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Ecological networks are more sensitive to plant than to animal extinction under climate change
(2016)
Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.
Purpose: High precision radiosurgery demands comprehensive delivery-quality-assurance techniques. The use of a liquid-filled ion-chamber-array for robotic-radiosurgery delivery-quality-assurance was investigated and validated using several test scenarios and routine patient plans.
Methods and material: Preliminary evaluation consisted of beam profile validation and analysis of source–detector-distance and beam-incidence-angle response dependence. The delivery-quality-assurance analysis is performed in four steps: (1) Array-to-plan registration, (2) Evaluation with standard Gamma-Index criteria (local-dose-difference ⩽ 2%, distance-to-agreement ⩽ 2 mm, pass-rate ⩾ 90%), (3) Dose profile alignment and dose distribution shift until maximum pass-rate is found, and (4) Final evaluation with 1 mm distance-to-agreement criterion. Test scenarios consisted of intended phantom misalignments, dose miscalibrations, and undelivered Monitor Units. Preliminary method validation was performed on 55 clinical plans in five institutions.
Results: The 1000SRS profile measurements showed sufficient agreement compared with a microDiamond detector for all collimator sizes. The relative response changes can be up to 2.2% per 10 cm source–detector-distance change, but remains within 1% for the clinically relevant source–detector-distance range. Planned and measured dose under different beam-incidence-angles showed deviations below 1% for angles between 0° and 80°. Small-intended errors were detected by 1 mm distance-to-agreement criterion while 2 mm criteria failed to reveal some of these deviations. All analyzed delivery-quality-assurance clinical patient plans were within our tight tolerance criteria.
Conclusion: We demonstrated that a high-resolution liquid-filled ion-chamber-array can be suitable for robotic radiosurgery delivery-quality-assurance and that small errors can be detected with tight distance-to-agreement criterion. Further improvement may come from beam specific correction for incidence angle and source–detector-distance response.
Background and aim. In the fall of 2013, the US Centers for Disease Control and Prevention (CDC) published a preliminary report on a cluster of liver disease cases that emerged in Hawaii in the summer 2013. This report claimed a temporal association as sufficient evidence that OxyELITE Pro (OEP), a dietary supplement (DS) mainly for weight loss, was the cause of this mysterious cluster. However, the presented data were inconsistent and required a thorough reanalysis.
Material and methods. To further investigate the cause(s) of this cluster, we critically evaluated redacted raw clinical data of the cluster patients, as the CDC report received tremendous publicity in local and nationwide newspapers and television. This attention put regulators and physicians from the medical center in Honolulu that reported the cluster, under enormous pressure to succeed, risking biased evaluations and hasty conclusions.
Results. We noted pervasive bias in the documentation, conclusions, and public statements, also poor quality of case management. Among the cases we reviewed, many causes unrelated to any DS were evident, including decompensated liver cirrhosis, acute liver failure by acetaminophen overdose, acute cholecystitis with gallstones, resolving acute hepatitis B, acute HSV and VZV hepatitis, hepatitis E suspected after consumption of wild hog meat, and hepatotoxicity by acetaminophen or ibuprofen. Causality assessments based on the updated CIOMS scale confirmed the lack of evidence for any DS including OEP as culprit for the cluster.
Conclusions. Thus, the Hawaii liver disease cluster is now best explained by various liver diseases rather than any DS, including OEP.