140 research outputs found

    Adaptation strategies and approaches for forested watersheds

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    Intentional climate adaptation planning for ecosystems has become a necessary part of the job for natural resource managers and natural resource professionals in this era of non-stationarity. One of the major challenges in adapting ecosystems to climate change is in the translation of broad adaptation concepts to specific, tangible actions. Addressing management goals and values while considering the long-term risks associated with local climate change can make forested watershed management plans more robust to uncertainty and changing conditions. We provide a menu of tiered adaptation strategies, which we developed with a focus on forests of the Midwest and Northeastern U.S., as part of a flexible framework to support the integration of climate change considerations into forested watershed management and conservation activities. This menu encapsulates ideas from the literature into statements that signify climate adaptation intention and provide examples of associated tactics to help ground the concepts in specific actions. Finally, we describe two demonstration projects, shared through the Northern Institute of Applied Climate Science’s Climate Change Response Framework, that have used this Forested Watershed Adaptation Menu and Adaptation Workbook in project-level planning

    Beyond planning tools: Experiential learning in climate adaptation planning and practices

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    In the past decade, several dedicated tools have been developed to help natural resources professionals integrate climate science into their planning and implementation; however, it is unclear how often these tools lead to on-the-ground climate adaptation. Here, we describe a training approach that we developed to help managers effectively plan to execute intentional, climate-informed actions. This training approach was developed through the Climate Change Response Framework (CCRF) and uses active and focused work time and peer-to-peer interaction to overcome observed barriers to using adaptation planning tools. We evaluate the effectiveness of this approach by examining participant evaluations and outlining the progress of natural resources projects that have participated in our trainings. We outline a case study that describes how this training approach can lead to place and context-based climate-informed action. Finally, we describe best practices based on our experience for engaging natural resources professionals and helping them increase their comfort with climate-informed planning

    STAT3 gain-of-function mutations connect leukemia with autoimmune disease by pathological NKG2Dhi CD8+T cell dysregulation and accumulation

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    The association between cancer and autoimmune disease is unexplained, exemplified by T cell large granular lymphocytic leukemia (T-LGL) where gain-of-function (GOF) somatic STAT3 mutations correlate with co -exist-ing autoimmunity. To investigate whether these mutations are the cause or consequence of CD8+ T cell clonal expansions and autoimmunity, we analyzed patients and mice with germline STAT3 GOF mutations. STAT3 GOF mutations drove the accumulation of effector CD8+ T cell clones highly expressing NKG2D, the receptor for stress-induced MHC-class-I-related molecules. This subset also expressed genes for granzymes, perforin, interferon-y, and Ccl5/Rantes and required NKG2D and the IL-15/IL-2 receptor IL2RB for maximal accumula-tion. Leukocyte-restricted STAT3 GOF was sufficient and CD8+ T cells were essential for lethal pathology in mice. These results demonstrate that STAT3 GOF mutations cause effector CD8+ T cell oligoclonal accumu-lation and that these rogue cells contribute to autoimmune pathology, supporting the hypothesis that somatic mutations in leukemia/lymphoma driver genes contribute to autoimmune disease.Peer reviewe

    Do brain networks evolve by maximizing their information flow capacity?

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    We propose a working hypothesis supported by numerical simulations that brain networks evolve based on the principle of the maximization of their internal information flow capacity. We find that synchronous behavior and capacity of information flow of the evolved networks reproduce well the same behaviors observed in the brain dynamical networks of Caenorhabditis elegans and humans, networks of Hindmarsh-Rose neurons with graphs given by these brain networks. We make a strong case to verify our hypothesis by showing that the neural networks with the closest graph distance to the brain networks of Caenorhabditis elegans and humans are the Hindmarsh-Rose neural networks evolved with coupling strengths that maximize information flow capacity. Surprisingly, we find that global neural synchronization levels decrease during brain evolution, reflecting on an underlying global no Hebbian-like evolution process, which is driven by no Hebbian-like learning behaviors for some of the clusters during evolution, and Hebbian-like learning rules for clusters where neurons increase their synchronization

    Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

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    Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
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