Microbial ligand costimulation drives neutrophilic steroid-refractory asthma

Funding: The authors thank the Wellcome Trust (102705) and the Universities of Aberdeen and Cape Town for funding. This research was also supported, in part, by National Institutes of Health GM53522 and GM083016 to DLW. KF and BNL are funded by the Fonds Wetenschappelijk Onderzoek, BNL is the recipient of an European Research Commission consolidator grant and participates in the European Union FP7 programs EUBIOPRED and MedALL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

SFSSClass: an integrated approach for miRNA based tumor classification

Background: MicroRNA (miRNA) expression profiling data has recently been found to be particularly important in cancer research and can be used as a diagnostic and prognostic tool. Current approaches of tumor classification using miRNA expression data do not integrate the experimental knowledge available in the literature. A judicious integration of such knowledge with effective miRNA and sample selection through a biclustering approach could be an important step in improving the accuracy of tumor classification. Results: In this article, a novel classification technique called SFSSClass is developed that judiciously integrates a biclustering technique SAMBA for simultaneous feature (miRNA) and sample (tissue) selection (SFSS), a cancer-miRNA network that we have developed by mining the literature of experimentally verified cancer-miRNA relationships and a classifier uncorrelated shrunken centroid (USC). SFSSClass is used for classifying multiple classes of tumors and cancer cell lines. In a part of the investigation, poorly differentiated tumors (PDT) having non diagnostic histological appearance are classified while training on more differentiated tumor (MDT) samples. The proposed method is found to outperform the best known accuracy in the literature on the experimental data sets. For example, while the best accuracy reported in the literature for classifying PDT samples is similar to 76.5%, the accuracy of SFSSClass is found to be similar to 82.3%. The advantage of incorporating biclustering integrated with the cancer-miRNA network is evident from the consistently better performance of SFSSClass (integration of SAMBA, cancer-miRNA network and USC) over USC (eg., similar to 70.5% for SFSSClass versus similar to 58.8% in classifying a set of 17 MDT samples from 9 tumor types, similar to 91.7% for SFSSClass versus similar to 75% in classifying 12 cell lines from 6 tumor types and similar to 382.3% for SFSSClass versus similar to 41.2% in classifying 17 PDT samples from 11 tumor types). Conclusion: In this article, we develop the SFSSClass algorithm which judiciously integrates a biclustering technique for simultaneous feature (miRNA) and sample (tissue) selection, the cancer-miRNA network and a classifier. The novel integration of experimental knowledge with computational tools efficiently selects relevant features that have high intra-class and low interclass similarity. The performance of the SFSSClass is found to be significantly improved with respect to the other existing approaches

A Survival Analysis of Islamic and Conventional Banks

Are Islamic banks inherently more stable than conventional banks? We address this question by applying a survival analysis based on the Cox proportional hazard model to a comprehensive sample of 421 banks in 20 Middle and Far Eastern countries from 1995 to 2010. By comparing the failure risk for both bank types, we find that Islamic banks have a significantly lower risk of failure than that of their conventional peers. This lower risk is based both unconditionally and conditionally on bank-specific (microeconomic) variables as well as macroeconomic and market structure variables. Our findings indicate that the design and implementation of early warning systems for bank failure should recognize the distinct risk profiles of the two bank types

The Silkworm (Bombyx mori) microRNAs and Their Expressions in Multiple Developmental Stages

BACKGROUND: MicroRNAs (miRNAs) play crucial roles in various physiological processes through post-transcriptional regulation of gene expressions and are involved in development, metabolism, and many other important molecular mechanisms and cellular processes. The Bombyx mori genome sequence provides opportunities for a thorough survey for miRNAs as well as comparative analyses with other sequenced insect species. METHODOLOGY/PRINCIPAL FINDINGS: We identified 114 non-redundant conserved miRNAs and 148 novel putative miRNAs from the B. mori genome with an elaborate computational protocol. We also sequenced 6,720 clones from 14 developmental stage-specific small RNA libraries in which we identified 35 unique miRNAs containing 21 conserved miRNAs (including 17 predicted miRNAs) and 14 novel miRNAs (including 11 predicted novel miRNAs). Among the 114 conserved miRNAs, we found six pairs of clusters evolutionarily conserved cross insect lineages. Our observations on length heterogeneity at 5' and/or 3' ends of nine miRNAs between cloned and predicted sequences, and three mature forms deriving from the same arm of putative pre-miRNAs suggest a mechanism by which miRNAs gain new functions. Analyzing development-related miRNAs expression at 14 developmental stages based on clone-sampling and stem-loop RT PCR, we discovered an unusual abundance of 33 sequences representing 12 different miRNAs and sharply fluctuated expression of miRNAs at larva-molting stage. The potential functions of several stage-biased miRNAs were also analyzed in combination with predicted target genes and silkworm's phenotypic traits; our results indicated that miRNAs may play key regulatory roles in specific developmental stages in the silkworm, such as ecdysis. CONCLUSIONS/SIGNIFICANCE: Taking a combined approach, we identified 118 conserved miRNAs and 151 novel miRNA candidates from the B. mori genome sequence. Our expression analyses by sampling miRNAs and real-time PCR over multiple developmental stages allowed us to pinpoint molting stages as hotspots of miRNA expression both in sorts and quantities. Based on the analysis of target genes, we hypothesized that miRNAs regulate development through a particular emphasis on complex stages rather than general regulatory mechanisms

MicroRNA Let-7f Inhibits Tumor Invasion and Metastasis by Targeting MYH9 in Human Gastric Cancer

BACKGROUND: MicroRNAs (miRNAs) are important regulators that play key roles in tumorigenesis and tumor progression. A previous report has shown that let-7 family members can act as tumor suppressors in many cancers. Through miRNA array, we found that let-7f was downregulated in the highly metastatic potential gastric cancer cell lines GC9811-P and SGC7901-M, when compared with their parental cell lines, GC9811 and SGC7901-NM; however, the mechanism was not clear. In this study, we investigate whether let-7f acts as a tumor suppressor to inhibit invasion and metastasis in gastric cancers. METHODOLOGY/PRINCIPAL: Real-time PCR showed decreased levels of let-7f expression in metastatic gastric cancer tissues and cell lines that are potentially highly metastatic. Cell invasion and migration were significantly impaired in GC9811-P and SGC7901-M cell lines after transfection with let-7f-mimics. Nude mice with xenograft models of gastric cancer confirmed that let-7f could inhibit gastric cancer metastasis in vivo after transfection by the lentivirus pGCsil-GFP- let-7f. Luciferase reporter assays demonstrated that let-7f directly binds to the 3'UTR of MYH9, which codes for myosin IIA, and real-time PCR and Western blotting further indicated that let-7f downregulated the expression of myosin IIA at the mRNA and protein levels. CONCLUSIONS/SIGNIFICANCE: Our study demonstrated that overexpression of let-7f in gastric cancer could inhibit invasion and migration of gastric cancer cells through directly targeting the tumor metastasis-associated gene MYH9. These data suggest that let-7f may be a novel therapeutic candidate for gastric cancer, given its ability to reduce cell invasion and metastasis