17 research outputs found

    A study of random laser modes in disordered photonic crystals

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    We studied lasing modes in a disordered photonic crystal. The scaling of the lasing threshold with the system size depends on the strength of disorder. For sufficiently large size, the minimum of the lasing threshold occurs at some finite value of disorder strength. The highest random cavity quality factor was comparable to that of an intentionally introduced single defect. At the minimum, the lasing threshold showed a super-exponential decrease with the size of the system. We explain it through a migration of the lasing mode frequencies toward the photonic bandgap center, where the localization length takes the minimum value. Random lasers with exponentially low thresholds are predicted.Comment: 4 pages, 4 figure

    Sequence Contexts That Determine the Pathogenicity of Base Substitutions at Position+3 of Donor Splice-Sites

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    Variations at position +3 of 5' splice-sites (5'ss) are reported to induce aberrant splicing in some cases but not in others suggesting that the overall nucleotidic environment can dictate the extent to which 5'ss are correctly selected. Functional studies of three variations identified in donor splice-sites of USH2A and PCDH15 genes sustain this assumption. To gain insights into this question, we compared the nucleotidic context of U2-dependent 5'ss naturally deviated (+3G, +3C, or +3T) from the +3A consensus with 5'ss for which a +3 variation (A>G, A>C, or A>T) was shown to induce aberrant splicing. Statistical differences were found between the two datasets, highlighting the role of one peculiar position in each context (+3G/+4A; +3C/-1G; and +3T/-1G). We provided experimental support to the biostatistical results through the analysis of a series of artificial mutants in reporter minigenes. Moreover, different 5' end-mutated U1 snRNA expression plasmids were used to investigate the importance of the position +3 and of the two identified compensatory positions -1 and +4 in the recognition of 5'ss by the U1 snRNP Overall, our findings establish general properties useful to Molecular geneticists to identify nucleotide substitutions at position +3 that are more likely to alter splicin

    Survey of the frequency of USH1 gene mutations in a cohort of Usher patients shows the importance of cadherin 23 and protocadherin 15 genes and establishes a detection rate of above 90%.

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    BACKGROUND: Usher syndrome, a devastating recessive disorder which combines hearing loss with retinitis pigmentosa, is clinically and genetically heterogeneous. Usher syndrome type 1 (USH1) is the most severe form, characterised by profound congenital hearing loss and vestibular dysfunction. OBJECTIVE: To describe an efficient protocol which has identified the mutated gene in more than 90% of a cohort of patients currently living in France. RESULTS: The five genes currently known to cause USH1 (MYO7A, USH1C, CDH23, PCDH15, and USH1G) were tested for. Disease causing mutations were identified in 31 of the 34 families referred: 17 in MYO7A, 6 in CDH23, 6 in PCDH15, and 2 in USH1C. As mutations in genes other than myosin VIIA form nearly 50% of the total, this shows that a comprehensive approach to sequencing is required. Twenty nine of the 46 identified mutations were novel. In view of the complexity of the genes involved, and to minimise sequencing, a protocol for efficient testing of samples was developed. This includes a preliminary linkage and haplotype analysis to indicate which genes to target. It proved very useful and demonstrated consanguinity in several unsuspected cases. In contrast to CDH23 and PCDH15, where most of the changes are truncating mutations, myosin VIIA has both nonsense and missense mutations. Methods for deciding whether a missense mutation is pathogenic are discussed. CONCLUSIONS: Diagnostic testing for USH1 is feasible with a high rate of detection and can be made more efficient by selecting a candidate gene by preliminary linkage and haplotype analysis

    PSI1 is responsible for the stearic acid enrichment that is characteristic of phosphatidylinositol in yeast

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    In yeast, both phosphatidylinositol and phosphatidylserine are synthesized from cytidine diphosphate-diacylglycerol. Because, as in other eukaryotes, phosphatidylinositol contains more saturated fatty acids than phosphatidylserine (and other phospholipids), it has been hypothesized that either phosphatidylinositol is synthesized from distinct cytidine diphosphate-diacylglycerol molecules, or that, after its synthesis, it is modified by a hypothetical acyltransferase that incorporates saturated fatty acid into neo-synthesized molecules of phosphatidylinositol. We used database search methods to identify an acyltransferase that could catalyze such an activity. Among the various proteins that we studied, we found that Psi1p (phosphatidylinositol stearoyl incorporating 1 protein) is required for the incorporation of stearate into phosphatidylinositol because GC and MS analyses of psi1Delta lipids revealed an almost complete disappearance of stearic (but not of palmitic acid) at the sn-1 position of this phospholipid. Moreover, it was found that, whereas glycerol 3-phosphate, lysophosphatidic acid and 1-acyl lysophosphatidylinositol acyltransferase activities were similar in microsomal membranes isolated from wild-type and psi1Delta cells, microsomal membranes isolated from psi1Delta cells are devoid of the sn-2-acyl-1-lysolysophosphatidylinositol acyltransferase activity that is present in microsomal membranes isolated from wild-type cells. Moreover, after the expression of PSI1 in transgenic psi1Delta cells, the sn-2-acyl-1-lysolysophosphatidylinositol acyltransferase activity was recovered, and was accompanied by a strong increase in the stearic acid content of lysophosphatidylinositol. As previously suggested for phosphatidylinositol from animal cells (which contains almost exclusively stearic acid as the saturated fatty acid), the results obtained in the present study demonstrate that the existence of phosphatidylinositol species containing stearic acid in yeast results from a remodeling of neo-synthesized molecules of phosphatidylinositol

    Analyse détaillée de 27 mois de fonctionnement de 6 zones de rejet végétalisée (ZRVs) de taille semi-industrielle : Projet BIOTRYTIS

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    Les Zones de Rejet VĂ©gĂ©talisĂ©es (ZRV) sont des amĂ©nagements placĂ©s entre la station de traitement des eaux usĂ©es et le milieu rĂ©cepteur. Les besoins en rĂšgles de conception et d’exploitation sont Ă  l’origine du projet BIOTRYTIS menĂ© par Irstea et financĂ© par l’AFB, l’Agence de l’eau Adour-Garonne et Bordeaux MĂ©tropole. Le site expĂ©rimental a Ă©tĂ© construit dans le cadre de ce projet Ă  BĂšgles et comprend 6 ZRV de taille semi-industrielle de 3 types diffĂ©rents (« prairie », « fossĂ© » et « autres ») alimentĂ©es par deux types d’eaux usĂ©es, et Ă©quipĂ©es spĂ©cifiquement pour rĂ©aliser des prĂ©lĂšvements d’eau et de solides (dĂ©pĂŽts, sols, vĂ©gĂ©taux). Il a Ă©tĂ© Ă©tudiĂ© finement pendant 27 mois, entre fin septembre 2015 et jusqu’à la fin 2017, en vue de dĂ©terminer l’efficacitĂ© des diffĂ©rents types de ZRV et l’influence du type d’eau appliquĂ©e, et aboutir aux performances d’élimination des compartiments eau, sol et plantes. Le site expĂ©rimental unique en France a fait l’objet d’expĂ©rimentations rĂ©guliĂšres telles que la caractĂ©risation des dĂ©bits et Ă©coulements dans le sol, la dĂ©termination du devenir des polluants (paramĂštres majeurs, micropolluants, bactĂ©riologie) dans l’eau de surface et dans le sol, et l’étude d’un indicateur lipidique pour Ă©valuer le stress des vĂ©gĂ©taux Ă  la pollution. Ce rapport fait suite au rapport de description dĂ©taillĂ©e du site expĂ©rimental publiĂ© en 2015 et aux diffĂ©rents rapports d’avancement internes au projet.Lorsque le temps de sĂ©jour est faible (moins d’une journĂ©e), les concentrations des paramĂštres physico-chimiques majeurs (DCO, MES, COT, ammonium, nitrates, phosphates, phosphore total), d’Escherichia coli et de la plupart des mĂ©taux et micropolluants organiques varient peu au passage de l’eau en surface des ZRV alimentĂ©es par l’eau nitrifiĂ©e. Seules les concentrations en aluminium et de quelques substances organiques (gemfibrozil, ritonavir, atĂ©nolol, diclofĂ©nac, gabapentine, nonylphĂ©nol) diminuent parfois de 50%. On note une augmentation des concentrations pour quelques pharmaceutiques et pour des molĂ©cules connues pour ĂȘtre des produits de dĂ©gradation (ex. estrone, NP1EC, PFOS). L’efficacitĂ© est plus marquĂ©e pour les ZRV alimentĂ©es par l’eau non-nitrifiĂ©e (eau plus concentrĂ©e en MES, DCO, nitrites, micropolluants biotransformables), toutefois l’eau sortant de ces ZRV reste de moins bonne qualitĂ© que l’eau ayant subi une Ă©tape de nitrification. Le rĂŽle des ZRV Ă©tudiĂ© Ă  principalement consistĂ© en la rĂ©duction des flux polluants par l’infiltration dans le sol. Contenant une fraction argileuse, le sol Ă©tudiĂ© a retenu 70 % des phosphates, 50 % de l’ammonium, le lithium et le rubidium, certains micropolluants organiques (hormones, alkylphĂ©nols et pharmaceutiques, certains pesticides). Les concentrations de plusieurs mĂ©taux dissous (manganĂšse, uranium, vanadium, cadmium) ont augmentĂ© lors du passage de l’eau dans le sol ou proche de certaines zones plus contaminĂ©es (relargage par le sol). Le suivi expĂ©rimental a dĂ©terminĂ© des infiltrations moyennes infĂ©rieures Ă  une dizaine de mm/h, diffĂ©renciĂ©es selon les endroits dans le sol, et maintenues au cours des trois ans de fonctionnement, ce qui s’explique par un dĂ©veloppement racinaire en profondeur. Dans le cas d’arrivĂ©es accidentelles de matiĂšres en suspension dans les mois ayant suivi la plantation des vĂ©gĂ©taux, nous avons constatĂ© un faible dĂ©veloppement racinaire dans le sol, et donc Ă  une moindre infiltration. Il est recommandĂ© de suivre la composition de l’eau du sol de façon Ă  dĂ©terminer le moment oĂč les sites d’adsorption du sol sont saturĂ©s. La durĂ©e de l’étude ne permettait pas de se concentrer sur ce point. Concernant les ZRV « autres » Ă©tanchĂ©es et remplies de matĂ©riaux rĂ©actifs (adsorbants), le charbon actif en grain a confirmĂ© les trĂšs bonnes performances pour les orthophosphates, l’ammonium, le COT, plusieurs mĂ©taux (Co, Cr, Cu, Fe, Mo, Mn, Pb, Se, U et V) et de nombreux micropolluants organiques (hormones, alkylphĂ©nols, pesticides, pharmaceutiques, perfluorĂ©s). Les ZRV garnies de zĂ©olite et d’argile expansĂ©e ont montrĂ© des performances intĂ©ressantes bien qu’infĂ©rieures Ă  celles du charbon actif. La zĂ©olite a peu d’effet sur les orthophosphates et l’ammonium, et prĂ©sente mĂȘme des relargages aprĂšs 18 mois de fonctionnement. L’argile expansĂ©e a retenu 40 % de phosphates et 20% de l’ammonium. Ces matĂ©riaux ont adsorbĂ© certains mĂ©taux (zĂ©olite : Ba, Sr et U ; argile expansĂ©e : Cu, Fe, et Zn). L’argile expansĂ©e a retenu partiellement plusieurs micropolluants organiques (hormones, pharmaceutiques, pesticides). Il est vivement recommandĂ© de suivre rĂ©guliĂšrement les performances de ces procĂ©dĂ©s, notamment pour dĂ©terminer lorsqu’il est nĂ©cessaire de renouveler les matĂ©riaux rĂ©actifs

    Démarche statistique pour la sélection des indicateurs par Random Forests pour la surveillance de la qualité des sols

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    The volume of data, and the large number of biological variables to be tested (one hundred), require analytical techniques, such as Random Forests, which can overcome the problem of multi-colinearity for the selection of indicators, sensitive to various factors. Random Forests methodology is appropriate for the selection of the most discriminant variables. So, we searched for the best way to select them, by bringing together all biological variables, representing the Microflora and Fauna. This approach focuses on impact indicators from the Bio2 program, indicators of flora and indicators of accumulation (snails) were not included. This work has been implemented on the three factors of discrimination : land use, metallic contamination levels and organic contamination levels. We grouped the most discriminating variables from each RF analysis. Linear discriminant analysis was then implemented for each factor, in order to develop a predictive model
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