Refine
Year of publication
Language
- English (1036)
Has Fulltext
- yes (1036)
Is part of the Bibliography
- no (1036)
Keywords
- Heavy Ion Experiments (20)
- Hadron-Hadron Scattering (11)
- Hadron-Hadron scattering (experiments) (11)
- Heavy-ion collision (6)
- LHC (6)
- ALICE experiment (4)
- Collective Flow (4)
- Jets (4)
- Quark-Gluon Plasma (4)
- Heavy Ions (3)
- Jets and Jet Substructure (3)
- pp collisions (3)
- Atmospheric chemistry (2)
- Beauty production (2)
- Charm physics (2)
- Experimental nuclear physics (2)
- Experimental particle physics (2)
- Heavy Quark Production (2)
- Lepton-Nucleon Scattering (experiments) (2)
- Particle Correlations and Fluctuations (2)
- Particle and resonance production (2)
- Particle correlations and fluctuations (2)
- Pb–Pb collisions (2)
- QCD (2)
- Single electrons (2)
- 4-FA (1)
- ALICE (1)
- ALICE detector (1)
- Anti-nuclei (1)
- Asian tiger mosquito (1)
- Biogeochemistry (1)
- Boosted Jets (1)
- Centrality Class (1)
- Centrality Selection (1)
- Climate-change impacts (1)
- Collective Flow, (1)
- Comparison with QCD (1)
- Dysgonomonas (1)
- Electron-pion identification (1)
- Electroweak interaction (1)
- Elliptic flow (1)
- Fibre/foam sandwich radiator (1)
- Hadron production (1)
- Hadron-Hadron Scattering Heavy (1)
- Hadron-hadron interactions (1)
- Hard Scattering (1)
- Heavy Ion Experiment (1)
- Heavy flavor production (1)
- Heavy flavour production (1)
- Heavy ions (1)
- Heavy-flavour decay muons (1)
- Heavy-flavour production (1)
- Inclusive spectra (1)
- Invariant Mass Distribution (1)
- Ionisation energy loss (1)
- Jet Physics (1)
- Jet Substructure (1)
- Material budget (1)
- Microbiota (1)
- Mid-rapidity (1)
- Minimum Bias (1)
- Monte Carlo (1)
- Multi-Parton Interactions (1)
- Multi-strange baryons (1)
- Multi-wire proportional drift chamber (1)
- Myotis bechsteinii (1)
- Neural network (1)
- Nyctalus leisleri (1)
- Particle and Resonance Production (1)
- Production Cross Section (1)
- Properties of Hadrons (1)
- Proton–proton (1)
- Quark Deconfinement (1)
- Quark Gluon Plasma (1)
- Quark Production (1)
- Quark gluon plasma (1)
- Quarkonium (1)
- Rapidity Range (1)
- Relativistic heavy ion physics (1)
- Relativistic heavy-ion collisions (1)
- Resolution Parameter (1)
- Sibling species (1)
- Single muons (1)
- Systematic Uncertainty (1)
- TR (1)
- Time Projection Chamber (1)
- Tracking (1)
- Transition radiation detector (1)
- Trigger (1)
- Vector Boson Production (1)
- Wolbachia (1)
- Xenon-based gas mixture (1)
- alleles (1)
- autism spectrum disorder (1)
- autistic disorder (1)
- automated radiotelemetry system (1)
- bats (1)
- behaviour (1)
- birds (1)
- copy number polymorphism (1)
- dE/dx (1)
- detector (1)
- experimental results (1)
- generalised additive models (1)
- genes (1)
- genetics (1)
- genome (1)
- genotype (1)
- genotype determination (1)
- heavy ion experiments (1)
- machine learning (1)
- neurocognition (1)
- novel psychoactive substance (1)
- phase-1 (1)
- phenotype (1)
- quark gluon plasma (1)
- random forest (1)
- safety (1)
- single nucleotide polymorphism (1)
- small animals (1)
- spectra (1)
- tRackIT (1)
Institute
Background: ClC-7 is a ubiquitous transporter which is broadly expressed in mammalian tissues. It is implied in the pathogenesis of lysosomal storage disease and osteopetrosis. Because of its endosomal/lysosomal localization it is still poorly characterized. Methodology/Principal Findings: An electrophysiological characterization of rat ClC-7 using solid-supported membrane-based electrophysiology is presented. The measured currents show the characteristics of ClC-7 and confirm its function as a Cl−/H+-antiporter. We have used rat ClC-7 in CHO cells as a model system to investigate the functionality and cellular localization of the wt transporter and its variant G213R ClC-7 which is the analogue of human G215R ClC-7 responsible for autosomal dominant osteopetrosis type II. Our study shows that rat G213R ClC-7 is functional but has a localization defect in CHO cells which prevents it from being correctly targeted to the lysosomal membrane. The electrophysiological assay is tested as a tool for drug discovery. The assay is validated with a number of drug candidates. It is shown that ClC-7 is inhibited by DIDS, NPPB and NS5818 at micromolar concentrations. Conclusions/Significance: It is suggested that the scenario found in the CHO model system also applies to the human transporter and that mislocalization rather than impaired functionality of G215R ClC-7 is the primary cause of the related autosomal dominant osteopetrosis type II. Furthermore, the robust solid-supported membrane-based electrophysiological assay is proposed for rapid screening for potential ClC-7 inhibitors which are discussed for treatment of osteoporosis.
Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.
While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.
he most basic behavioural states of animals can be described as active or passive. While high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g).
We used a dataset containing >3 million signals from very-high-frequency (VHF) telemetry from two forest-dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF-tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98).
We provide an ecological case-study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method.
Our approach can classify VHF-signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state-of-the-art open-source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.