Selecting effective siRNA sequences by using radial basis function network and decision tree learning

BACKGROUND: Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are only a few consistencies among the recently reported design rules/guidelines for selecting siRNA sequences effective for mammalian genes. Another shortcoming of the previously reported methods is that they cannot estimate the probability that a candidate sequence will silence the target gene. RESULTS: We propose two prediction methods for selecting effective siRNA target sequences from many possible candidate sequences, one based on the supervised learning of a radial basis function (RBF) network and other based on decision tree learning. They are quite different from the previous score-based siRNA design techniques and can predict the probability that a candidate siRNA sequence will be effective. The proposed methods were evaluated by applying them to recently reported effective and ineffective siRNA sequences for various genes (15 genes, 196 siRNA sequences). We also propose the combined prediction method of the RBF network and decision tree learning. As the average prediction probabilities of gene silencing for the effective and ineffective siRNA sequences of the reported genes by the proposed three methods were respectively 65% and 32%, 56.6% and 38.1%, and 68.5% and 28.1%, the methods imply high estimation accuracy for selecting candidate siRNA sequences. CONCLUSION: New prediction methods were presented for selecting effective siRNA sequences. As the proposed methods indicated high estimation accuracy for selecting candidate siRNA sequences, they would be useful for many other genes

Coincidence between transcriptome analyses on different microarray platforms using a parametric framework

A parametric framework for the analysis of transcriptome data is demonstrated to yield coincident results when applied to data acquired using two different microarray platforms. Discrepancies among transcriptome studies are frequently reported, casting doubt on the reliability of collected data. The inconsistency among observations can be largely attributed to differences among the analytical frameworks employed for data analysis. The existing frameworks normalizes data against a standard determined from the data to be analyzed. In the present study, a parametric framework based on a strict model for normalization is applied to data acquired using an in-house printed chip and GeneChip. The framework is based on a common statistical characteristic of microarray data, and each data is normalized on the basis of a linear relationship with this model. In the proposed framework, the expressional changes observed and genes selected are coincident between platforms, achieving superior universality of data compared to other methods

Nationwide surveillance of bacterial respiratory pathogens conducted by the surveillance committee of Japanese Society of Chemotherapy, the Japanese Association for Infectious Diseases, and the Japanese Society for Clinical Microbiology in 2010: General view of the pathogens\u27 antibacterial susceptibility

The nationwide surveillance on antimicrobial susceptibility of bacterial respiratory pathogens from patients in Japan, was conducted by Japanese Society of Chemotherapy, Japanese Association for Infectious Diseases and Japanese Society for Clinical Microbiology in 2010.The isolates were collected from clinical specimens obtained from well-diagnosed adult patients with respiratory tract infections during the period from January and April 2010 by three societies. Antimicrobial susceptibility testing was conducted at the central reference laboratory according to the method recommended by Clinical and Laboratory Standard Institutes using maximum 45 antibacterial agents.Susceptibility testing was evaluable with 954 strains (206 Staphylococcus aureus, 189 Streptococcus pneumoniae, 4 Streptococcus pyogenes, 182 Haemophilus influenzae, 74 Moraxella catarrhalis, 139 Klebsiella pneumoniae and 160 Pseudomonas aeruginosa). Ratio of methicillin-resistant S.aureus was as high as 50.5%, and those of penicillin-intermediate and -resistant S.pneumoniae were 1.1% and 0.0%, respectively. Among H.influenzae, 17.6% of them were found to be β-lactamase-non-producing ampicillin (ABPC)-intermediately resistant, 33.5% to be β-lactamase-non-producing ABPC-resistant and 11.0% to be β-lactamase-producing ABPC-resistant strains. Extended spectrum β-lactamase-producing K.pneumoniae and multi-drug resistant P.aeruginosa with metallo β-lactamase were 2.9% and 0.6%, respectively.Continuous national surveillance of antimicrobial susceptibility of respiratory pathogens is crucial in order to monitor changing patterns of susceptibility and to be able to update treatment recommendations on a regular basis

Comparative analyses for selecting effective siRNA sequences

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Transcatheter Arterial Coil Embolization of Ruptured Common Hepatic Artery Aneurysm in a Patient with Behçet’s Disease

Hepatic artery aneurysm is a rare and potentially life-threatening entity. We report a case of ruptured common hepatic artery aneurysm in a patient with Behçet’s disease. The ruptured aneurysm was treated successfully with transcatheter arterial coil embolization. Transcatheter arterial embolization is the preferred treatment modality in patients at high risk of surgical intervention

Evaluation of Macaca radiata as a non-human primate model of Dengue virus infection

Dengue virus (DENV) causes a wide range of illnesses in humans, including dengue fever and dengue haemorrhagic fever. Current animal models of DENV infection are limited for understanding infectious diseases in humans. Bonnet monkeys (Macaca radiata), a type of Old World monkey, have been used to study experimental and natural infections by flaviviruses, but Old World monkeys have not yet been used as DENV infection models. In this study, the replication levels of several DENV strains were evaluated using peripheral blood mononuclear cells. Our findings indicated that DENV-4 09-48 strain, isolated from a traveller returning from India in 2009, was a highly replicative virus. Three bonnet monkeys were infected with 09-48 strain and antibody responses were assessed. DENV nonstructural protein 1 antigen was detected and high viraemia was observed. These results indicated that bonnet monkeys and 09-48 strain could be used as a reliable primate model for the study of DENV