cERMIT is a computationally efficient motif discovery tool based on analyzing genome-wide quantitative regulatory evidence. Instead of pre-selecting promising candidate sequences, it utilizes information across all sequence regions to search for high-scoring motifs. We apply cERMIT on a range of direct binding and overexpression datasets; it substantially outperforms state-of-the-art approaches on curated ChIP-chip datasets, and easily scales to current mammalian ChIP-seq experiments with data on thousands of non-coding regions.     

龙脷叶茎显微和薄层色谱鉴别的研究

龙脷叶( Sauropus spatulifolius Beille)为大戟科守宫木属植物,主要分布于我国的广西和广东等地,为广西常用壮药,具有润肺止咳、通便之功效,在民间使用广泛。现代研究表明,龙脷叶具有较好的抗炎和镇痛作用。全草均可入药,为国家药典收载品种。但其鉴别方法尚未完全建立,质量标准有待进一步完善。目前其叶与根的显微鉴别已有报道,而茎的鉴别未见有相关报道,因此有必要对龙脷叶茎的鉴别方法进行研究。该研究采用生药学显微鉴别和薄层色谱法对龙脷叶的茎进行了鉴别。结果表明：龙脷叶茎的主要显微特征为木栓层有7~12列细胞,皮层中含有较多淀粉粒,并含有纤维束,韧皮部窄,木质部宽,射线明显,髓部大;粉末可见螺纹、网纹及梯纹导管,伴有草酸钙簇晶,淀粉粒较小,有纤维。薄层色谱采用对照药材进行对照,发现样品斑点与对照药材斑点数量和位置一一对应。上述特征可作为鉴别和制定龙脷叶茎质量标准的参考依据,该研究结果为建立龙脷叶茎的鉴别方法以及进一步建立其质量标准提供了科学依据。     

Automated identification of Fos expression

The concentration of Fos, a protein encoded by the immediate-early gene c-fos, provides a measure of synaptic activity that may not parallel the electrical activity of neurons. Such a measure is important for the difficult problem of identifying dynamic properties of neuronal circuitries activated by a variety of stimuli and behaviours. We employ two-stage statistical pattern recognition to identify cellular nuclei that express Fos in two-dimensional sections of rat forebrain after administration of antipsychotic drugs. In stage one, we distinguish dark-stained candidate nuclei from image background by a thresholding algorithm and record size and shape measurements of these objects. In stage two, we compare performance of linear and quadratic discriminants, nearest-neighbour and artificial neural network classifiers that employ functions of these measurements to label candidate objects as either Fos nuclei, two touching Fos nuclei or irrelevant background material. New images of neighbouring brain tissue serve as test sets to assess generalizability of the best derived classification rule, as determined by lowest cross-validation misclassification rate. Three experts, two internal and one external, compare manual and automated results for accuracy assessment. Analyses of a subset of images on two separate occasions provide quantitative measures of inter- and intra-expert consistency. We conclude that our automated procedure yields results that compare favourably with those of the experts and thus has potential to remove much of the tedium, subjectivity and irreproducibility of current Fos identification methods in digital microscopy.     

红色毛癣菌菌株的特异性PCR鉴定方法研究

目的建立一种快速的红色毛癣菌分子生物学鉴定方法。方法根据红色毛癣菌保守区域-真菌核糖体DNA（rDNA）的转录间隔区（ITS）设计特异性引物,采用上游：ITS19865＇GAC ACC AAG AAA AAA TTC TCT GAA GA3＇,下游：ITS24415＇GTC CTG AGG GCG CTG AA3＇为引物对45株红色毛癣菌、5株须癣毛癣菌和1株紫色毛癣菌菌株的DNA进行PCR扩增,观察产物电泳带型的差异。结果 45株红色毛癣菌均能扩增出目的片段,5株须癣毛癣菌和1株紫色毛癣菌均无目的片段扩增出。结论红色毛癣菌可用特异引物PCR方法快速鉴定。     

Computational identification of microRNA targets

Recent experiments have shown that the genomes of organisms such as worm, fly, human, and mouse encode hundreds of microRNA genes. Many of these microRNAs are thought to regulate the translational expression of other genes by binding to partially complementary sites in messenger RNAs. Phenotypic and expression analysis suggests an important role of microRNAs during development. Therefore, it is of fundamental importance to identify microRNA targets. However, no experimental or computational high-throughput method for target site identification in animals has been published yet. Our main result is a new computational method that is designed to identify microRNA target sites. This method recovers with high specificity known microRNA target sites that have previously been defined experimentally. Based on these results, we present a simple model for the mechanism of microRNA target site recognition. Our model incorporates both kinetic and thermodynamic components of target recognition. When we applied our method to a set of 74 Drosophila melanogaster microRNAs, searching 3'UTR sequences of a predefined set of fly mRNAs for target sites which were evolutionary conserved between D. melanogaster and Drosophila pseudoobscura, we found that many key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs.     

Molecular identification of Tetrahymena species

Mitochondrial cox1 689 bp barcodes are routinely used for identification of Tetrahymena species. Here, we examine whether two shorter nuclear sequences, the 5.8S rRNA gene region and the intergenic region between H3 and H4 histone genes, might also be useful either singly or in combination with each other or cox1. We obtained sequences from ~300 wild isolates deposited at the Tetrahymena Stock Center and analyzed additional sequences obtained from GenBank. The 5.8S rRNA gene and portions of its transcribed flanks identify isolates as to their major clade and uniquely identify some, but not all, species. The ~330 bp H3/H4 intergenic region possesses low intraspecific variability and is unique for most species. However, it fails to distinguish between two pairs of common species and their rarer counterparts, and its use is complicated by the presence of duplicate genes in some species. The results show that while the cox1 sequence is the best single marker for Tetrahymena species identification, 5.8S rRNA, and the H3/H4 intergenic regions sequences are useful, singly or in combination, to confirm cox1 species assignments or as part of a preliminary survey of newly collected Tetrahymena. From our newly collected isolates, the results extend the biogeographical range of T. shanghaiensis and T. malaccensis and identify a new species, Tetrahymena arleneae n. sp. herein described.