We undertook this study to understand how the transcription factor Sox2 contributes to the malignant phenotype of glioblastoma multiforme (GBM), the most aggressive primary brain tumor. We initially looked for unbalanced genomic rearrangements in the Sox2 locus in 42 GBM samples and found that Sox2 was amplified in 11.5% and overexpressed in all the samples. These results prompted us to further investigate the mechanisms involved in Sox2 overexpression in GBM. We analyzed the methylation status of the Sox2 promoter because high CpG density promoters are associated with key developmental genes. The Sox2 promoter presented a CpG island that was hypomethylated in all the patient samples when compared to normal cell lines. Treatment of Sox2-negative glioma cell lines with 5-azacitidine resulted in the re-expression of Sox2 and in a change in the methylation status of the Sox2 promoter. We further confirmed these results by analyzing data from GBM cases generated by The Cancer Genome Atlas project. We observed Sox2 overexpression (86%; N = 414), Sox2 gene amplification (8.5%; N = 492), and Sox 2 promoter hypomethylation (100%; N = 258), suggesting the relevance of this factor in the malignant phenotype of GBMs. To further explore the role of Sox2, we performed in vitro analysis with brain tumor stem cells (BTSCs) and established glioma cell lines. Downmodulation of Sox2 in BTSCs resulted in the loss of their self-renewal properties. Surprisingly, ectopic expression of Sox2 in established glioma cells was not sufficient to support self-renewal, suggesting that additional factors are required. Furthermore, we observed that ectopic Sox2 expression was sufficient to induce invasion and migration of glioma cells, and knockdown experiments demonstrated that Sox2 was essential for maintaining these properties. Altogether, our data underscore the importance of a pleiotropic role of Sox2 and suggest that it could be used as a therapeutic target in GBM.

Motivation: Elementary flux modes (EFMs) represent a key concept to analyze metabolic networks from a pathway-oriented perspective. In spite of considerable work in this field, the computation of the full set of elementary flux modes in large-scale metabolic networks still constitutes a challenging issue due to its underlying combinatorial complexity. Results: In this article, we illustrate that the full set of EFMs can be enumerated in increasing order of number of reactions via integer linear programming. In this light, we present a novel procedure to efficiently determine the K-shortest EFMs in large-scale metabolic networks. Our method was applied to find the K-shortest EFMs that produce lysine in the genome-scale metabolic networks of Escherichia coli and Corynebacterium glutamicum. A detailed analysis of the biological significance of the K-shortest EFMs was conducted, finding that glucose catabolism, ammonium assimilation, lysine anabolism and cofactor balancing were correctly predicted. The work presented here represents an important step forward in the analysis and computation of EFMs for large-scale metabolic networks, where traditional methods fail for networks of even moderate size. Contact:fplanes@tecnun.es Supplementary information: Supplementary data are available at Bioinformatics online.

A haptic interface is a kinesthetic link between a human operator and a virtual environment. A way of studying the stability of a 1 degree-of-freedom (DOF) haptic interface using the Routh-Hurwitz criterion is presented in this brief. Parameter conditions that guarantee the stability of the system with a static virtual environment have been found. These conditions can help in the development and implementation of haptic devices. Finally, they have been confirmed by experimental results.

Recent work shows that S -adenosylmethionine (AdoMet) helps maintain normal liver function as chronic hepatic deficiency results in spontaneous development of steatohepatitis and hepatocellular carcinoma. The mechanisms by which these nontraditional functions of AdoMet occur are unknown. Here, we use knockout mice deficient in hepatic AdoMet synthesis ( MAT1A ^−/− ) to study the proteome of the liver during the development of steatohepatitis. One hundred and seventeen protein spots, differentially expressed during the development of steatohepatitis, were selected and identified by peptide mass fingerprinting. Among them, 12 proteins were found to be affected from birth, when MAT1A ^−/− expression is switched on in WT mouse liver, to the rise of histological lesions, which occurs at ≈8 months. Of the 12 proteins, 4 [prohibitin 1 (PHB1), cytochrome c oxidase I and II, and ATPase β-subunit] have known roles in mitochondrial function. We show that the alteration in expression of PHB1 correlates with a loss of mitochondrial function. Experiments in isolated rat hepatocytes indicate that AdoMet regulates PHB1 content, thus suggesting ways by which steatohepatitis may be induced. Importantly, we found the expression of these mitochondrial proteins was abnormal in ob/ob mice and obese patients who are at risk for nonalcoholic steatohepatitis.

MiRNAs are small RNA molecules (′22 nt) that interact with their target mRNAs inhibiting translation or/and cleavaging the target mRNA. This interaction is guided by sequence complentarity and results in the reduction of mRNA and/or protein levels. miRNAs are involved in key biological processes and different diseases. Therefore, deciphering miRNA targets is crucial for diagnostics and therapeutics. However, miRNA regulatory mechanisms are complex and there is still no high-throughput and low-cost miRNA target screening technique. In recent years, several computational methods based on sequence complementarity of the miRNA and the mRNAs have been developed. However, the predicted interactions using these computational methods are inconsistent and the expected false positive rates are still large. Recently, it has been proposed to use the expression values of miRNAs and mRNAs (and/or proteins) to refine the results of sequence-based putative targets for a particular experiment. These methods have shown to be effective identifying the most prominent interactions from the databases of putative targets. Here, we review these methods that combine both expression and sequence-based putative targets to predict miRNA targets.

A procedure for experimental evaluation and objective/quantitative comparison among the different teleoperation architectures and systems is proposed. It is based on the analysis of the different matrices that can define the teleoperated system (two-port representations) and the selection of a set of four parameters that are easy to estimate via simple experimentation: free motion impedance, position tracking in free movement, force tracking in hard contact tasks and maximum transmittable impedance. These parameters provide complete characterization of the master-slave system and have clear physical interpretation. Furthermore, they require no maneouvering of the slave robot, which is very useful in the case of heavy or nonaccessible industrial robots. The method has been applied to compare position-position (PP), force-position (FP), and four-channel (4C) controllers in a 2 DOF master-slave system. Experimental measuring for all four parameters will be shown, proving the 4C architecture clearly better than any other.