Identification et caractérisation de gènes suppresseurs de tumeurs dans le glioblastome

Introduction: Glioblastoma (WHO Grade IV glioma) is the most frequent and most¦malignant primary tumor of the brain. With a mean survival of 15 months despite¦multidisciplinary management combining surgery, chemo- and radiotherapy, the prognosis¦is poor. Different studies measured a down-regulation of Wnt Inhibitory Factor 1 (WIF1)¦expression in a majority of gliobastoma due to genetic and epigenetic regulation. Recently,¦a focus on chromosome 12 identified WIF1 as a potential tumor suppressor gene. In¦previous results, transfected glioblastoma cells with ectopic expression of WIF1 had a¦decreased growth rate and adopted a senescence-like phenotype. In this report, we first¦investigated the effect of WIF1 re-expression in glioblastoma cell lines to see if Wnt¦inhibition by WIF1 can lead to senescence. To look further, we assessed p21 and c-Myc¦expression. p21 has a key role in senescence onset and is directly inhibited by c-Myc,¦itself a target of Wnt-pathway. We thus looked if a variation of expression of these genes is¦triggered by WIF1 activity. Finally, as autophagy is thought to play a role in senescence¦onset, we analyzed the expression of different autophagy genes. We therefore looked for¦an association between autophagy activity and senescent phenotype in WIF1-¦overexpressing cell lines.¦Methods: WIF1-overexpressing clones were selected after transfection of stable¦glioblastoma cell lines. Analysis were made through quantitative Polymerase Chain¦Reaction (qPCR), Fluorescence-activated Cell Sorting (FACS) and histochemistry.¦IGFBP7 and ALDH1A3 have been selected to reflect senescence. ATG5, ATG7 and ULK3¦have been selected to reflect autophagy activity.¦Results: Using FACS analysis, we found a higher percentage of large cells with increased¦granularity amongst WIF1-overexpressing cell lines, which are characteristics of¦senescence. In addition, histochemistry showed a higher percentage of multi-nucleated,¦beta-galactosidase positive cells in the same cell lines. An increased expression of genes¦associated with senescence was found as well. All characteristics were correlated with¦levels of WIF1 expression. We did not find any association between p21 and WIF1¦expression. No correlation between WIF1 and c-Myc expression was noticed either. In one¦of the two cell lines analyzed, the expression of autophagy genes showed some¦correlation with expression of WIF1 and expression of genes associated with senescence.¦Discussion: After investigations and characterizations on multiple levels, we have¦evidence for a senescence phenotype upon WIF1-overexpressing cell lines. This gives a¦role to Wnt pathway in the tumorigenicity of glioblastoma. Further experiments are¦required to investigate how Wnt inhibition leads to senescence. The role of autophagy in¦our senescent cells is here still unclear. Some correlations can be found, letting us think¦that there is indeed some involvement of autophagy. However, it is yet to soon to explain¦this relationship. Further experiments are required again to confirm the preliminary results¦and analyze the variations of autophagy activity within time.

A two-stage approach for tonic identification in indian art music

In this paper we propose a new approach for tonic identification in Indian art music and present a proposal for acomplete iterative system for the same. Our method splits the task of tonic pitch identification into two stages. In the first stage, which is applicable to both vocal and instrumental music, we perform a multi-pitch analysis of the audio signal to identify the tonic pitch-class. Multi-pitch analysisallows us to take advantage of the drone sound, which constantlyreinforces the tonic. In the second stage we estimate the octave in which the tonic of the singer lies and is thusneeded only for the vocal performances. We analyse the predominant melody sung by the lead performer in order to establish the tonic octave. Both stages are individually evaluated on a sizable music collection and are shown toobtain a good accuracy. We also discuss the types of errors made by the method.Further, we present a proposal for a system that aims to incrementally utilize all the available data, both audio and metadata in order to identify the tonic pitch. It produces a tonic estimate and a confidence value, and is iterative in nature. At each iteration, more data is fed into the systemuntil the confidence value for the identified tonic is above a defined threshold. Rather than obtain high overall accuracy for our complete database, ultimately our goal is to develop a system which obtains very high accuracy on a subset of the database with maximum confidence.

Invasive mould infections: a multi-disciplinary update.

Systemic fungal infections remain a significant cause of mortality in neutropenic and immunocompromised patients, despite advances in their diagnosis and treatment. The incidence of such infections is rising due to the use of intensive chemotherapy regimens in patients with solid tumours or haematological cancers, the increasing numbers of allogeneic haematopoietic stem cell and solid organ transplants, and the use of potent immunosuppressive therapy in patients with autoimmune disorders. In addition, the epidemiology of systemic fungal infections is changing, with atypical species such as Aspergillus terreus and zygomycetes becoming more common. Treatment has traditionally focused on empirical therapy, but targeted pre-emptive therapy in high-risk patients and prophylactic antifungal treatment are increasingly being adopted. New treatments, including lipid formulations of amphotericin B, second-generation broad-spectrum azoles, and echinocandins, offer effective antifungal activity with improved tolerability compared with older agents; the potential impact of these treatments is reflected in their inclusion in current treatment and prophylaxis guidelines. New treatment strategies, such as aerosolized lipid formulations of amphotericin B, may also reduce the burden of mortality associated with systemic fungal infections. The challenge is to identify ways of coupling potentially effective treatments with early and reliable identification of patients at highest risk of infection.

Multi-well fungal co-culture for de novo metabolite-induction in time-series studies based on untargeted metabolomics.

The induction of fungal metabolites by fungal co-cultures grown on solid media was explored using multi-well co-cultures in 2 cm diameter Petri dishes. Fungi were grown in 12-well plates to easily and rapidly obtain the large number of replicates necessary for employing metabolomic approaches. Fungal culture using such a format accelerated the production of metabolites by several weeks compared with using the large-format 9 cm Petri dishes. This strategy was applied to a co-culture of a Fusarium and an Aspergillus strain. The metabolite composition of the cultures was assessed using ultra-high pressure liquid chromatography coupled to electrospray ionisation and time-of-flight mass spectrometry, followed by automated data mining. The de novo production of metabolites was dramatically increased by nutriment reduction. A time-series study of the induction of the fungal metabolites of interest over nine days revealed that they exhibited various induction patterns. The concentrations of most of the de novo induced metabolites increased over time. However, interesting patterns were observed, such as with the presence of some compounds only at certain time points. This result indicates the complexity and dynamic nature of fungal metabolism. The large-scale production of the compounds of interest was verified by co-culture in 15 cm Petri dishes; most of the induced metabolites of interest (16/18) were found to be produced as effectively as on a small scale, although not in the same time frames. Large-scale production is a practical solution for the future production, identification and biological evaluation of these metabolites.

The contributions of sensory dominance and attentional bias to cross-modal enhancement of visual cortex excitability.

Approaching or looming sounds (L-sounds) have been shown to selectively increase visual cortex excitability [Romei, V., Murray, M. M., Cappe, C., & Thut, G. Preperceptual and stimulus-selective enhancement of low-level human visual cortex excitability by sounds. Current Biology, 19, 1799-1805, 2009]. These cross-modal effects start at an early, preperceptual stage of sound processing and persist with increasing sound duration. Here, we identified individual factors contributing to cross-modal effects on visual cortex excitability and studied the persistence of effects after sound offset. To this end, we probed the impact of different L-sound velocities on phosphene perception postsound as a function of individual auditory versus visual preference/dominance using single-pulse TMS over the occipital pole. We found that the boosting of phosphene perception by L-sounds continued for several tens of milliseconds after the end of the L-sound and was temporally sensitive to different L-sound profiles (velocities). In addition, we found that this depended on an individual's preferred sensory modality (auditory vs. visual) as determined through a divided attention task (attentional preference), but not on their simple threshold detection level per sensory modality. Whereas individuals with "visual preference" showed enhanced phosphene perception irrespective of L-sound velocity, those with "auditory preference" showed differential peaks in phosphene perception whose delays after sound-offset followed the different L-sound velocity profiles. These novel findings suggest that looming signals modulate visual cortex excitability beyond sound duration possibly to support prompt identification and reaction to potentially dangerous approaching objects. The observed interindividual differences favor the idea that unlike early effects this late L-sound impact on visual cortex excitability is influenced by cross-modal attentional mechanisms rather than low-level sensory processes.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Reversible cerebral vasoconstriction syndrome identification of prognostic factors.

OBJECT: Reversible cerebral vasoconstriction syndrome (RCVS) is described as a clinical and radiological entity characterized by thunderclap headaches, a reversible segmental or multifocal vasoconstriction of cerebral arteries with or without focal neurological deficits or seizures. The purpose of this study is to determine risk factors of poor outcome in patients presented a RCVS. METHODS: A retrospective multi-center review of invasive and non-invasive neurovascular imaging between January 2006 and January 2011 has identified 10 patients with criterion of reversible segmental vasoconstriction syndrome. Demographics data, vascular risks and evolution of each of these patients were analyzed. RESULTS: Seven of the ten patients were females with a mean age of 46 years. In four patients, we did not found any causative factors. Two cases presented RCVS in post-partum period between their first and their third week after delivery. The other three cases were drug-induced RCVS, mainly vaso-active drugs. Cannabis was found as the causative factor in two patient, Sumatriptan identified in one patient while cyclosporine was the causative agent in also one patient. The mean duration of clinical follow-up was 10.2 months (range: 0-28 months). Two patients had neurological sequelae: one patient kept a dysphasia and the other had a homonymous lateral hemianopia. We could not find any significant difference of the evolution between secondary RCVS and idiopathic RCVS. The only two factors, which could be correlated to the clinical outcome were the neurological status at admission and the presence of intraparenchymal abnormalities (ischemic stroke, hematoma) in brain imaging. CONCLUSIONS: Fulminant vasoconstriction resulting in progressive symptoms or death has been reported in exceptional frequency. Physicians had to remember that such evolution could happen and predict them by identifying all factors of poor prognosis (neurological status at admission, the presence of intraparenchymal abnormalities).

Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.

An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.

Broadband excitation in the system identification of active magnetic bearing rotor systems

One of the targets of the climate and energy package of the European Union is to increase the energy efficiency in order to achieve a 20 percent reduction in primary energy use compared with the projected level by 2020. The energy efficiency can be improved for example by increasing the rotational speed of large electrical drives, because this enables the elimination of gearboxes leading to a compact design with lower losses. The rotational speeds of traditional bearings, such as roller bearings, are limited by mechanical friction. Active magnetic bearings (AMBs), on the other hand, allow very high rotational speeds. Consequently, their use in large medium- and high-speed machines has rapidly increased. An active magnetic bearing rotor system is an inherently unstable, nonlinear multiple-input, multiple-output system. Model-based controller design of AMBs requires an accurate system model. Finite element modeling (FEM) together with the experimental modal analysis provides a very accurate model for the rotor, and a linearized model of the magneticactuators has proven to work well in normal conditions. However, the overall system may suffer from unmodeled dynamics, such as dynamics of foundation or shrink fits. This dynamics can be modeled by system identification. System identification can also be used for on-line diagnostics. In this study, broadband excitation signals are adopted to the identification of an active magnetic bearing rotor system. The broadband excitation enables faster frequency response function measurements when compared with the widely used stepped sine and swept sine excitations. Different broadband excitations are reviewed, and the random phase multisine excitation is chosen for further study. The measurement times using the multisine excitation and the stepped sine excitation are compared. An excitation signal design with an analysis of the harmonics produced by the nonlinear system is presented. The suitability of different frequency response function estimators for an AMB rotor system are also compared. Additionally, analytical modeling of an AMB rotor system, obtaining a parametric model from the nonparametric frequency response functions, and model updating are discussed in brief, as they are key elements in the modeling for a control design. Theoretical methods are tested with a laboratory test rig. The results conclude that an appropriately designed random phase multisine excitation is suitable for the identification of AMB rotor systems.

IDENTIFICATION OF SUITABLE AREAS FOR IRRIGATED RICE CROPPING USING MODIS IMAGES AND HAND MODEL

ABSTRACT One of the most relevant activities of Brazilian economy is agriculture. Among the main crops in Brazil, rice is one of high relevance. The state of Rio Grande do Sul, in Southern Brazil, is responsible for 68.7% of domestic production (IBGE, 2013). The goal of this study was to develop a low-cost methodology with a regional scope to identify suitable areas for irrigated rice cropping in this state, using spectro-temporal behavior of vegetation index by means of MODIS images and HAND model. The rice-cropped area of this study was the southern half of the State. Using the HAND model, flood areas were mapped to identify irrigated rice cultivation. We used multi-temporal images of vegetation index from MODIS sensor, covering the period from August 2001 to May 2012. To assess the results, we used data collected in the fields and cropped area information from IBGE. The results showed that the proposed methodology was satisfactory, with Kappa 0.92 and global accuracy of 98.18%. As result, MODIS sensor data and flood areas delineation by means of HAND model generated the estimate irrigated rice area for the area of study.

Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Influence of multi-phase phenomena on semibatch crystallization processes of aqueous solutions

Crystal properties, product quality and particle size are determined by the operating conditions in the crystallization process. Thus, in order to obtain desired end-products, the crystallization process should be effectively controlled based on reliable kinetic information, which can be provided by powerful analytical tools such as Raman spectrometry and thermal analysis. The present research work studied various crystallization processes such as reactive crystallization, precipitation with anti-solvent and evaporation crystallization. The goal of the work was to understand more comprehensively the fundamentals, phenomena and utilizations of crystallization, and establish proper methods to control particle size distribution, especially for three phase gas-liquid-solid crystallization systems. As a part of the solid-liquid equilibrium studies in this work, prediction of KCl solubility in a MgCl2-KCl-H2O system was studied theoretically. Additionally, a solubility prediction model by Pitzer thermodynamic model was investigated based on solubility measurements of potassium dihydrogen phosphate with the presence of non-electronic organic substances in aqueous solutions. The prediction model helps to extend literature data and offers an easy and economical way to choose solvent for anti-solvent precipitation. Using experimental and modern analytical methods, precipitation kinetics and mass transfer in reactive crystallization of magnesium carbonate hydrates with magnesium hydroxide slurry and CO2 gas were systematically investigated. The obtained results gave deeper insight into gas-liquid-solid interactions and the mechanisms of this heterogeneous crystallization process. The research approach developed can provide theoretical guidance and act as a useful reference to promote development of gas-liquid reactive crystallization. Gas-liquid mass transfer of absorption in the presence of solid particles in a stirred tank was investigated in order to gain understanding of how different-sized particles interact with gas bubbles. Based on obtained volumetric mass transfer coefficient values, it was found that the influence of the presence of small particles on gas-liquid mass transfer cannot be ignored since there are interactions between bubbles and particles. Raman spectrometry was successfully applied for liquid and solids analysis in semi-batch anti-solvent precipitation and evaporation crystallization. Real-time information such as supersaturation, formation of precipitates and identification of crystal polymorphs could be obtained by Raman spectrometry. The solubility prediction models, monitoring methods for precipitation and empirical model for absorption developed in this study together with the methodologies used gives valuable information for aspects of industrial crystallization. Furthermore, Raman analysis was seen to be a potential controlling method for various crystallization processes.

Identification of renin progenitors in the mouse bone marrow that give rise to B-cell leukaemia

cell of origin and triggering events for leukaemia are mostly unknown. Here we show that the bone marrow contains a progenitor that expresses renin throughout development and possesses a B-lymphocyte pedigree. This cell requires RBP-J to differentiate. Deletion of RBP-J in these renin-expressing progenitors enriches the precursor B-cell gene programme and constrains lymphocyte differentiation, facilitated by H3K4me3 activating marks in genes that control the pre-B stage. Mutant cells undergo neoplastic transformation, and mice develop a highly penetrant B-cell leukaemia with multi-organ infiltration and early death. These reninexpressing cells appear uniquely vulnerable as other conditional models of RBP-J deletion do not result in leukaemia. The discovery of these unique renin progenitors in the bone marrow and the model of leukaemia described herein may enhance our understanding of normal and neoplastic haematopoiesis.

La gouvernance des projets d’architecture : une typologie de la multi-organisation temporaire

Les débats éthiques sur l’architecture ont traditionnellement abordé trois thématiques récurrentes : la beauté, la solidité et l’utilité de l’œuvre architecturale. Plus récemment, les nouvelles connaissances provenant du domaine de la gestion des projets et du développement durable ont apporté d’importantes contributions à la compréhension de la gouvernance de projets. Cependant, la démarche de réalisation des projets d’architecture est tributaire des caractéristiques propres à l’industrie du bâtiment; une industrie qui fonctionne grâce à la mise en place d’équipes temporaires formées par des organisations hautement spécialisées. L’analyse systémique d’études de cas permet d’identifier la complexité des équipes qui interviennent dans les projets d’architecture. Nous examinons dans cet article trois caractéristiques de l’industrie du bâtiment : (i) la complexité organisationnelle du donneur d’ouvrage, (ii) l’influence des parties prenantes, et (iii) les divers niveaux de proximité entre l’architecte et les usagers. L’identification des diverses configurations organisationnelles met en évidence les effets de ces caractéristiques sur les relations formelles et informelles entre l’architecte et les donneurs d’ouvrage ainsi que celles entre toutes les parties prenantes. L’architecte est contraint de travailler sur un projet qui devient, de plus en plus, l’objet de négociation entre les diverses parties prenantes. Face à ce défi, il doit tenir compte de la complexité des relations entre tous les acteurs au sein du système social du projet et créer les scénarios adéquats à la participation, à la négociation et aux échanges entre eux.

Development of a multi-gene PCR assay for the prediction of the response to hormone therapy in breast cancer

Deux tiers des cancers du sein expriment des récepteurs hormonaux ostrogéniques (tumeur ER-positive) et la croissance de ces tumeurs est stimulée par l’estrogène. Des traitements adjuvant avec des anti-estrogènes, tel que le Tamoxifen et les Inhibiteurs de l’Aromatase peuvent améliorer la survie des patientes atteinte de cancer du sein. Toutefois la thérapie hormonale n’est pas efficace dans toutes les tumeurs mammaires ER-positives. Les tumeurs peuvent présenter avec une résistance intrinsèque ou acquise au Tamoxifen. Présentement, c’est impossible de prédire quelle patiente va bénéficier ou non du Tamoxifen. Des études préliminaires du laboratoire de Dr. Mader, ont identifié le niveau d’expression de 20 gènes, qui peuvent prédire la réponse thérapeutique au Tamoxifen (survie sans récidive). Ces marqueurs, identifié en utilisant une analyse bioinformatique de bases de données publiques de profils d’expression des gènes, sont capables de discriminer quelles patientes vont mieux répondre au Tamoxifen. Le but principal de cette étude est de développer un outil de PCR qui peut évaluer le niveau d’expression de ces 20 gènes prédictif et de tester cette signature de 20 gènes dans une étude rétrospective, en utilisant des tumeurs de cancer du sein en bloc de paraffine, de patients avec une histoire médicale connue. Cet outil aurait donc un impact direct dans la pratique clinique. Des traitements futiles pourraient être éviter et l’indentification de tumeurs ER+ avec peu de chance de répondre à un traitement anti-estrogène amélioré. En conséquence, de la recherche plus appropriée pour les tumeurs résistantes au Tamoxifen, pourront se faire.