30 research outputs found
The cross-sectional GRAS sample: A comprehensive phenotypical data collection of schizophrenic patients
<p>Abstract</p> <p>Background</p> <p>Schizophrenia is the collective term for an exclusively clinically diagnosed, heterogeneous group of mental disorders with still obscure biological roots. Based on the assumption that valuable information about relevant genetic and environmental disease mechanisms can be obtained by association studies on patient cohorts of ≥ 1000 patients, if performed on detailed clinical datasets and quantifiable biological readouts, we generated a new schizophrenia data base, the GRAS (Göttingen Research Association for Schizophrenia) data collection. GRAS is the necessary ground to study genetic causes of the schizophrenic phenotype in a 'phenotype-based genetic association study' (PGAS). This approach is different from and complementary to the genome-wide association studies (GWAS) on schizophrenia.</p> <p>Methods</p> <p>For this purpose, 1085 patients were recruited between 2005 and 2010 by an invariable team of traveling investigators in a cross-sectional field study that comprised 23 German psychiatric hospitals. Additionally, chart records and discharge letters of all patients were collected.</p> <p>Results</p> <p>The corresponding dataset extracted and presented in form of an overview here, comprises biographic information, disease history, medication including side effects, and results of comprehensive cross-sectional psychopathological, neuropsychological, and neurological examinations. With >3000 data points per schizophrenic subject, this data base of living patients, who are also accessible for follow-up studies, provides a wide-ranging and standardized phenotype characterization of as yet unprecedented detail.</p> <p>Conclusions</p> <p>The GRAS data base will serve as prerequisite for PGAS, a novel approach to better understanding 'the schizophrenias' through exploring the contribution of genetic variation to the schizophrenic phenotypes.</p
Conversion of hydrocarbons into nitriles by catalytic nitroxidation
Hydrocarbons can be transformed into nitriles with high selectivities using nitric oxide as a reactant and supported nickel, chromium, iron or lead-oxides as the catalysts. Binary and ternary mixed oxide catalysts have shown good activities and stabilities with time on stream. The reaction follows a redox mechanism for all catalysts used as well as for all the hydrocarbons converted. Recently developed catalysts are as active and selective with aliphatics as with aromatics. Two main supports, Al2O3 and Si02, and their combinations, have been utilized. Also, support additives like MgO have been evaluated
Bimetallic FeCo nanocrystals supported on highly porous silica aerogels as fischer-tropsch catalysts
In this work, nanocomposites constituted of FeCo alloy nanoparticles dispersed on a highly porous silica aerogel have been designed as catalysts for low temperature Fischer-Tropsch synthesis. The catalysts were characterized by XRD, TEM, N 2 physisorption and SEM analysis. A high catalytic activity with CO conversions up to 95 % has been obtained, with enhanced selectivity for the C 2-C 4 hydrocarbons