122 research outputs found

    From supported membranes to tethered vesicles: lipid bilayers destabilisation at the main transition

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    We report results concerning the destabilisation of supported phospholipid bilayers in a well-defined geometry. When heating up supported phospholipid membranes deposited on highly hydrophilic glass slides from room temperature (i.e. with lipids in the gel phase), unbinding was observed around the main gel to fluid transition temperature of the lipids. It lead to the formation of relatively monodisperse vesicles, of which most remained tethered to the supported bilayer. We interpret these observations in terms of a sharp decrease of the bending rigidity modulus κ\kappa in the transition region, combined with a weak initial adhesion energy. On the basis of scaling arguments, we show that our experimental findings are consistent with this hypothesis.Comment: 11 pages, 3 figure

    TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks

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    Automatic surgical phase recognition is a challenging and crucial task with the potential to improve patient safety and become an integral part of intra-operative decision-support systems. In this paper, we propose, for the first time in workflow analysis, a Multi-Stage Temporal Convolutional Network (MS-TCN) that performs hierarchical prediction refinement for surgical phase recognition. Causal, dilated convolutions allow for a large receptive field and online inference with smooth predictions even during ambiguous transitions. Our method is thoroughly evaluated on two datasets of laparoscopic cholecystectomy videos with and without the use of additional surgical tool information. Outperforming various state-of-the-art LSTM approaches, we verify the suitability of the proposed causal MS-TCN for surgical phase recognition.Comment: 10 pages, 2 figure

    Aberrant signaling in T-cell acute lymphoblastic leukemia: biological and therapeutic implications

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    T-cell acute lymphoblastic leukemia (T-ALL) is a biologically heterogeneous disease with respect to phenotype, gene expression profile and activation of particular intracellular signaling pathways. Despite very significant improvements, current therapeutic regimens still fail to cure a portion of the patients and frequently implicate the use of aggressive protocols with long-term side effects. In this review, we focused on how deregulation of critical signaling pathways, in particular Notch, PI3K/Akt, MAPK, Jak/STAT and TGF-beta, may contribute to T-ALL. Identifying the alterations that affect intracellular pathways that regulate cell cycle and apoptosis is essential to understanding the biology of this malignancy, to define more effective markers for the correct stratification of patients into appropriate therapeutic regimens and to identify novel targets for the development of specific, less detrimental therapies for T-ALL

    A New Pipeline for the Normalization and Pooling of Metabolomics Data

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    Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists

    Diverse RNA-Binding Proteins Interact with Functionally Related Sets of RNAs, Suggesting an Extensive Regulatory System

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    RNA-binding proteins (RBPs) have roles in the regulation of many post-transcriptional steps in gene expression, but relatively few RBPs have been systematically studied. We searched for the RNA targets of 40 proteins in the yeast Saccharomyces cerevisiae: a selective sample of the approximately 600 annotated and predicted RBPs, as well as several proteins not annotated as RBPs. At least 33 of these 40 proteins, including three of the four proteins that were not previously known or predicted to be RBPs, were reproducibly associated with specific sets of a few to several hundred RNAs. Remarkably, many of the RBPs we studied bound mRNAs whose protein products share identifiable functional or cytotopic features. We identified specific sequences or predicted structures significantly enriched in target mRNAs of 16 RBPs. These potential RNA-recognition elements were diverse in sequence, structure, and location: some were found predominantly in 3′-untranslated regions, others in 5′-untranslated regions, some in coding sequences, and many in two or more of these features. Although this study only examined a small fraction of the universe of yeast RBPs, 70% of the mRNA transcriptome had significant associations with at least one of these RBPs, and on average, each distinct yeast mRNA interacted with three of the RBPs, suggesting the potential for a rich, multidimensional network of regulation. These results strongly suggest that combinatorial binding of RBPs to specific recognition elements in mRNAs is a pervasive mechanism for multi-dimensional regulation of their post-transcriptional fate

    Principles of mRNA transport in yeast

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    mRNA localization and localized translation is a common mechanism by which cellular asymmetry is achieved. In higher eukaryotes the mRNA transport machinery is required for such diverse processes as stem cell division and neuronal plasticity. Because mRNA localization in metazoans is highly complex, studies at the molecular level have proven to be cumbersome. However, active mRNA transport has also been reported in fungi including Saccharomyces cerevisiae, Ustilago maydis and Candida albicans, in which these events are less difficult to study. Amongst them, budding yeast S. cerevisiae has yielded mechanistic insights that exceed our understanding of other mRNA localization events to date. In contrast to most reviews, we refrain here from summarizing mRNA localization events from different organisms. Instead we give an in-depth account of ASH1 mRNA localization in budding yeast. This approach is particularly suited to providing a more holistic view of the interconnection between the individual steps of mRNA localization, from transcriptional events to cytoplasmic mRNA transport and localized translation. Because of our advanced mechanistic understanding of mRNA localization in yeast, the present review may also be informative for scientists working, for example, on mRNA localization in embryogenesis or in neurons

    Comparisons between Chemical Mapping and Binding to Isoenergetic Oligonucleotide Microarrays Reveal Unexpected Patterns of Binding to the Bacillus subtilis RNase P RNA Specificity Domain†

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    ABSTRACT: Microarrays with isoenergetic pentamer and hexamer 20-O-methyl oligonucleotide probes with LNA (locked nucleic acid) and 2,6-diaminopurine substitutions were used to probe the binding sites on theRNase P RNA specificity domain of Bacillus subtilis. Unexpected binding patterns were revealed. Because of their enhanced binding free energies, isoenergetic probes can break short duplexes, merge adjacent loops, and/or induce refolding. This suggests new approaches to the rational design of short oligonucleotide therapeutics but limits the utility of microarrays for providing constraints for RNA structure determination. The microarray results are compared to results from chemical mapping experiments, which do provide constraints. Results from both types of experiments indicate that the RNase P RNA folds similarly in 1MNaþ and 10 mMMg2þ. Binding of RNA to RNA is important for many natural func-tions, includingproteinsynthesis (1,2), translationregulation (3,4), gene silencing (5, 6), metabolic regulation (7), RNAmodification (8, 9), etc. (10-13). Binding of oligonucleotides toRNAs is impor-tant for therapeutic approaches, such as siRNA, ribozymes, and antisense therapy (14, 15).Much remains to bediscovered, however, of the rules for predicting binding sites andpotential therapeutics
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