@article{SchibornSchulze2022, author = {Schiborn, Catarina and Schulze, Matthias Bernd}, title = {Precision prognostics for the development of complications in diabetes}, series = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)}, journal = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)}, publisher = {Springer}, address = {New York}, issn = {0012-186X}, doi = {10.1007/s00125-022-05731-4}, pages = {16}, year = {2022}, abstract = {Individuals with diabetes face higher risks for macro- and microvascular complications than their non-diabetic counterparts. The concept of precision medicine in diabetes aims to optimise treatment decisions for individual patients to reduce the risk of major diabetic complications, including cardiovascular outcomes, retinopathy, nephropathy, neuropathy and overall mortality. In this context, prognostic models can be used to estimate an individual's risk for relevant complications based on individual risk profiles. This review aims to place the concept of prediction modelling into the context of precision prognostics. As opposed to identification of diabetes subsets, the development of prediction models, including the selection of predictors based on their longitudinal association with the outcome of interest and their discriminatory ability, allows estimation of an individual's absolute risk of complications. As a consequence, such models provide information about potential patient subgroups and their treatment needs. This review provides insight into the methodological issues specifically related to the development and validation of prediction models for diabetes complications. We summarise existing prediction models for macro- and microvascular complications, commonly included predictors, and examples of available validation studies. The review also discusses the potential of non-classical risk markers and omics-based predictors. Finally, it gives insight into the requirements and challenges related to the clinical applications and implementation of developed predictions models to optimise medical decision making.}, language = {en} } @article{Tjaden2021, author = {Tjaden, Jasper}, title = {Measuring migration 2.0}, series = {Comparative migration studies : CMS}, volume = {9}, journal = {Comparative migration studies : CMS}, number = {1}, publisher = {Springer}, address = {London}, issn = {2214-594X}, doi = {10.1186/s40878-021-00273-x}, pages = {20}, year = {2021}, abstract = {The interest in human migration is at its all-time high, yet data to measure migration is notoriously limited. "Big data" or "digital trace data" have emerged as new sources of migration measurement complementing 'traditional' census, administrative and survey data. This paper reviews the strengths and weaknesses of eight novel, digital data sources along five domains: reliability, validity, scope, access and ethics. The review highlights the opportunities for migration scholars but also stresses the ethical and empirical challenges. This review intends to be of service to researchers and policy analysts alike and help them navigate this new and increasingly complex field.}, language = {en} } @article{EgliWeiseRadchuketal.2019, author = {Egli, Lukas and Weise, Hanna and Radchuk, Viktoriia and Seppelt, Ralf and Grimm, Volker}, title = {Exploring resilience with agent-based models: State of the art, knowledge gaps and recommendations for coping with multidimensionality}, series = {Ecological complexity}, volume = {40}, journal = {Ecological complexity}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1476-945X}, doi = {10.1016/j.ecocom.2018.06.008}, pages = {7}, year = {2019}, abstract = {Anthropogenic pressures increasingly alter natural systems. Therefore, understanding the resilience of agent-based complex systems such as ecosystems, i.e. their ability to absorb these pressures and sustain their functioning and services, is a major challenge. However, the mechanisms underlying resilience are still poorly understood. A main reason for this is the multidimensionality of both resilience, embracing the three fundamental stability properties recovery, resistance and persistence, and of the specific situations for which stability properties can be assessed. Agent-based models (ABM) complement empirical research which is, for logistic reasons, limited in coping with these multiple dimensions. Besides their ability to integrate multidimensionality through extensive manipulation in a fully controlled system, ABMs can capture the emergence of system resilience from individual interactions and feedbacks across different levels of organization. To assess the extent to which this potential of ABMs has already been exploited, we reviewed the state of the art in exploring resilience and its multidimensionality in ecological and socio-ecological systems with ABMs. We found that the potential of ABMs is not utilized in most models, as they typically focus on a single dimension of resilience by using variability as a proxy for persistence, and are limited to one reference state, disturbance type and scale. Moreover, only few studies explicitly test the ability of different mechanisms to support resilience. To overcome these limitations, we recommend to simultaneously assess multiple stability properties for different situations and under consideration of the mechanisms that are hypothesised to render a system resilient. This will help us to better exploit the potential of ABMs to understand and quantify resilience mechanisms, and hence support solving real-world problems related to the resilience of agent-based complex systems.}, language = {en} } @article{BragaGomezAparicioHegeretal.2018, author = {Braga, Raul Renno and Gomez-Aparicio, Lorena and Heger, Tina and Simoes Vitule, Jean Ricardo and Jeschke, Jonathan M.}, title = {Structuring evidence for invasional meltdown}, series = {Biological invasions : unique international journal uniting scientists in the broad field of biological invasions}, volume = {20}, journal = {Biological invasions : unique international journal uniting scientists in the broad field of biological invasions}, number = {4}, publisher = {Springer}, address = {Dordrecht}, issn = {1387-3547}, doi = {10.1007/s10530-017-1582-2}, pages = {923 -- 936}, year = {2018}, abstract = {Negative interactions have been suggested as a major barrier for species arriving in a new habitat. More recently, positive interactions drew attention from community assembly theory and invasion science. The invasional meltdown hypothesis (IMH) introduced the idea that positive interactions among non-native species could facilitate one another's invasion, even increasing their impact upon the native community. Many studies have addressed IMH, but with contrasting results, reflecting various types of evidence on a multitude of scales. Here we use the hierarchy-of-hypotheses (HoH) approach to differentiate key aspects of IMH, organizing and linking empirical studies to sub-hypotheses of IMH. We also assess the level of empirical support for each sub-hypothesis based on the evidence reported in the studies. We identified 150 studies addressing IMH. The majority of studies support IMH, but the evidence comes from studies with different aims and questions. Supporting studies at the community or ecosystem level are currently rare. Evidence is scarce for marine habitats and vertebrates. Few sub-hypotheses are questioned by more than 50\% of the evaluated studies, indicating that non-native species do not affect each other's survival, growth, reproduction, abundance, density or biomass in reciprocal A ↔ B interactions. With the HoH for IMH presented here, we can monitor progress in empirical tests and evidences of IMH. For instance, more tests at the community and ecosystem level are needed, as these are necessary to address the core of this hypothesis.}, language = {en} } @article{ChenBornhorstAschner2018, author = {Chen, Pan and Bornhorst, Julia and Aschner, Michael}, title = {Manganese metabolism in humans}, series = {Frontiers in Bioscience-Landmark}, volume = {23}, journal = {Frontiers in Bioscience-Landmark}, number = {9}, publisher = {Frontiers in Bioscience INC}, address = {Irvine}, issn = {1093-9946}, doi = {10.2741/4665}, pages = {1655 -- 1679}, year = {2018}, abstract = {Manganese (Mn) is an essential nutrient for intracellular activities; it functions as a cofactor for a variety of enzymes, including arginase, glutamine synthetase (GS), pyruvate carboxylase and Mn superoxide dismutase (Mn-SOD). Through these metalloproteins, Mn plays critically important roles in development, digestion, reproduction, antioxidant defense, energy production, immune response and regulation of neuronal activities. Mn deficiency is rare. In contrast Mn poisoning may be encountered upon overexposure to this metal. Excessive Mn tends to accumulate in the liver, pancreas, bone, kidney and brain, with the latter being the major target of Mn intoxication. Hepatic cirrhosis, polycythemia, hypermanganesemia, dystonia and Parkinsonism-like symptoms have been reported in patients with Mn poisoning. In recent years, Mn has come to the forefront of environmental concerns due to its neurotoxicity. Molecular mechanisms of Mn toxicity include oxidative stress, mitochondrial dysfunction, protein misfolding, endoplasmic reticulum (ER) stress, autophagy dysregulation, apoptosis, and disruption of other metal homeostasis. The mechanisms of Mn homeostasis are not fully understood. Here, we will address recent progress in Mn absorption, distribution and elimination across different tissues, as well as the intracellular regulation of Mn homeostasis in cells. We will conclude with recommendations for future research areas on Mn metabolism.}, language = {en} }