Showing results 1201 to 1220 on 1252 in total
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Courant 2005, le constat de contamination des poissons du Rhône par les PCB près de Lyon a entraîné une série d'investigations conduisant à l'interdiction de consommation sur un secteur allant de l'amont de Lyon jusqu'à la mer Méditerranée. Alors qu'un lien a pu être mis en évidence entre la contamination des poissons et celle des sédiments, un projet de recherche a été élaboré dans le but de développer un modèle trophique décrivant le transfert des PCB du sédiment à des espèces « clés » de poissons. Des analyses PCB ont alors été réalisées sur 3 espèces de poissons (le barbeau, le chevaine et la brème, espèces longévives suffisamment communes pour être retrouver facilement dans le Rhône et susceptibles d'accumuler des PCB) et sur différentes espèces d'invertébrés faisant partie du régime alimentaire de ces poissons. Trois sites ont été échantillonnés : (1) un site de « référence », en amont de Lyon et de le première zone contaminée ; (2) un site proche de Lyon et (3) un site en aval de Lyon. A partir de l'analyse des contenus stomacaux des poissons et des données en isotopes stables (Carbone et Azote) mesurées sur les poissons et leurs potentielles sources de nourriture (invertébrés et plantes aquatiques), le réseau trophique de ces espèces a pu être décrit. Par ailleurs, les données de contamination observées ont montré un gradient de contamination des poissons entre l'amont et l'aval de Lyon, avec peu (ou pas) d'individus au dessus du seuil sanitaire (fixé à 8pg TEQ/g poids frais) en amont, et une majorité (voire une totalité) d'individus au dessus du seuil en aval. La description de cette contamination en fonction de différents facteurs explicatifs sera présentée, ainsi que les principes du modèle trophique en cours de développement. Séminaire en Français - Seminar in French
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Cumulative culture requires individuals to build upon the knowledge of previous generations such that trait complexity/efficiency evolves across generations. Such cumulative cultural evolution is arguably unique to humans and is widely held to be responsible for our outstanding success in colonising virtually every terrestrial habitat on the planet and solving countless ecological, social and technological challenges. In contrast, social learning (learning from others) underlies the wide-spread occurrence of traditions or culture in all animals. Although social learning is a cheap and efficient form of learning, it is not adaptive to use social information indiscriminately due to its potential unreliability. Thus it is predicted that social learning strategies (heuristics / transmission biases) should evolve enabling individuals to avoid the costs associated with asocial learning and determine when they should use social information and from whom they should acquire it. I shall review several of my recent empirical studies, with young children and non-human primates, highlighting the role of socio-cognition, and in particular the potential role of transmission biases, in humanity's striking capacity for cumulative culture. (page web: https://www.dur.ac.uk/research/directory/staff/?id=5444)
Thèse de Sébastien Lambert le vendredi 29 novembre 2019 à 13 h 30, BU salle de conférence (La Doua)
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Mitochondrial genomes (mtDNA) are normally maternally inherited and encode for subunits of respiratory chain complexes and ATP synthase among others. The integrity of mtDNA is crucial for cellular energetic and redox homeostasis, and mtDNA mutations are associated with modifications of individual fitness and longevity. Bivalves are the only zoological group in which Doubly Uniparental Inheritance (DUI), characterized by the presence of two divergent mitochondrial genomes within different tissues of male individuals, is frequently observed. The F-genome, maternally inherited, is found in somatic tissue and female gonads whereas the M-mtDNA is found in male gonadic tissue only. The clam Arctica islandica is widely distributed throughout the North Atlantic shelf regions. Due to different environmental regimes (salinity, temperature, oxygen), the maximum lifespan of its populations varies between >500 years around Iceland and 35 years in the Baltic Sea. I will present our recent investigations that describe for the first time the existence of the DUI system in Arctica islandica. Based on 16S and cytochrome b markers, we highlight the presence of an M-genome in male gonads in individuals belonging to Baltic and North Sea populations. The two genomes show a low level of sequence divergence compared to other DUI species, around 6-8% at the nucleotide level. Whilst the analysis of mitochondrial markers generally indicated genetically homogeneity of all North Atlantic populations, they further reveal few clam individuals that carry a "divergent" mtDNA haplotype, resembling the M-genome. These individuals occurred however exclusively in the Icelandic population. Unlike the M-genome, which is confined to male gonadic tissue in DUI species, this "divergent" mtDNA occurs in somatic tissues from 20% of individuals of both sexes. In association with transcriptomic and biochemical data, we will discuss the possible impacts of this uncommon mitochondrial genome on Arctica islandica biology and cellular physiology. This study will enhance the understanding of the role of DUI and mtDNA in general for fitness, aging and adaptation of bivalves.
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Biological networks of large dimensions, with their diagram of interactions, are often well represented by a Boolean model with a family of logical rules. An advantage of Boolean and discrete modelling is the possibility of fully characterizing all qualitative dynamical trajectories of a particular network, based simply on the structure of links and interactions between nodes. A biological network may have different qualitative behaviours in response to different conditions. For instance, in response to different inputs, the system may have a single steady state, or multiple steady states, or exhibit oscillatory behaviour. In this context, using the asynchronous transition graph of the Boolean network, we have developed a method for identifying the groups of active or operational interactions that are responsible for a given dynamic behaviour.As an example, a model of an apoptosis network will be analysed. Two core groups of elements and interactions are identified: they correspond to two different mechanisms that may be used by the cell for the decision between apoptosis or cell survival.
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The turn from the 20th to the 21st Century was marked by a drastic change in the scale at which biologists study regulatory networks. In the 1990, a PhD student could spend years analysing the regulation of one particular gene by one or a few transcription factors. Microarray technologies enabled monitoring the expression of all the genes of an organism in a single experiment (transcriptome arrays), and to lead genome-wide location analysis to report supposedly exhaustive lists of transcription factor binding sites. Next Generation Sequencing amplified the movement, and many labs are now combining ChIP-seq and RNA-seq experiments to get a wide view on transcription factor binding locations, histone modifications, and transcriptional responses to a multitude of conditions, cell types, developmental stages, etc. In the first part of the talk, I will present some of the bioinformatics approaches and tools that we developed to analyse regulatory motifs from various types of high-throughput data (e.g. co-expression clusters, ChIP-seq peaks, replication origins).At the light of the evolution of the domain, I would also like to address a more general question about the insights gained from high-throughput approaches on fundamental mechanisms of regulation. Indeed, it implicitly became standard to consider that a typical high-throughput experiments should return thousands of significant features (differentially expressed genes, TF binding sites, active enhancers). This however does not fit with our classical models, were transcription factors would turn on or off specific sets of target genes ("regulatory switches"), thereby forming regulatory networks whose behaviour was understandably determined by feedback loops. How can we conciliate the undeniable robustness of regulatory networks with the apparent noisiness of binding and transcription profiles?
Thèse Cecilia Coimbra Klein - mardi 12 novembre 2013 à 14 h 30, amphithéâtre CNRS
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