Autism genetic database (AGD): a comprehensive database including autism susceptibility gene-CNVs integrated with known noncoding RNAs and fragile sites

<p>Abstract</p> <p>Background</p> <p>Autism is a highly heritable complex neurodevelopmental disorder, therefore identifying its genetic basis has been challenging. To date, numerous susceptibility genes and chromosomal abnormalities have been reported in association with autism, but most discoveries either fail to be replicated or account for a small effect. Thus, in most cases the underlying causative genetic mechanisms are not fully understood. In the present work, the Autism Genetic Database (AGD) was developed as a literature-driven, web-based, and easy to access database designed with the aim of creating a comprehensive repository for all the currently reported genes and genomic copy number variations (CNVs) associated with autism in order to further facilitate the assessment of these autism susceptibility genetic factors.</p> <p>Description</p> <p>AGD is a relational database that organizes data resulting from exhaustive literature searches for reported susceptibility genes and CNVs associated with autism. Furthermore, genomic information about human fragile sites and noncoding RNAs was also downloaded and parsed from miRBase, snoRNA-LBME-db, piRNABank, and the MIT/ICBP siRNA database. A web client genome browser enables viewing of the features while a web client query tool provides access to more specific information for the features. When applicable, links to external databases including GenBank, PubMed, miRBase, snoRNA-LBME-db, piRNABank, and the MIT siRNA database are provided.</p> <p>Conclusion</p> <p>AGD comprises a comprehensive list of susceptibility genes and copy number variations reported to-date in association with autism, as well as all known human noncoding RNA genes and fragile sites. Such a unique and inclusive autism genetic database will facilitate the evaluation of autism susceptibility factors in relation to known human noncoding RNAs and fragile sites, impacting on human diseases. As a result, this new autism database offers a valuable tool for the research community to evaluate genetic findings for this complex multifactorial disorder in an integrated format. AGD provides a genome browser and a web based query client for conveniently selecting features of interest. Access to AGD is freely available at <url>http://wren.bcf.ku.edu/</url>.</p

Fluorescence optical analysis method for assessing homogeneity of granular mixtures

This paper presents a method of optical fluorescence analysis for the evaluation of homogeneity of multicomponent grain mixtures. This method is based on the evaluation of the content of fluorescent marker. Maize with two degrees of fineness d1 = 1.25 mm and d2 = 2.00 mm was used as a tracer. Maize was covered with Rhodamine B, which emits red light under the influence of ultraviolet radiation. The tracer was introduced into the mixture before the mixing process began. Nine multicomponent grain mixtures were used. The proportion of fluorescent maize was evaluated on the basis of computer image analysis. Additionally, the fraction of the tracer was evaluated using a control method (validation of the accuracy of the proposed method). The results indicate that the degree of the tracer’s fineness influences the results obtained. The use of fluorescent maize with particle size d2 = 2.00 mm allowed to obtain results which differed less from the control method. The average size of the difference in results ranged from 0.20-0.38 for the 2.00 mm tracer and 0.38-1.34 for the 1.25 mm tracer

Application of fluorescent markers for homogeneity assessment of grain mixtures based on maize content

The paper presents test results for the assessment of the tracer content in a three-component (green peas, sorghum, maize) feed mixture that is based on the fluorescent method. The homogeneity of mixtures was determined on the basis of the maize content (as the key component), which was treated with fluorescent substance: tinopal, rhodamine B, uranine and eosin. The key components were wet-treated with fluorescent substances with different concentrations. Feed components were mixed in a vertical funnel-flow mixer. 10 samples were collected from each mixed batch. Samples were placed in a chamber equipped with UV light and, then, an image recorded as BMP file was generated. The image was analysed by means of the software programme Patan. On the basis of the analyses conducted, data on the maize content marked with a fluorescent marker were obtained. Additionally, the content of the key component was determined in a conventional manner – using an analytical scale. Results indicate the possibility of using this method for homogeneity assessment of the three-component grain mixture. From these tests, fluorescent substances that can be applied in the case of maize as a key component, together with their minimum concentrations, were identified: tinopal 0.3%, rhodamine B 0.001%

Numerical studies on the influence of air staging on the temperature of flue gas and emission of gases in the combustion chamber of OP 230 boiler

The primary methods of reducing nitrogen oxides, despite the development of more advanced technologies, will continue to be the basis for NOx reduction. This paper presents the results of multivariate numerical studies on the impact of air staging on the flue gas temperature and composition, as well as on NOx emissions in a OP 230 boiler furnace. A numerical model of the furnace and the platen superheater was validated based on measurements using a 0-dimensional model of the boiler. Numerical simulations were performed using the ANSYS Workbench package. It is shown that changes in the distribution of air to OFA nozzles, the angle of the air outflow from the nozzles and the nozzle location involve a change in the flue gas temperature and in the volume of NOx and CO emissions at the furnace outlet