Tensions, parallèles et interférences entre texte et musique. Le cas de Pierrot lunaire d’Arnold Schoenberg.

Cet article vise un double objectif. Il propose d’abord un examen détaillé des interférences entre le texte (forme et sémantique) et les structures musicales dans Pierrot lunaire d’Arnold Schoenberg. Les résultats de cette analyse suggèrent que le rapport texte-musique de cette oeuvre ne se conçoit que sur un mode hétérogène et extrêmement ambigu. Le deuxième objectif est de montrer que l’examen des exemples doit être étayé par une réflexion théorique sur les conditions de possibilité des interférences musico-textuelles, et sur les outils de description dont l’analyste dispose pour les mettre à jour.This article has two goals. First, it proposes a detailed analysis of the interference between the text (in its formal and semantic aspects) and the musical structures in Arnold Schoenberg’s Pierrot lunaire. The results suggest that the text-music relation in this work must be conceived of as heterogeneous and extremely ambivalent. The second goal is to show that such an analysis needs to be elaborated within a more general theoretical reflection about, on the one hand, the very conditions of possibility of the musical-textual interference and, on the other hand, the descriptive tools the researcher has at his disposition to reveal them

IAMBEE : a web-service for the identification of adaptive pathways from parallel evolved clonal populations

IAMBEE is a web server designed for the Identification of Adaptive Mutations in Bacterial Evolution Experiments (IAMBEE). Input data consist of genotype information obtained from independently evolved clonal populations or strains that show the same adapted behavior (phenotype). To distinguish adaptive from passenger mutations, IAMBEE searches for neighborhoods in an organism-specific interaction network that are recurrently mutated in the adapted populations. This search for recurrently mutated network neighborhoods, as proxies for pathways is driven by additional information on the functional impact of the observed genetic changes and their dynamics during adaptive evolution. In addition, the search explicitly accounts for the differences in mutation rate between the independently evolved populations. Using this approach, IAMBEE allows exploiting parallel evolution to identify adaptive pathways. The web-server is freely available at http://bioinformatics.intec.ugent.be/iambee/ with no login requirement

Effect of streptozotocin-induced diabetes on left ventricular function in adult rats: an in vivo Pinhole Gated SPECT study

<p>Abstract</p> <p>Background</p> <p>Recent studies have suggested that diabetes mellitus (DM) may cause left ventricular (LV) dysfunction directly resulting in increased susceptibility to heart failure. Using pinhole collimators and advances in data processing, gated SPECT was recently adapted to image the rat heart. The present study was aimed to assess this new imaging technique for quantifying LV function and remodeling from the Streptozotocin (STZ) rat model compared to controls.</p> <p>Methods</p> <p>Twenty one rats were randomly assigned to control or diabetic group. Six months after the induction of diabetes by STZ, Pinhole 99 m Tc-sestamibi gated SPECT was performed for determining rat LV volumes and function. Post-mortem histopathologic analysis was performed to evaluate the determinant of LV remodeling in this model.</p> <p>Results</p> <p>After six months, the normalized to body weight LV End-systolic volume was significantly different in diabetic rats compared to controls (0.46 ± 0.02 vs 0.33 ± 0.03 μL/g; p = 0.01). The normalized LV End-diastolic volume was also different in both groups (1.51 ± 0.03 vs 0.88 ± 0.05 μL/g; p = 0.001) and the normalized stroke volume was significantly higher in STZ-rats (1.05 ± 0.02 vs 0.54 ± 0.06 μL/g; p = 0.001). The muscular fibers were thinner at histology in the diabetic rats (0.44 ± 0.07 vs 0.32 ± 0.06 AU; p = 0.01).</p> <p>Conclusion</p> <p>Pinhole 99 m Tc-sestamibi gated SPECT can successfully be applied for the evaluation of cardiac function and remodeling in STZ-induced diabetic rats. In this model, LV volumes were significantly changed compared to a control population, leading to a LV dysfunction. These findings were consistent with the histopathological abnormalities. Finally, these data further suggest the presence of diabetes cardiomyopathy.</p

Network-based identification of adaptive pathways in evolved ethanol-tolerant bacterial populations

Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well

PheNetic : network-based interpretation of molecular profiling data

Molecular profiling experiments have become standard in current wet-lab practices. Classically, enrichment analysis has been used to identify biological functions related to these experimental results. Combining molecular profiling results with the wealth of currently available interactomics data, however, offers the opportunity to identify the molecular mechanism behind an observed molecular phenotype. In this paper, we therefore introduce 'PheNetic', a userfriendly web server for inferring a sub-network based on probabilistic logical querying. PheNetic extracts from an interactome, the sub-network that best explains genes prioritized through a molecular profiling experiment. Depending on its run mode, PheNetic searches either for a regulatorymechanism that gave explains to the observed molecular phenotype or for the pathways (in) activated in the molecular phenotype. The web server provides access to a large number of interactomes, making sub-network inference readily applicable to a wide variety of organisms. The inferred sub-networks can be interactively visualized in the browser. PheNetic's method and use are illustrated using an example analysis of differential expression results of ampicillin treated Escherichia coli cells. The PheNetic web service is available at http://bioinformatics.intec.ugent.be/phenetic/