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- Gonze, X., et al.
(author)
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Recent developments in the ABINIT software package
- 2016
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In: Computer Physics Communications. - : Elsevier BV. - 0010-4655. ; 205, s. 106-131
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Journal article (peer-reviewed)abstract
- ABINIT is a package whose main program allows one to find the total energy, charge density, electronic structure and many other properties of systems made of electrons and nuclei, (molecules and periodic solids) within Density Functional Theory (DFT), Many-Body Perturbation Theory (GW approximation and Bethe-Salpeter equation) and Dynamical Mean Field Theory (DMFT). ABINIT also allows to optimize the geometry according to the DFT forces and stresses, to perform molecular dynamics simulations using these forces, and to generate dynamical matrices, Born effective charges and dielectric tensors. The present paper aims to describe the new capabilities of ABINIT that have been developed since 2009. It covers both physical and technical developments inside the ABINIT code, as well as developments provided within the ABINIT package. The developments are described with relevant references, input variables, tests and tutorials. Program summary: . Program title: ABINIT. . Catalogue identifier: AEEU_v2_0. . Program summary URL: . http://cpc.cs.qub.ac.uk/summaries/AEEU_v2_0.html . . Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland. . Licensing provisions: GNU General Public License, version 3. . No. of lines in distributed program, including test data, etc.: 4845789. . No. of bytes in distributed program, including test data, etc.: 71340403. . Distribution format: tar.gz. . Programming language: Fortran2003, PERL scripts, Python scripts. . Classification: 7.3, 7.8. . External routines: (all optional) BigDFT [2], ETSF_IO [3], libxc [4], NetCDF [5], MPI [6], Wannier90 [7], FFTW [8]. . Catalogue identifier of previous version: AEEU_v1_0. . Journal reference of previous version: Comput. Phys. Comm. 180 (2009) 2582. . Does the new version supersede the previous version?: Yes. The abinit-7.10.5 version is now the up to date stable version of ABINIT. . Nature of problem: . This package has the purpose of computing accurately material and nanostructure properties: electronic structure, bond lengths, bond angles, primitive cell size, cohesive energy, dielectric properties, vibrational properties, elastic properties, optical properties, magnetic properties, non-linear couplings, electronic and vibrational life-times, and others. . Solution method: . Software application based on Density Functional Theory, Many-Body Perturbation Theory and Dynamical Mean Field Theory, pseudopotentials, with plane waves or wavelets as basis functions. . Reasons for new version: . Since 2009, the abinit-5.7.4 version of the code has considerably evolved and is not yet up to date. The abinit- 7.10.5 version contains new physical and technical features that allow electronic structure calculations impossible to carry out in the previous versions. . Summary of revisions: . •new physical features: quantum effects for the nuclei treated by the Path-integral Molecular Dynamics; finding transition states using image dynamics (NEB or string methods); two component DFT for electron-positron annihilation; linear response in a Projector Augmented-Wave approach -PAW-, electron-phonon interactions and temperature dependence of the gap; Bethe Salpeter Equation -BSE-; Dynamical Mean Field Theory (DMFT).•new technical features: development of a PAW approach for a wavelet basis; parallelisation of the code on more than 10,000 processors; new build system.•new features in the ABINIT package: tests; test farm; new tutorials; new pseudopotentials and PAW atomic data tables; GUI and postprocessing tools like the AbiPy and APPA libraries. . Running time: . It is difficult to answer to the question as the use of ABINIT is very large. On one hand, ABINIT can run on 10,000 processors for hours to perform quantum molecular dynamics on large systems. On the other hand, tutorials for students can be performed on a laptop within a few minutes. . References: . 1 http://www.gnu.org/copyleft/gpl.txt 2 http://bigdft.org 3 http://www.etsf.eu/fileformats 4 http://www.tddft.org/programs/octopus/wiki/index.php/Libxc 5 http://www.unidata.ucar.edu/software/netcdf 6 https://en.wikipedia.org/wiki/Message_Passing_Interface 7 http://www.wannier.org 8M. Frigo and S.G. Johnson, Proceedings of the IEEE, 93, 216-231 (2005). . .
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- Thompson, Deborah J, et al.
(author)
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Genetic predisposition to mosaic Y chromosome loss in blood
- 2019
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 575, s. 652-657
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Journal article (peer-reviewed)abstract
- Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism1-5, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.
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- Genovese, G., et al.
(author)
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Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia
- 2016
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In: Nature Neuroscience. - : Springer Science and Business Media LLC. - 1097-6256 .- 1546-1726. ; 19:11, s. 1433-1441
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Journal article (peer-reviewed)abstract
- By analyzing the exomes of 12,332 unrelated Swedish individuals, including 4,877 individuals affected with schizophrenia, in ways informed by exome sequences from 45,376 other individuals, we identified 244,246 coding-sequence and splice-site ultra-rare variants (URVs) that were unique to individual Swedes. We found that gene-disruptive and putatively protein-damaging URVs (but not synonymous URVs) were more abundant among individuals with schizophrenia than among controls (P = 1.3 x 10(-10)). This elevation of protein-compromising URVs was several times larger than an analogously elevated rate for de novo mutations, suggesting that most rare-variant effects on schizophrenia risk are inherited. Among individuals with schizophrenia, the elevated frequency of protein-compromising URVs was concentrated in brain-expressed genes, particularly in neuronally expressed genes; most of this elevation arose from large sets of genes whose RNAs have been found to interact with synaptically localized proteins. Our results suggest that synaptic dysfunction may mediate a large fraction of strong, individually rare genetic influences on schizophrenia risk.
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- Holm Nielsen, S., et al.
(author)
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A biomarker of collagen type I degradation is associated with cardiovascular events and mortality in patients with atherosclerosis
- 2019
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In: Journal of Internal Medicine. - : Wiley. - 0954-6820. ; 285:1, s. 118-123
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Journal article (peer-reviewed)abstract
- Objective: Atherosclerosis is characterized by accumulation of lipids, cells and extracellular matrix (ECM) proteins in the arterial wall. Collagen type I (COL1), a component of the arterial ECM, is cleaved by matrix metalloproteinases (MMPs) and known to be remodelled in atherosclerosis. We explored whether the MMP-mediated COL1 biomarker, C1M, was associated with cardiovascular events, cardiovascular mortality and all-cause mortality in a large prospective cohort of patients with known atherosclerosis. Methods: Serum from 787 patients who underwent a carotid endarterectomy was included. Circulating levels of C1M were measured in serum. A total of 473 patients were followed for 6 years after surgery. Associations between C1M and incidence of cardiovascular events, cardiovascular mortality and all-cause mortality were assessed by Kaplan–Meier curves and Cox regression analysis. Results: A total of 101 (21.4%) patients suffered from nonfatal cardiovascular events during the follow-up period, and 64 (13.5%) patients died. Of these, 39 (60.9%) died from cardiovascular diseases. Patients with C1M levels above the median were significantly associated with cardiovascular events, cardiovascular mortality and all-cause mortality (P < 0.001, P = 0.004 and P < 0.001, respectively). C1M was included in the final model for prediction of cardiovascular events (HR 2.15, 95% CI 1.40–3.32, P = 0.001), cardiovascular mortality (HR 2.20, 95% CI 1.07–4.51, P = 0.031) and all-cause mortality (HR 2.98 95% CI 1.67–5.33, P = < 0.001). Conclusions: In patients with atherosclerotic carotid lesions, high levels of C1M predicted cardiovascular events, cardiovascular mortality and all-cause mortality. These findings emphasize the importance of remodelling mechanisms in atherosclerosis that are now becoming more and more explored.
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