Characterization of two isoforms of human SPRR3 from saliva of preterm human newborn and autoptic fetal oral mucosa, parotid and submandibular gland samples

RP-HPLC-ESI-MS profile of saliva samples from human preterm newborn showed a protein peak in the elution range 26.6-27.6 min. Deconvolution of ESI-MS spectra revealed the presence of two proteins with average molecular mass (Mav) values of 17,239 ± 3 Da and 18,065 ± 3 Da in 9 samples, with Mav value of 17,239 ± 3 Da in 4 samples and Mav value of 18,065 ± 3 Da in 2 samples. MALDI-TOF-MS analysis of tryptic digest allowed identifying the proteins as two isoforms of small proline-rich protein 3 and cDNA amplification of RNA extracts from oral mucosa, parotid and submandibular gland samples, obtained at fetal autopsy, provided two nucleotide sequences in agreement with those reported in the literature. The two proteins differ for an octapeptide repeat (GCTKVPEP) and the substitution Leu → Val, at position 148 and 140 of the mature form of the 18,065 and 17,239 Da protein, respectively. During maturation the two proteins undergo two post-translational modifications, corresponding to N-terminal acetylation and removal of the initiator methionine. cDNA amplification did not allow to clarify if the proteins found in saliva originated from cellular shedding of the epithelium and/or secretion.     

基于时间聚类分析和独立成分分析的癫痫fMRI盲分析方法

提出了一种基于时间聚类分析和独立成分分析的癫痫fMRI数据盲分析方法,并将两种方法有效联合,提取发作间期的癫痫fMRI激活时空信息.该方法首先由时间聚类分析得到与激活相关的时间峰度特征曲线,以此特征作为时间参考信息;再由空间独立成分分析分解fMRI信号得到空间独立成分;最后将每个独立成分所对应的时间曲线与参考曲线做相关分析提取相应脑激活图.提出的方法无需任何关于癫痫fMRI的先验假设信息,有效解决了独立成分的排序问题,实现了对数据的盲分析.仿真试验结果阐明了这一方法的有效性及可靠性,对癫痫数据的试验结果显示空间定位准确性优于统计参数图方法.     

Transcriptional Profiling of Gene Expression Changes in a PACE-Transfected CHO DUKX Cell Line Secreting High Levels of rhBMP-2

Chinese hamster ovary (CHO) cells are widely used in the biopharmaceutical industry for the production of recombinant human proteins including complex polypeptides such as recombinant human bone morphogenic protein 2 (rhBMP-2). Large-scale manufacture of rhBMP-2 has associated production difficulties resulting from incomplete processing of the recombinant human protein due to insufficient endogenous levels of the paired basic amino acid cleaving enzyme (PACE) in CHO. In order to resolve this issue, CHO DUKX cells expressing rhBMP-2 were transfected with the soluble version of human PACE (PACEsol) resulting in improved amino-terminal homogeneity and a fourfold increase in rhBMP-2 productivity. In this article, we present a microarray expression profile analysis comparing the parental lineage to the higher producing subclone co-expressing PACEsol using a proprietary CHO-specific microarray. Using this technology we observed 1,076 significantly different genes in the high-productivity cells co-expressing PACEsol. Following further analysis of the differentially expressed genes, the Unfolded Protein Response (UPR) component of the endoplasmic reticulum stress response pathway was identified as a key candidate for effecting increased productivity in this cell system. Several additional ER- and Golgi-localised proteins were identified which may also contribute to this effect. The results presented here support the use of large-scale microarray expression profiling as a viable and valuable route towards understanding the behaviour of bioprocess cultures in vitro.     

A DSRPCL-SVM approach to informative gene analysis

Microarray data based tumor diagnosis is a very interesting topic in bioinformatics. One of the key problems is the discovery and analysis of informative genes of a tumor. Although there are many elaborate approaches to this problem, it is still difficult to select a reasonable set of informative genes for tumor diagnosis only with microarray data. In this paper, we classify the genes expressed through microarray data into a number of clusters via the distance sensitive rival penalized competitive learning （DSRPCL） algorithm and then detect the informative gene cluster or set with the help of support vector machine （SVM）. Moreover, the critical or powerful informative genes can be found through further classifications and detections on the obtained informative gene clusters. It is well demonstrated by experiments on the colon, leukemia, and breast cancer datasets that our proposed DSRPCL-SVM approach leads to a reasonable selection of informative genes for tumor diagnosis.     

Simple Sequence Repeat Analysis of Genetic Diversity in Primary Core Collection of Peach （Prunus persica）

In this study, the genetic diversity of 51 cultivars in the primary core collection of peach （Prunus persica （L.） Batsch） was evaluated by using simple sequence repeats （SSRs）. The phylogenetic relationships and the evolutionary history among different cultivars were determined on the basis of SSR data. Twenty-two polymorphic SSR primer pairs were selected, and a total of 111 alleles were identified in the 51 cultivars, with an average of 5 alleles per locus. According to traditional Chinese classification of peach cultivars, the 51 cultivars in the peach primary core collection belong to six variety groups. The SSR analysis revealed that the levels of the genetic diversity within each variety group were ranked as Sweet peach 〉 Crisp peach 〉 Flat peach 〉 Nectarine 〉 Honey Peach 〉 Yellow fleshed peach. The genetic diversity among the Chinese cultivars was higher than that among the introduced cultivars. Cluster analysis by the unweighted pair group method with arithmetic averaging （UPGMA） placed the 51 cultivars into five linkage clusters. Cultivar members from the same variety group were distributed in different UPGMA clusters and some members from different variety groups were placed under the same cluster. Different variety groups could not be differentiated in accordance with SSR markers. The SSR analysis revealed rich genetic diversity in the peach primary core collection, representative of genetic resources of peach.     

Homogeneous Agent-Based Distributed Information Filtering

Recent advances in processor, networking and software technologies have made distributed computing a reality in today's world. Distributed systems offer many advantages, ranging from a higher performance to the effective utilization of physically dispersed resources. Many diverse application domains can benefit by exploiting principles of distributed computing. Information filtering is one such application domain. In this article, we present a design of a homogeneous distributed multi-agent information filtering system, called D-SIFTER. D-SIFTER is based on the language-dependent model of Java RMI. The detailed design process and various experiments carried out using D-SIFTER are also described. The results indicate that the distributed inter-agent collaboration improves the overall filtering performance.     

Indices of bird-habitat preference from field surveys of birds and remote sensing of land cover: a study of south-eastern England with wider implications for conservation and biodiversity assessment

Aim This paper describes the development of novel indices of bird‐habitat preference to examine bird species’ use of habitats and their distributions relative to habitats. It assesses the implications for bird conservation regionally and the scope for biodiversity assessments generally. Location A 200 km by 400 km area of farmland with seminatural and urban areas, covering south‐eastern England. Methods Cluster analysis was used to link birds to landscapes. Cluster centroid coordinate values were processed to derive indices of bird‐habitat preference. Further developments assessed the relative values of individual habitats for birds. Results Clustering objectively linked birds to landscapes. Maps of the clusters showed strong regional patterns associated with distinctive habitat assemblages. Derived indices related bird species directly to individual habitats and habitats to birds. Even rare species and scarce habitats showed successful linkages, often to each other. Objective corroboration strongly supported the associations of coastal, wetland, urban and woodland birds and habitats; but, it suggested that farmland birds, whose numbers have nearly halved since 1977, may prefer alternative habitats. Main conclusions Land cover maps from remote sensing provide an effective way to link birds to habitats and vice versa. Thus, generalized habitat maps might be used to extrapolate localized or sample‐based bird observations or the results of autecological studies, helping to predict and understand bird distributions in the wider countryside. The weak links between farmland birds and farmland habitats in a region dominated by farming, suggests that reasons for the decline in farmland birds may be deep seated and thus hard to reverse. The procedures described are repeatable elsewhere and applicable more generally to evaluate landscapes and biodiversity. It is suggested that remote sensing could rarely be bettered as a means of assessing habitats, comprehensively, over wide areas, in most parts of the world.     

多维协变量具有测量误差的结构回归模型

提出具有测量误差的结构回归模型,研究可交换条件下多维协变量的测量误差对平均处理效应估计的影响,在没有其它的附加条件下,尽管大多数模型参数不可识别,平均处理效应仍可识别,由于平均处理效应的极大似然估计求解困难,建议在实际中使用拟极大似然估计作为替代。     

不同寄主来源的灰葡萄孢对番茄的致病力分化研究

Eighteen isolates of Botrytis cinerea were obtained from the diseased plant tissue collected in Hefei, Bengbu, Changfeng and Hexian in Anhui province, by means of tissue isolating method. The pathogenicity of the isolates of B. cinerea from different hosts to the fruits and leaves of tomato were investigated by applying wound inoculation with mycelial blocks. The results showed that all of the tested isolates caused grey mould on tomato fruits, but there was significant difference in the average diameters of the lesions caused by different isolates, suggesting that there was significant differentiation in pathogenicity of B. cinerea strains to tomato fruits among isolates. According to the average diameters of the lesions on tomato fruits, the pathogenicity of the all isolates was classified into three categories: strong, intermediate and weak. In general, the isolates from tomato were more strongly pathogenic to tomato fruits than the isolates from strawberry, grape and capsicum. However, there was difference in pathogenicity among the different isolates from the same host, and the pathogenicity difference was not obviously related to the localities of isolates. After inoculating of tomato leaves, all of the tested isolates except CF3 caused grey mould on tomato leaves, but there was significant difference in the average diameters of the lesions caused by different isolates; and the difference in pathogenicity to tomato leaves was not obviously related to the host and locality of isolates.     

Variable selection for model-based high-dimensional clustering and its application to microarray data

Summary .   Variable selection in high-dimensional clustering analysis is an important yet challenging problem. In this article, we propose two methods that simultaneously separate data points into similar clusters and select informative variables that contribute to the clustering. Our methods are in the framework of penalized model-based clustering. Unlike the classical L ₁-norm penalization, the penalty terms that we propose make use of the fact that parameters belonging to one variable should be treated as a natural "group." Numerical results indicate that the two new methods tend to remove noninformative variables more effectively and provide better clustering results than the L ₁-norm approach.