| 1. |
- Kelly, J. J., et al.
(författare)
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Recoil polarization measurements for neutral pion electroproduction at Q(2)=1(GeV/c)(2) near the Delta resonance
- 2007
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Ingår i: Physical Review C (Nuclear Physics). - 0556-2813. ; 75:2
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Tidskriftsartikel (refereegranskat)abstract
- We measured angular distributions of differential cross section, beam analyzing power, and recoil polarization for neutral pion electroproduction at Q(2)=1.0 (GeV/c)(2) in 10 bins of 1.17 <= W <= 1.35 GeV across the Delta resonance. A total of 16 independent response functions were extracted, of which 12 were observed for the first time. Comparisons with recent model calculations show that response functions governed by real parts of interference products are determined relatively well near the physical mass, W=M-Delta approximate to 1.232 GeV, but the variation among models is large for response functions governed by imaginary parts, and for both types of response functions, the variation increases rapidly with W > M-Delta. We performed a multipole analysis that adjusts suitable subsets of center dot(pi)<= 2 amplitudes with higher partial waves constrained by baseline models. This analysis provides both real and imaginary parts. The fitted multipole amplitudes are nearly model independent-there is very little sensitivity to the choice of baseline model or truncation scheme. By contrast, truncation errors in the traditional Legendre analysis of N ->Delta quadrupole ratios are not negligible. Parabolic fits to the W dependence around M-Delta for the multiple analysis gives values for Re(S1+/M1+)=(-6.61 +/- 0.18)% and Re(E1+/M1+)=(-2.87 +/- 0.19)% for the p pi(0) channel at W=1.232 GeV and Q(2)=1.0 (GeV/c)(2) that are distinctly larger than those from the Legendre analysis of the same data. Similarly, the multipole analysis gives Re(S0+/M1+)=(+7.1 +/- 0.8)% at W=1.232 GeV, consistent with recent models, while the traditional Legendre analysis gives the opposite sign because its truncation errors are quite severe.
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| 2. |
- Liu, DJ, et al.
(författare)
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Schizophrenia risk conferred by rare protein-truncating variants is conserved across diverse human populations
- 2023
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Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 55:3, s. 369-
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Tidskriftsartikel (refereegranskat)abstract
- Schizophrenia (SCZ) is a chronic mental illness and among the most debilitating conditions encountered in medical practice. A recent landmark SCZ study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes1. This recent study—and most other large-scale human genetics studies—was mainly composed of individuals of European (EUR) ancestry, and the generalizability of the findings in non-EUR populations remains unclear. To address this gap, we designed a custom sequencing panel of 161 genes selected based on the current knowledge of SCZ genetics and sequenced a new cohort of 11,580 SCZ cases and 10,555 controls of diverse ancestries. Replicating earlier work, we found that cases carried a significantly higher burden of rare protein-truncating variants (PTVs) among evolutionarily constrained genes (odds ratio = 1.48; P = 5.4 × 10−6). In meta-analyses with existing datasets totaling up to 35,828 cases and 107,877 controls, this excess burden was largely consistent across five ancestral populations. Two genes (SRRM2 and AKAP11) were newly implicated as SCZ risk genes, and one gene (PCLO) was identified as shared by individuals with SCZ and those with autism. Overall, our results lend robust support to the rare allelic spectrum of the genetic architecture of SCZ being conserved across diverse human populations.
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| 3. |
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| 4. |
- Degasperi, Andrea, et al.
(författare)
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A practical framework and online tool for mutational signature analyses show intertissue variation and driver dependencies
- 2020
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Ingår i: Nature Cancer. - : Springer Science and Business Media LLC. - 2662-1347. ; 1:2, s. 249-263
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Tidskriftsartikel (refereegranskat)abstract
- Mutational signatures are patterns of mutations that arise during tumorigenesis. We present an enhanced, practical framework for mutational signature analyses. Applying these methods to 3,107 whole-genome-sequenced (WGS) primary cancers of 21 organs reveals known signatures and nine previously undescribed rearrangement signatures. We highlight interorgan variability of signatures and present a way of visualizing that diversity, reinforcing our findings in an independent analysis of 3,096 WGS metastatic cancers. Signatures with a high level of genomic instability are dependent on TP53 dysregulation. We illustrate how uncertainty in mutational signature identification and assignment to samples affects tumor classification, reinforcing that using multiple orthogonal mutational signature data is not only beneficial, but is also essential for accurate tumor stratification. Finally, we present a reference web-based tool for cancer and experimentally generated mutational signatures, called Signal (https://signal.mutationalsignatures.com), that also supports performing mutational signature analyses.
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