| 51. |
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| 52. |
- Kalman, JL, et al.
(författare)
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Investigating the phenotypic and genetic associations between personality traits and suicidal behavior across major mental health diagnoses
- 2022
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Ingår i: European archives of psychiatry and clinical neuroscience. - : Springer Science and Business Media LLC. - 1433-8491 .- 0940-1334. ; 272:8, s. 1611-1620
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Tidskriftsartikel (refereegranskat)abstract
- Personality traits influence risk for suicidal behavior. We examined phenotype- and genotype-level associations between the Big Five personality traits and suicidal ideation and attempt in major depressive, bipolar and schizoaffective disorder, and schizophrenia patients (N = 3012) using fixed- and random-effects inverse variance-weighted meta-analyses. Suicidal ideations were more likely to be reported by patients with higher neuroticism and lower extraversion phenotypic scores, but showed no significant association with polygenic load for these personality traits. Our findings provide new insights into the association between personality and suicidal behavior across mental illnesses and suggest that the genetic component of personality traits is unlikely to have strong causal effects on suicidal behavior.
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| 53. |
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| 54. |
- Altenburger, R., et al.
(författare)
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Future water quality monitoring - Adapting tools to deal with mixtures of pollutants in water resource management
- 2015
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 512, s. 540-551
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Tidskriftsartikel (refereegranskat)abstract
- Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigation measures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicals co-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and to derive combined effect estimates suitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measures integrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at the Danube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis of findings will be organised to provide guidance for future solution-oriented environmental monitoring and explore more systematic ways to assess mixture exposures and combination effects in future water quality monitoring. (C) 2015 Elsevier B.V. All rights reserved.
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| 55. |
- Altenburger, R., et al.
(författare)
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Future water quality monitoring: improving the balance between exposure and toxicity assessments of real-world pollutant mixtures
- 2019
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Ingår i: Environmental Sciences Europe. - : Springer Science and Business Media LLC. - 2190-4715 .- 2190-4707. ; 31
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Tidskriftsartikel (refereegranskat)abstract
- Environmental water quality monitoring aims to provide the data required for safeguarding the environment against adverse biological effects from multiple chemical contamination arising from anthropogenic diffuse emissions and point sources. Here, we integrate the experience of the international EU-funded project SOLUTIONS to shift the focus of water monitoring from a few legacy chemicals to complex chemical mixtures, and to identify relevant drivers of toxic effects. Monitoring serves a range of purposes, from control of chemical and ecological status compliance to safeguarding specific water uses, such as drinking water abstraction. Various water sampling techniques, chemical target, suspect and non-target analyses as well as an array of in vitro, in vivo and in situ bioanalytical methods were advanced to improve monitoring of water contamination. Major improvements for broader applicability include tailored sampling techniques, screening and identification techniques for a broader and more diverse set of chemicals, higher detection sensitivity, standardized protocols for chemical, toxicological, and ecological assessments combined with systematic evidence evaluation techniques. No single method or combination of methods is able to meet all divergent monitoring purposes. Current monitoring approaches tend to emphasize either targeted exposure or effect detection. Here, we argue that, irrespective of the specific purpose, assessment of monitoring results would benefit substantially from obtaining and linking information on the occurrence of both chemicals and potentially adverse biological effects. In this paper, we specify the information required to: (1) identify relevant contaminants, (2) assess the impact of contamination in aquatic ecosystems, or (3) quantify cause-effect relationships between contaminants and adverse effects. Specific strategies to link chemical and bioanalytical information are outlined for each of these distinct goals. These strategies have been developed and explored using case studies in the Danube and Rhine river basins as well as for rivers of the Iberian Peninsula. Current water quality assessment suffers from biases resulting from differences in approaches and associated uncertainty analyses. While exposure approaches tend to ignore data gaps (i.e., missing contaminants), effect-based approaches penalize data gaps with increased uncertainty factors. This integrated work suggests systematic ways to deal with mixture exposures and combined effects in a more balanced way, and thus provides guidance for future tailored environmental monitoring.
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| 56. |
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| 57. |
- Brack, W., et al.
(författare)
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Strengthen the European collaborative environmental research to meet European policy goals for achieving a sustainable, non-toxic environment
- 2019
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Ingår i: Environmental Sciences Europe. - : Springer Science and Business Media LLC. - 2190-4707 .- 2190-4715. ; 31:1
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Tidskriftsartikel (refereegranskat)abstract
- To meet the United Nations (UN) sustainable development goals and the European Union (EU) strategy for a non-toxic environment, water resources and ecosystems management require cost-efficient solutions for prevailing complex contamination and multiple stressor exposures. For the protection of water resources under global change conditions, specific research needs for prediction, monitoring, assessment and abatement of multiple stressors emerge with respect to maintaining human needs, biodiversity, and ecosystem services. Collaborative European research seems an ideal instrument to mobilize the required transdisciplinary scientific support and tackle the large-scale dimension and develop options required for implementation of European policies. Calls for research on minimizing society's chemical footprints in the water-food-energy-security nexus are required. European research should be complemented with targeted national scientific funding to address specific transformation pathways and support the evaluation, demonstration and implementation of novel approaches on regional scales. The foreseeable pressure developments due to demographic, economic and climate changes require solution-oriented thinking, focusing on the assessment of sustainable abatement options and transformation pathways rather than on status evaluation. Stakeholder involvement is a key success factor in collaborative projects as it allows capturing added value, to address other levels of complexity, and find smarter solutions by synthesizing scientific evidence, integrating governance issues, and addressing transition pathways. This increases the chances of closing the value chain by implementing novel solutions. For the water quality topic, the interacting European collaborative projects SOLUTIONS, MARS and GLOBAQUA and the NORMAN network provide best practice examples for successful applied collaborative research including multi-stakeholder involvement. They provided innovative conceptual, modelling and instrumental options for future monitoring and management of chemical mixtures and multiple stressors in European water resources. Advancement of EU water framework directive-related policies has therefore become an option. Bt Aachen Biol, Aachen, Germany.
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| 58. |
- Nunes, A, et al.
(författare)
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Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
- 2020
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Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 25:9, s. 2130-2143
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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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| 59. |
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| 60. |
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