| 1. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 2. |
- Aad, G., et al.
(författare)
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- 2011
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swepub:Mat__t
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| 3. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 4. |
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| 5. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 6. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 7. |
- Aaltonen, T., et al.
(författare)
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Combination of Tevatron Searches for the Standard Model Higgs Boson in the W+W- Decay Mode
- 2010
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Ingår i: Physical Review Letters. - 0031-9007 .- 1079-7114. ; 104:6, s. 061802-
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Tidskriftsartikel (refereegranskat)abstract
- We combine searches by the CDF and D0 Collaborations for a Higgs boson decaying to W+W-. The data correspond to an integrated total luminosity of 4.8 (CDF) and 5.4 (D0) fb(-1) of p (p) over bar collisions at root s = 1.96 TeV at the Fermilab Tevatron collider. No excess is observed above background expectation, and resulting limits on Higgs boson production exclude a standard model Higgs boson in the mass range 162-166 GeV at the 95% C.L.
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| 8. |
- Landén, Mikael, 1966, et al.
(författare)
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Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
- 2021
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Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26
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Tidskriftsartikel (refereegranskat)abstract
- Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d = 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates. © 2020, The Author(s).
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| 9. |
- Thompson, Paul M., et al.
(författare)
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The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
- 2014
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Ingår i: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
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Tidskriftsartikel (refereegranskat)abstract
- The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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| 10. |
- Bauer, M., et al.
(författare)
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Solar insolation in springtime influences age of onset of bipolar I disorder
- 2017
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Ingår i: Acta Psychiatrica Scandinavica. - : Wiley. - 0001-690X .- 1600-0447. ; 136:6, s. 571-582
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Forskningsöversikt (refereegranskat)abstract
- Objective: To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. Method: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. Results: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). Conclusion: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.
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