11 research outputs found

    Comprehensive analysis via exome sequencing uncovers genetic etiology in autosomal recessive nonsyndromic deafness in a large multiethnic cohort

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    Purpose:Autosomal recessive nonsyndromic deafness (ARNSD) is characterized by a high degree of genetic heterogeneity, with reported mutations in 58 different genes. This study was designed to detect deafness-causing variants in a multiethnic cohort with ARNSD by using whole-exome sequencing (WES).Methods:After excluding mutations in the most common gene, GJB2, we performed WES in 160 multiplex families with ARNSD from Turkey, Iran, Mexico, Ecuador, and Puerto Rico to screen for mutations in all known ARNSD genes.Results:We detected ARNSD-causing variants in 90 (56) families, 54 of which had not been previously reported. Identified mutations were located in 31 known ARNSD genes. The most common genes with mutations were MYO15A (13), MYO7A (11), SLC26A4 (10), TMPRSS3 (9), TMC1 (8), ILDR1 (6), and CDH23 (4). Nine mutations were detected in multiple families with shared haplotypes, suggesting founder effects.Conclusion:We report on a large multiethnic cohort with ARNSD in which comprehensive analysis of all known ARNSD genes identifies causative DNA variants in 56 of the families. In the remaining families, WES allows us to search for causative variants in novel genes, thus improving our ability to explain the underlying etiology in more families.Genet Med 18 4, 364-371. © American College of Medical Genetics and Genomics

    Equilibrium adsorption measurements of pure Nitrogen, Carbon Dioxide, and Methane on a Carbon molecular sieve at cryogenic temperatures and high pressures†

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    A detailed experimental study of the adsorption behavior at equilibrium of pure nitrogen, methane, and carbon dioxide gases on a commercial carbon molecular sieve (Shirasagi MSC 3K-161) is reported at temperatures between 115 K to 323 K and pressures up to 5 MPa. A volumetric-type apparatus was used to obtain over 200 excess (Gibbs) adsorption capacity data over this range of pressure and temperature with an estimated uncertainty of 4 %. The absolute adsorption isotherms were type I in the IUPAC classification with the adsorption capacity at constant pressure increasing significantly with decreasing temperature. For each gas, the adsorption data were regressed to a four parameter Toth equation to represent the temperature and pressure dependence of the data with a relative standard uncertainty of 4 %. The optimized parameters from the Toth equation included the isosteric enthalpies of adsorption that were 17 kJ·mol−1, 27 kJ·mol−1, and 18 kJ·mol−1 for N2, CO2, and CH4, respectively

    Volumetric adsorption measurements of N 2, CO 2, CH 4, and a CO 2 + CH 4 mixture on a natural chabazite from (5 to 3000) kPa

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    We report here measured adsorption capacities for a natural chabazite zeolite at pressures ranging from (5 to 3000) kPa, at temperatures of (244 and 305) K, for pure N-2, CH4, and CO2, and for gas mixtures of CH4 + CO2. The pure gas data sets from this work and from the literature were in good agreement (10 %) and were regressed to Toth models over a wide range of pressure and temperature. We show that extrapolation of models that were fit only to low pressure data (below 120 kPa) can lead to a 30 % deviation in adsorption capacities predicted at high pressures. Similarly, models fit only to high pressure pure fluid data resulted in unreliable predictions for mixture adsorption capacities particularly when the component's partial pressure was low. The experimental results indicate that, while the chabazite is unlikely to be useful for N-2/CH4 separation, it may have potential for removing bulk CO2 from natural gas, particularly at low temperatures. A feed gas mixture of 0.95CH(4) + 0.05CO(2) placed in contact with the chabazite resulted in equilibrium vapor phases with CO2 mole fractions of about (0.0013 and 0.0002) at (305 and 244) K, respectively. The ideal adsorbed solution theory was used to successfully describe the observed mixture behavior, although it was found to be sensitive to the data range over which the pure fluid models were regressed
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