Refine
Year of publication
Document Type
- Article (23)
- Preprint (7)
- Working Paper (1)
Language
- English (31)
Has Fulltext
- yes (31)
Is part of the Bibliography
- no (31)
Keywords
- Brain tumor (1)
- Charged-particle multiplicity (1)
- Cold nuclear matter effects (1)
- Collectivity (1)
- Correlation (1)
- Data sharing (1)
- Di-hadron correlations (1)
- Diffraction (1)
- EWSR1 (1)
- Elastic scattering (1)
- Gene fusion (1)
- Groomed jet radius (1)
- Interference fragmentation function (1)
- J/ψ suppression (1)
- Jet substructure (1)
- MN1 (1)
- Multiple parton interactions (1)
- Neuroepithelial (1)
- Neurooncology (1)
- PATZ1 (1)
- Pediatric (1)
- Proton-proton collisions (1)
- Quarkonium (1)
- RHIC (1)
- Shear viscosity (1)
- SoftDrop (1)
- Splitting function (1)
- Transversity (1)
- global change (1)
- habitat destruction (1)
- land use (1)
- p+p collisions (1)
Institute
- Physik (13)
- Frankfurt Institute for Advanced Studies (FIAS) (9)
- Medizin (8)
- Biodiversität und Klima Forschungszentrum (BiK-F) (1)
- Center for Financial Studies (CFS) (1)
- House of Finance (HoF) (1)
- Institut für Ökologie, Evolution und Diversität (1)
- Sustainable Architecture for Finance in Europe (SAFE) (1)
- Wirtschaftswissenschaften (1)
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
Measurement of inclusive charged-particle jet production in Au+Au collisions at √sNN = 200 GeV
(2021)
The STAR Collaboration at the Relativistic Heavy Ion Collider reports the first measurement of inclusive jet production in peripheral and central Au+Au collisions at sNN−−−−√=200 GeV. Jets are reconstructed with the anti-kT algorithm using charged tracks with pseudorapidity |η|<1.0 and transverse momentum 0.2<pchT,jet<30 GeV/c, with jet resolution parameter R=0.2, 0.3, and 0.4. The large background yield uncorrelated with the jet signal is observed to be dominated by statistical phase space, consistent with a previous coincidence measurement. This background is suppressed by requiring a high-transverse-momentum (high-pT) leading hadron in accepted jet candidates. The bias imposed by this requirement is assessed, and the pT region in which the bias is small is identified. Inclusive charged-particle jet distributions are reported in peripheral and central Au+Au collisions for 5<pchT,jet<25 GeV/c and 5<pchT,jet<30 GeV/c, respectively. The charged-particle jet inclusive yield is suppressed for central Au+Au collisions, compared to both the peripheral Au+Au yield from this measurement and to the pp yield calculated using the PYTHIA event generator. The magnitude of the suppression is consistent with that of inclusive hadron production at high pT, and that of semi-inclusive recoil jet yield when expressed in terms of energy loss due to medium-induced energy transport. Comparison of inclusive charged-particle jet yields for different values of R exhibits no significant evidence for medium-induced broadening of the transverse jet profile for R<0.4 in central Au+Au collisions. The measured distributions are consistent with theoretical model calculations that incorporate jet quenching.
Measurement of inclusive charged-particle jet production in Au + Au collisions at √sNN=200 GeV
(2020)
The STAR Collaboration at the Relativistic Heavy Ion Collider reports the first measurement of inclusive jet production in peripheral and central Au+Au collisions at √𝑠𝑁𝑁=200 GeV. Jets are reconstructed with the anti-𝑘𝑇 algorithm using charged tracks with pseudorapidity |𝜂|<1.0 and transverse momentum 0.2<𝑝ch
𝑇,jet<30 GeV/𝑐, with jet resolution parameter 𝑅=0.2, 0.3, and 0.4. The large background yield uncorrelated with the jet signal is observed to be dominated by statistical phase space, consistent with a previous coincidence measurement. This background is suppressed by requiring a high-transverse-momentum (high-𝑝𝑇) leading hadron in accepted jet candidates. The bias imposed by this requirement is assessed, and the 𝑝𝑇 region in which the bias is small is identified. Inclusive charged-particle jet distributions are reported in peripheral and central Au+Au collisions for 5<𝑝ch
𝑇,jet<25 GeV/𝑐 and 5<𝑝ch
𝑇,jet<30 GeV/𝑐, respectively. The charged-particle jet inclusive yield is suppressed for central Au+Au collisions, compared to both the peripheral Au+Au yield from this measurement and to the 𝑝𝑝 yield calculated using the PYTHIA event generator. The magnitude of the suppression is consistent with that of inclusive hadron production at high 𝑝𝑇 and that of semi-inclusive recoil jet yield when expressed in terms of energy loss due to medium-induced energy transport. Comparison of inclusive charged-particle jet yields for different values of 𝑅 exhibits no significant evidence for medium-induced broadening of the transverse jet profile for 𝑅 <0.4 in central Au+Au collisions. The measured distributions are consistent with theoretical model calculations that incorporate jet quenching.
Large-scale molecular profiling studies in recent years have shown that central nervous system (CNS) tumors display a much greater heterogeneity in terms of molecularly distinct entities, cellular origins and genetic drivers than anticipated from histological assessment. DNA methylation profiling has emerged as a useful tool for robust tumor classification, providing new insights into these heterogeneous molecular classes. This is particularly true for rare CNS tumors with a broad morphological spectrum, which are not possible to assign as separate entities based on histological similarity alone. Here, we describe a molecularly distinct subset of predominantly pediatric CNS neoplasms (n = 60) that harbor PATZ1 fusions. The original histological diagnoses of these tumors covered a wide spectrum of tumor types and malignancy grades. While the single most common diagnosis was glioblastoma (GBM), clinical data of the PATZ1-fused tumors showed a better prognosis than typical GBM, despite frequent relapses. RNA sequencing revealed recurrent MN1:PATZ1 or EWSR1:PATZ1 fusions related to (often extensive) copy number variations on chromosome 22, where PATZ1 and the two fusion partners are located. These fusions have individually been reported in a number of glial/glioneuronal tumors, as well as extracranial sarcomas. We show here that they are more common than previously acknowledged, and together define a biologically distinct CNS tumor type with high expression of neural development markers such as PAX2, GATA2 and IGF2. Drug screening performed on the MN1:PATZ1 fusion-bearing KS-1 brain tumor cell line revealed preliminary candidates for further study. In summary, PATZ1 fusions define a molecular class of histologically polyphenotypic neuroepithelial tumors, which show an intermediate prognosis under current treatment regimens.