INTRODUCING A FRAMEWORK FOR CONFLATING ROAD NETWORK DATA WITH SEMANTIC WEB TECHNOLOGIES

Road network asset management is a challenging task as many data sources with different road asset location accuracies are available. In Australia and New Zealand transport agencies are investigating into harmonisation of road asset data, whereby two or more data sets are merged to create a new data set. Currently, identifying relations between road assets of the same meaning is not always possible, as road authorities of these countries use their own data structures and standards. This paper employs SemanticWeb Technologies, such as RDF/Turtle ontologies and semantic rules to enable road network conflation (merge multiple data sets without creating a new data set) as a first step towards data harmonisation by means of information exchange, and shifts road network data from intersections and road nodes to data sets considering the accuracy of the data sets in the selected area. The data integration from GeoJSON into RDF/Turtle files is processed with Python. A geographic coordinates shifting algorithm reads unique data entries that have been extracted from RDF/Turtle into JSON-LD and saves the processed data in their origin file format, so that a closed data flow can be approached

Performance of Layer-by-Layer-Modified Multibore® Ultrafiltration Capillary Membranes for Salt Retention and Removal of Antibiotic Resistance Genes

Polyether sulfone Multibore® ultrafiltration membranes were modified using polyelectrolyte multilayers via the layer-by-layer (LbL) technique in order to increase their rejection capabilities towards salts and antibiotic resistance genes. The modified capillary membranes were characterized to exhibit a molecular weight cut-off (at 90% rejection) of 384 Da. The zeta-potential at pH 7 was −40 mV. Laboratory tests using single-fiber modified membrane modules were performed to evaluate the removal of antibiotic resistance genes; the LbL-coated membranes were able to completely retain DNA fragments from 90 to 1500 nt in length. Furthermore, the pure water permeability and the retention of single inorganic salts, MgSO$_{4}$, CaCl$_{2}$ and NaCl, were measured using a mini-plant testing unit. The modified membranes had a retention of 80% toward MgSO$_{4}$ and CaCl$_{2}$ salts, and 23% in case of NaCl. The modified membranes were also found to be stable against mechanical backwashing (up to 80 LMH) and chemical regeneration (in acidic conditions and basic/oxidizing conditions)

Isotope Effects on Delayed Annihilation Time Spectra of Antiprotonic Helium Atoms in Low-Temperature Gas

The delayed annihilation time spectra (DATS) of antiprotonic helium atoms have been studied in isotopically pure low temperature ^3He and ^4He gas at various densities. The DATS taken at 5.8~K and 400~mbar are very similar in shape except for i) a small difference in the time scale and ii) the presence of a distinct fast decay component in the case of ^3He. The ratio of overall trapping times (mean lifetimes against annihilation), R = T_{\mathrm{trap}}(\mbox{^{4}He})/T_{\mathrm{trap}}(\mbox{^{3}He}), has been determined to be 1.144 \pm 0.009, which is in good agreement with a theoretical estimate yielding R = [(M^*(\mbox{\overline{\mathrm{p}}}\mbox{^{4}He})/ M^*(\mbox{\overline{ \mathrm{p}}}\mbox{^{3}He})]^2=1.14, where M^* denotes the reduced mass of the \mbox{\overline{\mathrm{p}}}\mbox{He^{++}}\ system. The presence of a short-lived component with a lifetime of (0.154\pm 0.007)\ \mbox{\mus} in the case of \mbox{^{3}He}\ suggests that the \mbox{\overline{\mathrm{p}}}\mbox{^{3}He^{+}}\ atom has a state of intermediate lifetime on the border between a metastable zone and an Auger-dominated short-lived zone. The fraction of antiprotons trapped in metastable states at 5.8~K and 400~mbar is lower by 22.2(4)\% for \mbox{^{3}He}\ than for \mbox{^{4}He}. All the data can be fitted fai

Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

Background Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs. Methods Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families. Results We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint. Conclusion This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes

Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

Abstract Background Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs. Methods Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families. Results We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint. Conclusion This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12- q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice

Identification of pathogenic variant enriched regions across genes and gene families

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene-family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2871 gene-family protein sequence alignments involving 9990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 76,153 missense variants from patients. With this gene-family approach, we identified 465 regions enriched for patient variants spanning 41,463 amino acids in 1252 genes. As a comparison, by testing the same genes individually, we identified fewer patient variant enriched regions, involving only 2639 amino acids and 215 genes. Next, we selected de novo variants from 6753 patients with neurodevelopmental disorders and 1911 unaffected siblings and observed an 8.33-fold enrichment of patient variants in our identified regions (95% C.I. = 3.90-Inf, P-value= 2.72 x 10(-11)). By using the complete ClinVar variant set, we found that missense variants inside the identified regions are 106-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 106.15, 95% C.I = 70.66-Inf, P-value <2.2x10(-16)). All pathogenic variant enriched regions (PERs) identified are available online through "PER viewer," a user-friendly online platform for interactive data mining, visualization, and download. In summary, our gene-family burden analysis approach identified novel PERs in protein sequences. This annotation can empower variant interpretation.Peer reviewe