19 research outputs found

    Deregulation of Rab and Rab Effector Genes in Bladder Cancer

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    Growing evidence indicates that Rab GTPases, key regulators of intracellular transport in eukaryotic cells, play an important role in cancer. We analysed the deregulation at the transcriptional level of the genes encoding Rab proteins and Rab-interacting proteins in bladder cancer pathogenesis, distinguishing between the two main progression pathways so far identified in bladder cancer: the Ta pathway characterized by a high frequency of FGFR3 mutation and the carcinoma in situ pathway where no or infrequent FGFR3 mutations have been identified. A systematic literature search identified 61 genes encoding Rab proteins and 223 genes encoding Rab-interacting proteins. Transcriptomic data were obtained for normal urothelium samples and for two independent bladder cancer data sets corresponding to 152 and 75 tumors. Gene deregulation was analysed with the SAM (significant analysis of microarray) test or the binomial test. Overall, 30 genes were down-regulated, and 13 were up-regulated in the tumor samples. Five of these deregulated genes (LEPRE1, MICAL2, RAB23, STXBP1, SYTL1) were specifically deregulated in FGFR3-non-mutated muscle-invasive tumors. No gene encoding a Rab or Rab-interacting protein was found to be specifically deregulated in FGFR3-mutated tumors. Cluster analysis showed that the RAB27 gene cluster (comprising the genes encoding RAB27 and its interacting partners) was deregulated and that this deregulation was associated with both pathways of bladder cancer pathogenesis. Finally, we found that the expression of KIF20A and ZWINT was associated with that of proliferation markers and that the expression of MLPH, MYO5B, RAB11A, RAB11FIP1, RAB20 and SYTL2 was associated with that of urothelial cell differentiation markers. This systematic analysis of Rab and Rab effector gene deregulation in bladder cancer, taking relevant tumor subgroups into account, provides insight into the possible roles of Rab proteins and their effectors in bladder cancer pathogenesis. This approach is applicable to other group of genes and types of cancer

    Tillage management effects on pesticide fate in soils. A review

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    Une ferme de l’Armorique gauloise

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    Découverte lors de la construction de la deviation de la N 176 pres de Dinan, la ferine du Boisanne n’est qu’une modeste exploitation rurale ; elle constitue pourtant un objet d’étude exemplaire. On pent en effet suivre sans interruption son evolution sur une très longue durée, du VIe s. av. J. -C. au IIIe s. ap. J. -C. La stratigraphic, les structures ct le mobilier sont présentés de façon detaillee. La ferme est replacée dans son contexte tant géographique (l’estuaire de la Rance) qu’historique (Page du Fer armoricain).L’étude s’achève sur une réflexion depassant largement le cadre régional: la fonction et l’évolution des « fermes indigenes » ou aedificia (mythe ou réalité archéologique ? ) de l’âge du Fer à l’époque gallo-romaine.Discovered during the construction of a four- lane trunk road (N 176) near Dinan, the Iron Age farm at Le Boisanne is but a modest rural settlement ; it constituted however an ideal subject of study. One can follow without interruption its evolution during a very long period, from the 4th century BC up to the 3rd century AD. The stratigraphy, the structures and the artefacts are presented in detail. The farm is placed in its context, both geographical (the Rance estuary) and historic (Armorican Iron Age). This study is concluded by a broad reflection, extending outside the purely regional framework: on the function and evolution of “native farms” or aedificia (archaeological myth or reality ?) of the Iron Age and gallo-roman periods

    Archéologie et GEoarchéologie du premier Remiremont et de ses abords: Projet Collectif de Recherche AGER. Rapport 2019-2020

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    La montagne comme espace peu et tardivement peuplé en marge des grands axes d’échanges, fait depuis quelques temps déjà l’objet d’une attention particulière. Le massif vosgien n’échappe pas à ce phénomène. En écho aux travaux déjà réalisés sur les hautes-chaumes et le versant alsacien du massif, une équipe pluridisciplinaire tente de mesurer, sur la longue durée, la dynamique d’un espace forestier du versant lorrain. Le choix, comme objet d'étude, du massif du Fossard, qui domine le piémont occidental du massif et s'étend sur près de 150 km² entre Epinal et Remiremont (Vosges), résulte de son lien étroit, topographique et historique, avec cette dernière ville née d'une abbaye fondée au VIIe siècle dans un castrum tardo-antique perché, à 670 m d'altitude, à l'extrémité méridionale du relief.Dans ce secteur de moyenne montagne au relief contrasté où les grès superficiels côtoient des affleurements cristallins, la question se posait de savoir si la forêt qui s'est développée après la disparition des glaciers, vers le dixième millénaire avant notre ère, a subi depuis le Néolithique, les mêmes alternances de défrichements et de reprises que d’autres. Au cours du premier millénaire, reste-t-elle un espace réservé aux activités cynégétiques des puissants ou, au contraire, n'est-elle impactée qu’à partir du VIIe siècle, comme le laisse supposer le récit des vies des saints fondateurs de l’abbaye de Remiremont, par l'activité des moines défricheurs ? L'abbaye y a-t-elle développé de nouveaux modèles de gestion du sol ? A-t-elle favorisé le peuplement du massif par des essartages nombreux qui auraient donné le nom « Fossard » bien avant sa conquête à compter du XVIe siècle, mise en évidence par les historiens modernistes ? Autant d'interrogations, qui, grâce à une cartographie LiDAR réalisée pour l’occasion et une approche pluridisciplinaire mêlant géologie, géomorphologie, botanique, pédologie, histoire, archéologie et onomastique, devraient trouver des éléments de réponses susceptibles de mieux appréhender les phases d’anthropisation de cette « montagne-forêt », comme on s’est plu à qualifier le massif vosgien

    The ATLAS project - XII : Recovery of the mass-to-light ratio of simulated early-type barred galaxies with axisymmetric dynamical models

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    We investigate the accuracy in the recovery of the stellar dynamics of barred galaxies when using axisymmetric dynamical models. We do this by trying to recover the mass-to-light ratio (M/L) and the anisotropy of realistic galaxy simulations using the Jeans Anisotropic Multi-Gaussian Expansion (JAM) modelling method. However, given that the biases we find are mostly due to an application of an axisymmetric modelling algorithm to a non-axisymmetric system and in particular to inaccuracies in the deprojected mass model, our results are relevant for general axisymmetric modelling methods. We run N-body collisionless simulations to build a library with various luminosity distribution, constructed to mimic real individual galaxies, with realistic anisotropy. The final result of our evolved library of simulations contains both barred and unbarred galaxies. The JAM method assumes an axisymmetric mass distribution, and we adopt a spatially constant M/L and anisotropy distributions. The models are fitted to two-dimensional maps of the second velocity moments of the simulations for various viewing angles [position angle (PA) of the bar and inclination of the galaxy]. We find that the inclination is generally well recovered by the JAM models, for both barred and unbarred simulations. For unbarred simulations the M/L is also accurately recovered, with negligible median bias and with a maximum one of just ?(M/L) < 1.5 per cent when the galaxy is not too close to face on. At very low inclinations () the M/L can be significantly overestimated (9 per cent in our tests, but errors can be larger for very face-on views). This is in agreement with previous studies. For barred simulations the M/L is on average (when PA = 45 degrees) essentially unbiased, but we measure an over/underestimation of up to ?(M/L) = 15 per cent in our tests. The sign of the M/L bias depends on the PA of the bar as expected: overestimation occurs when the bar is closer to end-on, due to the increased stellar motion along the line-of-sight, and underestimation otherwise. For unbarred simulations, the JAM models are able to recover the mean value of the anisotropy with bias , within the region constrained by the kinematics. However when a bar is present, or for nearly face-on models, the recovered anisotropy varies wildly, with biases up to ?beta z similar to 0.3.Peer reviewe
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