A Large-Scale Epidemiological Study to Identify Bacteria Pathogenic to Pacific Oyster Crassostrea gigas and Correlation Between Virulence and Metalloprotease-like Activity

A 4-year bacteriological survey (2003-2007) of four molluscs cultivated in France and faced with mortality episodes was performed by the French shellfish pathology network. The more abundant bacteria isolated during 92 mortality episodes, occurring mainly in Pacific oyster Crassostrea gigas, were identified by genotyping methods. It allowed us both to confirm the representativeness of Vibrio splendidus and Vibrio aestuarianus bacterial strains and to identify both a large number of Vibrio harveyi-related strains mainly detected during 2007 oyster mortality outbreaks and to a lesser extent bacterial strains identified as Shewanella colwelliana. Because metalloprotease has been reported to constitute a virulence factor in a few Vibrio strains pathogenic for C. gigas, several bacterial strains isolated in this study were screened to evaluate their pathogenicity in C. gigas spat by experimental infection and their ability to produce metalloprotease-like activity in the culture supernatant fluids. A high level (84%) of concordant results between azocaseinase activities and virulence of strains was obtained in this study. Because bacterial metalloprotease activities appeared as a common feature of pathogenic bacteria strains associated with mortality events of C. gigas reared in France, this phenotypic test could be useful for the evaluation of virulence in bacterial strains associated with such mortality episodes.     

TSUNAMI: Translational Bioinformatics Tool Suite for Network Analysis and Mining

Gene co-expression network (GCN) mining identifies gene modules with highly correlated expression profiles across samples/conditions. It enables researchers to discover latent gene/molecule interactions, identify novel gene functions, and extract molecular features from certain disease/condition groups, thus helping to identify disease biomarkers. However, there lacks an easy-to-use tool package for users to mine GCN modules that are relatively small in size with tightly connected genes that can be convenient for downstream gene set enrichment analysis, as well as modules that may share common members. To address this need, we developed an online GCN mining tool package: TSUNAMI (Tools SUite for Network Analysis and MIning). TSUNAMI incorporates our state-of-the-art lmQCM algorithm to mine GCN modules for both public and user-input data (microarray, RNA-seq, or any other numerical omics data), and then performs downstream gene set enrichment analysis for the identified modules. It has several features and advantages: 1) a user-friendly interface and real-time co-expression network mining through a web server; 2) direct access and search of NCBI Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, as well as user-input gene expression matrices for GCN module mining; 3) multiple co-expression analysis tools to choose from, all of which are highly flexible in regards to parameter selection options; 4) identified GCN modules are summarized to eigengenes, which are convenient for users to check their correlation with other clinical traits; 5) integrated downstream Enrichr enrichment analysis and links to other gene set enrichment tools; and 6) visualization of gene loci by Circos plot in any step of the process. The web service is freely accessible through URL: https://biolearns.medicine.iu.edu/. Source code is available at https://github.com/huangzhii/TSUNAMI/.     

基于社会网络分析和共词分析的制药技术领域研究

目的:深入研究制药技术领域的发展态势。方法:本研究以Pub Med数据库中收录的制药技术领域研究论文为研究对象,采用社会网络分析、共词分析等定量方法,结合药学专业知识的定性分析,从论文数量年度分布、国家/地区分布及合作网络、研究主题等多个角度开展研究。结果:研究发现:第一,全球制药技术领域共有研究论文95381篇,近几年正处于快速发展阶段;第二,论文发表集中在美国、中国和日本等国家;第三,在定量分析的基础上,结合药学专业知识,共得到15个研究主题,包括点击化学、晶型药物、纳米微球药物等。结论:美国在制药技术领域处于主导地位,中国发文量已经具备一定优势,但发文量和国际影响力与美国相比还是存在较大差距;通过对制药技术领域研究主题的深入分析可以全面把握制药技术领域的研究现状和发展态势。     

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.     

Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy,Identify Key Nodes and Predict Network Dynamics

Background

Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult.

Methodology/Principal Findings

Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics.

Conclusions/Significance

The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.     

An Agent-Based Model of Centralized Institutions,Social Network Technology,and Revolution

This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change.     

The Cost Effectiveness of Psychological and Pharmacological Interventions for Social Anxiety Disorder: A Model-Based Economic Analysis

Background

Social anxiety disorder is one of the most persistent and common anxiety disorders. Individually delivered psychological therapies are the most effective treatment options for adults with social anxiety disorder, but they are associated with high intervention costs. Therefore, the objective of this study was to assess the relative cost effectiveness of a variety of psychological and pharmacological interventions for adults with social anxiety disorder.

Methods

A decision-analytic model was constructed to compare costs and quality adjusted life years (QALYs) of 28 interventions for social anxiety disorder from the perspective of the British National Health Service and personal social services. Efficacy data were derived from a systematic review and network meta-analysis. Other model input parameters were based on published literature and national sources, supplemented by expert opinion.

Results

Individual cognitive therapy was the most cost-effective intervention for adults with social anxiety disorder, followed by generic individual cognitive behavioural therapy (CBT), phenelzine and book-based self-help without support. Other drugs, group-based psychological interventions and other individually delivered psychological interventions were less cost-effective. Results were influenced by limited evidence suggesting superiority of psychological interventions over drugs in retaining long-term effects. The analysis did not take into account side effects of drugs.

Conclusion

Various forms of individually delivered CBT appear to be the most cost-effective options for the treatment of adults with social anxiety disorder. Consideration of side effects of drugs would only strengthen this conclusion, as it would improve even further the cost effectiveness of individually delivered CBT relative to phenelzine, which was the next most cost-effective option, due to the serious side effects associated with phenelzine. Further research needs to determine more accurately the long-term comparative benefits and harms of psychological and pharmacological interventions for social anxiety disorder and establish their relative cost effectiveness with greater certainty.     

表型特征结合基因组分析鉴定不同菌落形态Bacillus velezensis ACCC 19742

在中国农业微生物菌种中心(ACCC)菌株的定期转接保藏过程中,发现解淀粉芽孢杆菌ACCC 19742在同一培养基上出现两种不同的菌落形态,将这两个不同形态的菌株编号为19742-1和19742-2。通过形态学、生理生化及基因组分析相结合鉴定不同菌落形态ACCC 19742,并进一步确定该菌株的分类地位。首先将菌株进行分离与纯化,其次将纯化后的菌株进行16S rRNA及gyrB基因扩增及序列分析,通过MEGA 7.0软件构建系统发育树;API 20NE、BIOLOG及脂肪酸等分析菌株的生理生化特性;全基因组分析菌株的ANI和DDH值。两株菌在API 20NE中,仅葡萄糖酸盐同化反应存在差异;脂肪酸检测中主要组成相同,仅是百分含量方面略有差别;两株菌的16S rRNA基因相似性为100%,gyrB基因的相似性为99.4%;全基因组测序表明,两株菌的ANI值为99.95%,DDH值为99.62%。综合遗传学特征和表型特征,证实两者为来源于同一菌株不同的形态变异型,而并非污染所致。同时,19742-1和19742-2与Bacillus velezensis NRRL_B 41580~T的ANI及DDH值最高,分别为97%和77%,且16S rRNA和gyrB系统进化分析也表明,该菌株在分类地位上属于贝莱斯芽孢杆菌(Bacillus velezensis),而非解淀粉芽孢杆菌。这为菌株的保藏提供了一定的参考价值。     

Using FAME Analysis to Compare, Differentiate, and Identify Multiple Nematode Species

We have adapted the Sherlock^® Microbial Identification system for identification of plant parasitic nematodes based on their fatty acid profiles. Fatty acid profiles of 12 separate plant parasitic nematode species have been determined using this system. Additionally, separate profiles have been developed for Rotylenchulus reniformis and Meloidogyne incognita based on their host plant, four species and three races within the Meloidogyne genus, and three life stages of Heterodera glycines. Statistically, 85% of these profiles can be delimited from one another; the specific comparisons between the cyst and vermiform stages of H. glycines, M. hapla and M. arenaria, and M. arenaria and M. javanica cannot be segregated using canonical analysis. By incorporating each of these fatty acid profiles into the Sherlock^® Analysis Software, 20 library entries were created. While there was some similarity among profiles, all entries correctly identified the proper organism to genus, species, race, life stage, and host at greater than 86% accuracy. The remaining 14% were correctly identified to genus, although species and race may not be correct due to the underlying variables of host or life stage. These results are promising and indicate that this library could be used for diagnostics labs to increase response time.     

The Effectiveness of Different Interventions to Promote Poison Prevention Behaviours in Households with Children: A Network Meta-Analysis

Background

There is evidence from 2 previous meta-analyses that interventions to promote poison prevention behaviours are effective in increasing a range of poison prevention practices in households with children. The published meta-analyses compared any intervention against a “usual care or no intervention” which potentially limits the usefulness of the analysis to decision makers. We aim to use network meta-analysis to simultaneously evaluate the effectiveness of different interventions to increase prevalence of safe storage of i) Medicines only, ii) Other household products only, iii) Poisons (both medicines and non-medicines), iv) Poisonous plants; and v) Possession of poison control centre (PCC) telephone number in households with children.

Methods

Data on the effectiveness of poison prevention interventions was extracted from primary studies identified in 2 newly-undertaken systematic reviews. Effect estimates were pooled across studies using a random effects network meta-analysis model.

Results

28 of the 47 primary studies identified were included in the analysis. Compared to usual care intervention, the intervention with education and low cost/free equipment elements was most effective in promoting safe storage of medicines (odds ratio 2.51, 95% credible interval 1.01 to 6.00) while interventions with education, low cost/free equipment, home safety inspection and fitting components were most effective in promoting safe storage of other household products (2.52, 1.12 to 7.13), safe storage of poisons (11.10, 1.60 to 141.50) and possession of PCC number (38.82, 2.19 to 687.10). No one intervention package was more effective than the others in promoting safe storage of poisonous plants.

Conclusion

The most effective interventions varied by poison prevention practice, but education alone was not the most effective intervention for any poison prevention practice. Commissioners and providers of poison prevention interventions should tailor the interventions they commission or provide to the poison prevention practices they wish to promote.

Highlights

• Network meta-analysis is useful for comparing multiple injury-prevention interventions.
• More intensive poison prevention interventions were more effective than education alone.
• Education and low cost/free equipment was most effective in promoting safe storage of medicines.
• Education, low cost/free equipment, home safety inspection and fitting was most effective in promoting safe storage of household products and poisons.
• Education, low cost/free equipment and home inspection were most effective in promoting possession of a poison control centre number.
• None of the intervention packages was more effective than the others in promoting safe storage of poisonous plants.

     

Proteomics and Phosphoproteomic Analysis to Identify Spleen of Takifugu rubripes Infected Cryptocaryon irritans

Marine Biotechnology - Takifugu rubripes is important commercially fish species in China and it is under serious threat from white spot disease (cyptocaryoniasis), which leads to heavy economic...