| 11. |
- Belov, Vladimir, et al.
(författare)
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Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
- 2024
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.
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| 12. |
- Lembrechts, Jonas J., et al.
(författare)
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SoilTemp : A global database of near-surface temperature
- 2020
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Ingår i: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 26:11, s. 6616-6629
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Tidskriftsartikel (refereegranskat)abstract
- Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.
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| 13. |
- Watson, Hunna J., et al.
(författare)
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Common Genetic Variation and Age of Onset of Anorexia Nervosa
- 2022
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Ingår i: BIOLOGICAL PSYCHIATRY: GLOBAL OPEN SCIENCE. - : Elsevier BV. - 2667-1743. ; 2:4, s. 368-378
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Genetics and biology may influence the age of onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to age of onset of AN and to investigate the genetic associations between age of onset of AN and age at menarche.METHODS: A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed, which included 9335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age of onset, early-onset AN (,13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses.RESULTS: Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (single nucleotide polymorphism-h2) were 0.01-0.04 for age of onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early-and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age of onset and early-onset AN estimated from independent GWASs significantly predicted age of onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early -onset AN.CONCLUSIONS: Our results provide evidence consistent with a common variant genetic basis for age of onset and implicate biological pathways regulating menarche and reproduction.
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| 14. |
- Baker, Paul A., et al.
(författare)
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The emerging field of geogenomics : Constraining geological problems with genetic data
- 2014
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Ingår i: Earth-Science Reviews. - : Elsevier BV. - 0012-8252 .- 1872-6828. ; 135, s. 38-47
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Tidskriftsartikel (refereegranskat)abstract
- The development of a genomics-derived discipline within geology is timely, as a result of major advances in acquiring and processing geologically relevant genetic data. This paper articulates the emerging field of geogenomics, which involves the use of large-scale genetic data to constrain geological hypotheses. The paper introduces geogenomics and discusses how hypotheses can be addressed through collaboration between geologists and evolutionary biologists. As an example, geogenomic methods are applied to evaluate competing hypotheses regarding the timing of the Andean uplift, the closure of the Isthmus of Panama, the onset of trans-Amazon drainage, and Quaternary climate variation in the Neotropics.
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| 15. |
- Bernal, Ximena E., et al.
(författare)
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Empowering Latina scientists
- 2019
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 363:6429, s. 825-826
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 16. |
- Callaghan, Terry, et al.
(författare)
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Multi-Decadal Changes in Tundra Environments and Ecosystems : Synthesis of the International Polar Year-Back to the Future Project (IPY-BTF)
- 2011
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Ingår i: Ambio. - : Springer Science and Business Media LLC. - 0044-7447 .- 1654-7209. ; 40:6, s. 705-716
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Tidskriftsartikel (refereegranskat)abstract
- Understanding the responses of tundra systemsto global change has global implications. Most tundraregions lack sustained environmental monitoring and oneof the only ways to document multi-decadal change is toresample historic research sites. The International PolarYear (IPY) provided a unique opportunity for such researchthrough the Back to the Future (BTF) project (IPY project#512). This article synthesizes the results from 13 paperswithin this Ambio Special Issue. Abiotic changes includeglacial recession in the Altai Mountains, Russia; increasedsnow depth and hardness, permafrost warming, andincreased growing season length in sub-arctic Sweden;drying of ponds in Greenland; increased nutrient availabilityin Alaskan tundra ponds, and warming at mostlocations studied. Biotic changes ranged from relativelyminor plant community change at two sites in Greenland tomoderate change in the Yukon, and to dramatic increasesin shrub and tree density on Herschel Island, and in subarcticSweden. The population of geese tripled at one sitein northeast Greenland where biomass in non-grazed plotsdoubled. A model parameterized using results from a BTFstudy forecasts substantial declines in all snowbeds andincreases in shrub tundra on Niwot Ridge, Colorado overthe next century. In general, results support and provideimproved capacities for validating experimental manipulation,remote sensing, and modeling studies.
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| 17. |
- Chye, Yann, et al.
(författare)
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Subcortical surface morphometry in substance dependence : An ENIGMA addiction working group study
- 2020
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Ingår i: Addiction Biology. - : WILEY. - 1355-6215 .- 1369-1600. ; 25:6
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Tidskriftsartikel (refereegranskat)abstract
- While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.
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| 18. |
- Davies, Stuart J., et al.
(författare)
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ForestGEO: Understanding forest diversity and dynamics through a global observatory network
- 2021
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Ingår i: Biological Conservation. - : Elsevier BV. - 0006-3207. ; 253
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Tidskriftsartikel (refereegranskat)abstract
- ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.
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| 19. |
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| 20. |
- Petrov, Dmitry, et al.
(författare)
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Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
- 2017
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Ingår i: Machine learning in medical imaging. MLMI (Workshop). - Cham : Springer International Publishing. ; 10541, s. 371-378
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Tidskriftsartikel (refereegranskat)abstract
- As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability.
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