Diverse roles of androgen receptor (AR) domains in AR-mediated signaling

Androgens control male sexual development and maintenance of the adult male phenotype. They have very divergent effects on their target organs like the reproductive organs, muscle, bone, brain and skin. This is explained in part by the fact that different cell types respond differently to androgen stimulus, even when all these responses are mediated by the same intracellular androgen receptor. To understand these tissue- and cell-specific readouts of androgens, we have to learn the many different steps in the transcription activation mechanisms of the androgen receptor (NR3C4). Like all nuclear receptors, the steroid receptors have a central DNA-binding domain connected to a ligand-binding domain by a hinge region. In addition, all steroid receptors have a relatively large amino-terminal domain. Despite the overall structural homology with other nuclear receptors, the androgen receptor has several specific characteristics which will be discussed here. This receptor can bind two types of androgen response elements (AREs): one type being similar to the classical GRE/PRE-type elements, the other type being the more divergent and more selective AREs. The hormone-binding domain has low intrinsic transactivation properties, a feature that correlates with the low affinity of this domain for the canonical LxxLL-bearing coactivators. For the androgen receptor, transcriptional activation involves the alternative recruitment of coactivators to different regions in the amino-terminal domain, as well as the hinge region. Finally, a very strong ligand-induced interaction between the amino-terminal domain and the ligand-binding domain of the androgen receptor seems to be involved in many aspects of its function as a transcription factor. This review describes the current knowledge on the structure-function relationships within the domains of the androgen receptor and tries to integrate the involvement of different domains, subdomains and motifs in the functioning of this receptor as a transcription factor with tissue- and cell-specific readouts

Mechanisms Establishing TLR4-Responsive Activation States of Inflammatory Response Genes

Precise control of the innate immune response is required for resistance to microbial infections and maintenance of normal tissue homeostasis. Because this response involves coordinate regulation of hundreds of genes, it provides a powerful biological system to elucidate the molecular strategies that underlie signal- and time-dependent transitions of gene expression. Comprehensive genome-wide analysis of the epigenetic and transcription status of the TLR4-induced transcriptional program in macrophages suggests that Toll-like receptor 4 (TLR4)-dependent activation of nearly all immediate/early- (I/E) and late-response genes results from a sequential process in which signal-independent factors initially establish basal levels of gene expression that are then amplified by signal-dependent transcription factors. Promoters of I/E genes are distinguished from those of late genes by encoding a distinct set of signal-dependent transcription factor elements, including TATA boxes, which lead to preferential binding of TBP and basal enrichment for RNA polymerase II immediately downstream of transcriptional start sites. Global nuclear run-on (GRO) sequencing and total RNA sequencing further indicates that TLR4 signaling markedly increases the overall rates of both transcriptional initiation and the efficiency of transcriptional elongation of nearly all I/E genes, while RNA splicing is largely unaffected. Collectively, these findings reveal broadly utilized mechanisms underlying temporally distinct patterns of TLR4-dependent gene activation required for homeostasis and effective immune responses

La motilite chez le dinoflagelle evolue Noctiluca scintillans McCartney : organisation structurale, regulation ionique, caracterisation biochimique et immunologique des proteines corticales

SIGLECNRS T 59948 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Is combination of UVC and H2O2 effective to remove estrogens from water?

International audienceWater pollution is of major concern in France. Half of water resources was still not meeting the European quality requirement in 2012. Moreover, recent progresses in analytical chemistry have identified numerous micropollutants in Wastewater Treatment Plant (WTP) discharge coming from urban, agricultural or industrial activities. Amongst hundreds of micropollutants, estrogenic compounds were shown to cause endocrine disruption in fish at very low doses [3] and suspected to impact human fertility [4]. Therefore, WTP upgrade is needed to eliminate these endocrine disruptors. Advanced oxidation processes were shown to eliminate up to 80% of targeted micropollutants [6]. However small and middle sized WTP (< 10000 equivalent inhabitants) are poorly equipped despite representing 90% of the overall French WTP [7]. Advanced Oxidation Processes (AOPs), based on the generation of highly reactive hydroxyl radicals for the unselective oxidation of chemical pollutants can be an adequate solution. This study aims at developing a cost-effective UV/H₂O₂ advance oxidation process (AOP) in order to reduce estrogenic activity in small and middle sized WTP discharge. Experiments were conducted at 20°C with a commercial UV reactor (COMAP WT) and a 55W low pressure lamp (Phillips) emitting at 254nm. Local tap water (Lyon, France) was added in a 50L glass tank and circulated at a flow rate of 40L/min in a closed system. A mixture of Estrone (E1), β-Estradiol (E2), and α-ethynyl estradiol (EE2) was added at 5µM and degradation rates were measured during either UV (photolysis) or UV + H₂O₂ treatments over 60min. Samples were taken every 10 minutes and analyzed by HPLC. Three different concentrations of H₂O₂ were tested: 10, 50 or 100mg/L. First results showed a low degradation of E2 and EE2 by photolysis after 60 min exposure (< 20%) in tap water but E1 was well degraded (up to 80%). When adding H₂O₂, every hormones degradation rate were significantly improved. Degradation rate reached 80% for E1 and 90% for E2 and EE2 at 10mg/L H₂0₂. Total degradation was both reached with 50mg/L and 100mg/L H₂0₂. These results pointed out that estrogens removal can be highly enhanced by combining UV and H₂O₂. Further investigations are needed to test this process on treated water at environmental concentrations

Comparison of UV/H2O2 and UV/S2O82- photolysis efficiency for the removal of estrogens in treated wastewater: chemical and biological assessment

International audienc

Evidence for common epitopes among proteins of the membrane skeleton of a ciliate, an euglenoid and a dinoflagellate.

International audienceThe cytoskeleton of many protists comprises an extensive submembranous epiplasm which contributes to cell shape and integration of cell membranes with underlying structures according to the species-specific cortical architecture. Using various extraction procedures, epiplasm-enriched fractions have been isolated from the ciliate Pseudomicrothorax dubius, the euglenoid Euglena acus and the dinoflagellate Noctiluca scintillans. Comparative gel electrophoretic analysis of such preparations reveals heterogeneity of protein composition, the major polypeptides differing in size. Antibodies raised against epiplasmic proteins from these three organisms have permitted the confirmation of submembranous localization of the antigens by immunoelectron microscopy. Heterologous reactions performed by means of combined immunocytochemical and immunoblotting procedures indicate the existence of common epitopes among major proteins making up the bulk of the epiplasm of the three species examined. These findings suggest that proteins of the epiplasm have significantly diverged during evolution while conserving structural domains essential for their cytoskeletal function. It is postulated that these common domains may underly the ability of epiplasmic proteins to assemble into an ordered spatial organization, typical of the highly differentiated cortex of unicellular micro-organisms

Reprogrammation des cellules MCF7 issues de cancer du sein par hyperhydroxymethylation de l’ADN

Reprogrammation des cellules MCF7 issues de cancer du sein par hyperhydroxymethylation de l’AND. EpiPhase 201

The potential for using alcohol and tobacco taxes to fund prevention and control of noncommunicable diseases in Caribbean Community countries

Objectives. To determine the extent to which increased taxes on alcohol and tobacco products in Caribbean Community (CARICOM) countries might successfully reduce consumption of those products and raise revenues, which could then be channeled into noncommunicable disease (NCD) prevention and control initiatives. Methods. The Tobacco Tax Simulation (TaXSiM) model, which was developed by the World Health Organization (WHO), was used to simulate the impact of tax changes on alcohol and tobacco products in three CARICOM member countries. Estimates of the NCD response cost in the 15 countries that are full members of CARICOM were also produced. Results. For the 15 full-member CARICOM countries, the revenues from increased excise taxes on beer, rum, and cigarettes associated with a 5.0% reduction in consumption were estimated at US$86.32 million. This expected revenue intake from excise taxes exceeded the estimated US$ 52.73 million required to respond to NCDs in those 15 CARICOM countries. The amount also exceeds US$ 78.87 million, which will be required if there is a 50.0% increase in the per capita NCD response cost. Conclusions. The findings showed that for CARICOM countries, there is a substantial potential for revenue generation from increases in taxes on alcohol and tobacco, as well as for decreases in consumption of the products. Although increased taxes on alcohol and cigarettes can sufficiently cover the cost of controlling NCDs among CARICOM countries, a comprehensive response also requires widespread participation from various sectors

Fouille de motifs et CRF pour la reconnaissance de symptômes dans les textes biomédicaux

National audiencePattern mining and CRF for symptoms recognition in biomedical texts. In this paper, we tackle the issue of symptoms recognition in biomedical texts. There is not much attention to this problem in the literature and it does not exist to our knowledge an annotated dataset to train a model. We propose two weakly-supervised approaches to extract these entities. The first is based on pattern mining and introduces a new constraint based on semantic similarity. The second represents the task as sequence labeling using CRF (Conditional Random Fields). We describe our experiments which show that the two approaches are complementary in terms of quantification (recall and precision). We further show that their combination significantly improves the results.Dans cet article, nous nous intéressons à l'extraction d'entités médicales de type symptôme dans les textes biomédicaux. Cette tâche est peu explorée dans la littérature et il n'existe pas à notre connaissance de corpus annoté pour entraîner un modèle d'apprentissage. Nous proposons deux approches faiblement supervisées pour extraire ces entités. Une première est fondée sur la fouille de motifs et introduit une nouvelle contrainte de similarité sémantique. La seconde formule la tache comme une tache d'étiquetage de séquences en utilisant les CRF (champs conditionnels aléatoires). Nous décrivons les expérimentations menées qui montrent que les deux approches sont complémentaires en termes d'évaluation quantitative (rappel et précision). Nous montrons en outre que leur combinaison améliore sensiblement les résultats

Weakly-supervised Symptom Recognition for Rare Diseases in Biomedical Text

International audienceIn this paper, we tackle the issue of symptom recognition for rare diseases in biomedical texts. Symptoms typically have more complex and ambiguous structure than other biomedical named entities. Furthermore , existing resources are scarce and incomplete. Therefore, we propose a weakly-supervised framework based on a combination of two approaches: sequential pattern mining under constraints and sequence labeling. We use unannotated biomedical paper abstracts with dictionaries of rare diseases and symptoms to create our training data. Our experiments show that both approaches outperform simple projection of the dictionaries on text, and their combination is beneficial. We also introduce a novel pattern mining constraint based on semantic similarity between words inside patterns