| 1. |
- Roselli, Carolina, et al.
(författare)
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Multi-ethnic genome-wide association study for atrial fibrillation
- 2018
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 50:9, s. 1225-1233
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Tidskriftsartikel (refereegranskat)abstract
- Atrial fibrillation (AF) affects more than 33 million individuals worldwide(1) and has a complex heritability(2). We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.
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| 2. |
- Liemohn, Michael W., et al.
(författare)
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Model Evaluation Guidelines for Geomagnetic Index Predictions
- 2018
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Ingår i: Space Weather. - 1542-7390. ; 16:12, s. 2079-2102
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Tidskriftsartikel (refereegranskat)abstract
- Geomagnetic indices are convenient quantities that distill the complicated physics of some region or aspect of near‐Earth space into a single parameter. Most of the best‐known indices are calculated from ground‐based magnetometer data sets, such as Dst, SYM‐H, Kp, AE, AL, and PC. Many models have been created that predict the values of these indices, often using solar wind measurements upstream from Earth as the input variables to the calculation. This document reviews the current state of models that predict geomagnetic indices and the methods used to assess their ability to reproduce the target index time series. These existing methods are synthesized into a baseline collection of metrics for benchmarking a new or updated geomagnetic index prediction model. These methods fall into two categories: (1) fit performance metrics such as root‐mean‐square error and mean absolute error that are applied to a time series comparison of model output and observations and (2) event detection performance metrics such as Heidke Skill Score and probability of detection that are derived from a contingency table that compares model and observation values exceeding (or not) a threshold value. A few examples of codes being used with this set of metrics are presented, and other aspects of metrics assessment best practices, limitations, and uncertainties are discussed, including several caveats to consider when using geomagnetic indices.
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| 3. |
- Alexander, Stephen P. H., et al.
(författare)
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The Concise Guide to PHARMACOLOGY 2023/24: G protein-coupled receptors
- 2023
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Ingår i: BRITISH JOURNAL OF PHARMACOLOGY. - : British pharmacological society. - 0007-1188 .- 1476-5381. ; 180
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Tidskriftsartikel (refereegranskat)abstract
- The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
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| 4. |
- Charney, Alexander W, et al.
(författare)
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Contribution of Rare Copy Number Variants toBipolar Disorder Risk Is Limited to Schizoaffective Cases.
- 2019
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Ingår i: Biological psychiatry. - : Elsevier BV. - 1873-2402 .- 0006-3223. ; 86:2, s. 110-119
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Tidskriftsartikel (refereegranskat)abstract
- Genetic risk for bipolar disorder (BD) is conferred through many common alleles, while a role for rare copy number variants (CNVs) is less clear. Subtypes of BD including schizoaffective disorder bipolar type (SAB), bipolar I disorder (BD I), and bipolar II disorder (BD II) differ according to the prominence and timing of psychosis, mania, and depression. The genetic factors contributing to the combination of symptoms among these subtypes are poorly understood.Rare large CNVs were analyzed in 6353 BD cases (3833 BD I [2676 with psychosis, 850 without psychosis, and 307 with unknown psychosis history], 1436 BD II, 579 SAB, and 505 BD not otherwise specified) and 8656 controls. CNV burden and a polygenic risk score (PRS) for schizophrenia were used to evaluate the relative contributions of rare and common variants to risk of BD, BD subtypes, and psychosis.CNV burden did not differ between BD and controls when treated as a single diagnostic entity. However, burden in SAB was increased relative to controls (p= .001), BD I (p= .0003), and BD II (p= .0007). Burden and schizophrenia PRSs were increased in SAB compared with BD I with psychosis (CNV p= .0007, PRS p= .004), and BD I without psychosis (CNV p= .0004, PRS p= 3.9× 10-5). Within BD I, psychosis was associated with increased schizophrenia PRSs (p= .005) but not CNV burden.CNV burden in BD is limited to SAB. Rare and common genetic variants may contribute differently to risk for psychosis and perhaps other classes of psychiatric symptoms.
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| 5. |
- Christopoulos, Arthur, et al.
(författare)
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THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: G protein-coupled receptors.
- 2021
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Ingår i: British journal of pharmacology. - : Wiley. - 1476-5381 .- 0007-1188. ; 178 Suppl 1
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Forskningsöversikt (refereegranskat)abstract
- The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15538. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
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| 6. |
- Rogers, David, et al.
(författare)
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Highlights of Coastal Waves 1996
- 1998
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Ingår i: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 79, s. 1307-1326
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Tidskriftsartikel (refereegranskat)
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| 7. |
- Vandegriff, Erik M., et al.
(författare)
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Exploring Localized Geomagnetic Disturbances in Global MHD : Physics and Numerics
- 2024
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Ingår i: Space Weather. - : American Geophysical Union (AGU). - 1542-7390. ; 22:4
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Tidskriftsartikel (refereegranskat)abstract
- One of the prominent effects of space weather is the formation of rapid geomagnetic field variations on Earth's surface driven by the magnetosphere-ionosphere system. These geomagnetic disturbances (GMDs) cause geomagnetically induced currents to run through ground conducting systems. In particular, localized GMDs (LGMDs) can be high amplitude and can have an effect on scale sizes less than 100 km, making them hazardous to power grids and difficult to predict. In this study, we examine the ability of the Space Weather Modeling Framework (SWMF) to reproduce LGMDs in the 7 September 2017 event using both existing and new metrics to quantify the success of the model against observation. We show that the high-resolution SWMF can reproduce LGMDs driven by ionospheric sources, but struggles to reproduce LGMDs driven by substorm effects. We calculate the global maxima of the magnetic fluctuations to show instances when the SWMF captures LGMDs at the correct times but not the correct locations. To remedy these shortcomings we suggest model developments that will directly impact the ability of the SWMF to reproduce LGMDs, most importantly updating the ionospheric conductance calculation from empirical to physics-based. Studying the negative effects of space weather on Earth is a crucial part of protecting ourselves and our technology from solar phenomena. Fluctuations in Earth's magnetic field cause high-amplitude currents to run through ground conducting systems such as underwater cables and power lines, causing damage to the hardware. Being able to predict these magnetic field fluctuations is essential to protecting ourselves and our technology; however these effects can be highly localized, making them more difficult to predict. This study presents an analysis of a high-resolution model run of Earth's magnetic field that captures localized magnetic fluctuations on the ground. We use the model results to explore the causes of these fluctuations in the model and compare the results with observation. We show that the model can reproduce magnetic fluctuations associated with some dynamics in Earth's ionosphere, but misses some of the fluctuations caused by complex dynamics farther out in Earth's magnetic field. We also show that in some cases the model captures fluctuations at the correct times but not the correct locations. Finally we suggest model improvements that will directly improve our model's ability to reproduce and predict localized magnetic fluctuations. High resolution Space Weather Modeling Framework can reproduce Localized Geomagnetic Disturbances (localized geomagnetic disturbances s (LGMDs)) driven by ionospheric sources Magnetospheric disturbances associated with substorms appear in model, but effects do not translate to LGMDs on the ground Improvements to calculation of ionospheric conductance and capture of substorm dynamics in model needed to better predict LGMDs
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