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  • Landén, Mikael, 1966, et al. (författare)
  • Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
  • 2021
  • Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 5124-5139
  • 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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  • Ching, C. R. K., et al. (författare)
  • What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group
  • 2022
  • Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 56-82
  • Tidskriftsartikel (refereegranskat)abstract
    • MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.
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  • Hibar, D. P., et al. (författare)
  • Cortical abnormalities in bipolar disorder: An MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group
  • 2018
  • Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 23:4, s. 932-942
  • Tidskriftsartikel (refereegranskat)abstract
    • Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d='0.293; P=1.71 × 10 '21), left fusiform gyrus (d='0.288; P=8.25 × 10 '21) and left rostral middle frontal cortex (d='0.276; P=2.99 × 10 '19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD. © 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
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  • Hibar, D. P., et al. (författare)
  • Subcortical volumetric abnormalities in bipolar disorder
  • 2016
  • Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 21:12, s. 1710-1716
  • Tidskriftsartikel (refereegranskat)abstract
    • Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10 -7) and thalamus (d=-0.148; P=4.27 × 10 -3) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10 -5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons. © 2016 Macmillan Publishers Limited, part of Springer Nature.
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  • Nunes, A, et al. (författare)
  • Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
  • 2020
  • Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 25:9, s. 2130-2143
  • Tidskriftsartikel (refereegranskat)abstract
    • Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.
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  • McWhinney, Sean R, et al. (författare)
  • Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.
  • 2021
  • Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 26:11, s. 6806-6819
  • Tidskriftsartikel (refereegranskat)abstract
    • Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediatedby BMI (Z=2.73, p=0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.
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  • McWhinney, Sean R, et al. (författare)
  • Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.
  • 2022
  • Ingår i: Bipolar disorders. - : Wiley. - 1399-5618 .- 1398-5647. ; 24:5, s. 509-520
  • Tidskriftsartikel (refereegranskat)abstract
    • Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry.We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles.We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex.We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.
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  • McWhinney, Sean R, et al. (författare)
  • Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.
  • 2023
  • Ingår i: Psychological medicine. - 1469-8978. ; 53:14, s. 6743-6753
  • Tidskriftsartikel (refereegranskat)abstract
    • Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.
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  • Schijven, Dick, et al. (författare)
  • Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium
  • 2023
  • Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences (PNAS). - 0027-8424 .- 1091-6490. ; 120:14
  • Tidskriftsartikel (refereegranskat)abstract
    • Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
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  • Abé, Christoph, et al. (författare)
  • Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group.
  • 2022
  • Ingår i: Biological psychiatry. - : Elsevier BV. - 1873-2402 .- 0006-3223. ; 91:6, s. 582-592
  • Tidskriftsartikel (refereegranskat)abstract
    • Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD.Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables.Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18
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  • Thompson, PM, et al. (författare)
  • ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
  • 2020
  • Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 100-
  • Tidskriftsartikel (refereegranskat)abstract
    • This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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  • Thompson, Paul M., et al. (författare)
  • The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
  • 2014
  • Ingår i: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
  • 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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  • Bralower, T, et al. (författare)
  • The Habitat of the Nascent Chicxulub Crater
  • 2020
  • Ingår i: AGU Advances. - : American Geophysical Union (AGU). ; 1
  • Tidskriftsartikel (refereegranskat)abstract
    • An expanded sedimentary section provides an opportunity to elucidate conditions in the nascent Chicxulub crater during the hours to millennia after the Cretaceous‐Paleogene (K‐Pg) boundary impact. The sediments were deposited by tsunami followed by seiche waves as energy in the crater declined, culminating in a thin hemipelagic marlstone unit that contains atmospheric fallout. Seiche deposits are predominantly composed of calcite formed by decarbonation of the target limestone during impact followed by carbonation in the water column. Temperatures recorded by clumped isotopes of these carbonates are in excess of 70°C, with heat likely derived from the central impact melt pool. Yet, despite the turbidity and heat, waters within the nascent crater basin soon became a viable habitat for a remarkably diverse cross section of the food chain. The earliest seiche layers deposited with days or weeks of the impact contain earliest Danian nannoplankton and dinocyst survivors. The hemipelagic marlstone representing the subsequent years to a few millennia contains a nearly monogeneric calcareous dinoflagellate resting cyst assemblage suggesting deteriorating environmental conditions, with one interpretation involving low light levels in the impact aftermath. At the same horizon, microbial fossils indicate a thriving bacterial community and unique phosphatic fossils including appendages of pelagic crustaceans, coprolites andbacteria‐tunneled fish bone, suggesting that this rapid recovery of the base of the food chain may have supported the survival of larger, higher trophic‐level organisms. The extraordinarily diverse fossil assemblage indicates that the crater was a unique habitat in the immediate impact aftermath, possibly as aresult of heat and nutrients supplied by hydrothermal activity.
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  • Puchalska, Monika, 1977, et al. (författare)
  • NUNDO: a numerical model of a human torso phantom and its application to effective dose equivalent calculations for astronauts at the ISS
  • 2014
  • Ingår i: Radiation and Environmental Biophysics. - : Springer Science and Business Media LLC. - 1432-2099 .- 0301-634X. ; 53:4, s. 719-727
  • Tidskriftsartikel (refereegranskat)abstract
    • The health effects of cosmic radiation on astronauts need to be precisely quantified and controlled. This task is important not only in perspective of the increasing human presence at the International Space Station (ISS), but also for the preparation of safe human missions beyond low earth orbit. From a radiation protection point of view, the baseline quantity for radiation risk assessment in space is the effective dose equivalent. The present work reports the first successful attempt of the experimental determination of the effective dose equivalent in space, both for extra-vehicular activity (EVA) and intra-vehicular activity (IVA). This was achieved using the anthropomorphic torso phantom RANDO(A (R)) equipped with more than 6,000 passive thermoluminescent detectors and plastic nuclear track detectors, which have been exposed to cosmic radiation inside the European Space Agency MATROSHKA facility both outside and inside the ISS. In order to calculate the effective dose equivalent, a numerical model of the RANDO(A (R)) phantom, based on computer tomography scans of the actual phantom, was developed. It was found that the effective dose equivalent rate during an EVA approaches 700 mu Sv/d, while during an IVA about 20 % lower values were observed. It is shown that the individual dose based on a personal dosimeter reading for an astronaut during IVA results in an overestimate of the effective dose equivalent of about 15 %, whereas under an EVA conditions the overestimate is more than 200 %. A personal dosemeter can therefore deliver quite good exposure records during IVA, but may overestimate the effective dose equivalent received during an EVA considerably.
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  • Bergsten, Johannes, 1975-, et al. (författare)
  • Coleoptera: Dytiscidae, diving beetles, tsikovoka
  • 2022. - 1
  • Ingår i: The new natural history of Madagascar. - Princeton : Princeton University Press. - 9780691222622 ; , s. 1024-1034
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)
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  • Biurrun, Idoia, et al. (författare)
  • Benchmarking plant diversity of Palaearctic grasslands and other open habitats
  • 2021
  • Ingår i: Journal of Vegetation Science. - Oxford : John Wiley & Sons. - 1100-9233 .- 1654-1103. ; 32:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Journal of Vegetation Science published by John Wiley & Sons Ltd on behalf of International Association for Vegetation Science.Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology. © 2021 The Authors.
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  • Dengler, Juergen, et al. (författare)
  • GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands
  • 2018
  • Ingår i: Phytocoenologia. - : Schweizerbart. - 0340-269X. ; 48:3, s. 331-347
  • Tidskriftsartikel (refereegranskat)abstract
    • GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.
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  • Dietze, LMF, et al. (författare)
  • Extended and replicated white matter changes in obesity: Voxel-based and region of interest meta-analyses of diffusion tensor imaging studies
  • 2023
  • Ingår i: Frontiers in nutrition. - : Frontiers Media SA. - 2296-861X. ; 10, s. 1108360-
  • Tidskriftsartikel (refereegranskat)abstract
    • Obesity has become a global public health issue, which impacts general health and the brain. Associations between obesity and white matter microstructure measured using diffusion tensor imaging have been under reviewed, despite a relatively large number of individual studies. Our objective was to determine the association between obesity and white matter microstructure in a large general population sample.MethodsWe analyzed location of brain white matter changes in obesity using the Anisotropic Effect Size Seed-based d Mapping (AES-SDM) method in a voxel-based meta-analysis, with validation in a region of interest (ROI) effect size meta-analysis. Our sample included 21 742 individuals from 51 studies.ResultsThe voxel-based spatial meta-analysis demonstrated reduced fractional anisotropy (FA) with obesity in the genu and splenium of the corpus callosum, middle cerebellar peduncles, anterior thalamic radiation, cortico-spinal projections, and cerebellum. The ROI effect size meta-analysis replicated associations between obesity and lower FA in the genu and splenium of the corpus callosum, middle cerebellar peduncles. Effect size of obesity related brain changes was small to medium.DiscussionOur findings demonstrate obesity related brain white matter changes are localized rather than diffuse. Better understanding the brain correlates of obesity could help identify risk factors, and targets for prevention or treatment of brain changes.
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  • Hajek, J., et al. (författare)
  • Processing of gluconic acid derivatives to value added monosaccharides via oxidative degradation
  • 2012
  • Konferensbidrag (refereegranskat)abstract
    • One of the components that can be efficiently obtained, e.g., via fermentation of polysaccharide containing waste or biomass, is glucose and some of its derivatives. Degradation of C6 carbohydrates yields corresponding C5 sugars. In case of gluconic acid, the product is arabinose. The reaction, illustrating a valuable synthetic route, e.g., for the abatement of waste streams containing gluconic acid is shown. In spite of high yields, the reaction is characterized by complex analytics due to the presence of organic as well as inorganic by-products. Under optimized conditions, yields between 70-80% could be achieved. This is an abstract of a paper presented at the CHISA 2012 - 20th International Congress of Chemical and Process Engineering and PRES 2012 - 15th Conference PRES (Prague, Czech Republic 8/25-29/2012).
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  • McWhinney, Sean R, et al. (författare)
  • Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.
  • 2024
  • Ingår i: Human brain mapping. - 1097-0193. ; 45:8
  • Tidskriftsartikel (refereegranskat)abstract
    • Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
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  • Palumbo, A., et al. (författare)
  • International Myeloma Working Group guidelines for the management of multiple myeloma patients ineligible for standard high-dose chemotherapy with autologous stem cell transplantation
  • 2009
  • Ingår i: Leukemia. - : Springer Science and Business Media LLC. - 1476-5551 .- 0887-6924. ; 23:10, s. 1716-1730
  • Forskningsöversikt (refereegranskat)abstract
    • In 2005, the first guidelines were published on the management of patients with multiple myeloma (MM). An expert panel reviewed the currently available literature as the basis for a set of revised and updated consensus guidelines for the diagnosis and management of patients with MM who are not eligible for autologous stem cell transplantation. Here we present recommendations on the diagnosis, treatment of newly diagnosed non-transplant-eligible patients and the management of complications occurring during induction therapy among these patients. These guidelines will aid the physician in daily clinical practice and will ensure optimal care for patients with MM. Leukemia (2009) 23, 1716-1730; doi: 10.1038/leu.2009.122; published online 4 June 2009
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