158 research outputs found

    Fewer Basins Will Follow Their Budyko Curves Under Global Warming and Fossil‐Fueled Development

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    The Budyko framework consists of a curvilinear relationship between the evaporative ratio (i.e., actual evaporation over precipitation) and the aridity index (i.e., potential evaporation over precipitation) and defines evaporation's water and energy limits. A basin's movement within the Budyko space illustrates its hydroclimatic change and helps identify the main drivers of change. On the one hand, long-term aridity changes drive evaporative ratio changes, moving basins along their Budyko curves. On the other hand, historical human development can cause river basins to deviate from their curves. The question is if basins will deviate or follow their Budyko curves under the future effects of global warming and related human developments. To answer this, we quantify the movement in the Budyko space of 405 river basins from 1901–1950 to 2051–2100 based on the outputs of seven models from the Coupled Model Intercomparison Project - Phase 6 (CMIP6). We account for the implications of using different potential evaporation models and study low- and high-emissions scenarios. We find considerable differences of movement in Budyko space regarding direction and intensity when using the two estimates of potential evaporation. However, regardless of the potential evaporation estimate and the scenario used, most river basins will not follow their reference Budyko curves (>72%). Furthermore, the number of basins not following their curves increases under high greenhouse gas emissions and fossil-fueled development SP585 and across dry and wet basin groups. We elaborate on the possible explanations for a large number of basins not following their Budyko curves

    Poor correlation between large-scale environmental flow violations and freshwater biodiversity: implications for water resource management and the freshwater planetary boundary

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    The freshwater ecosystems around the world are degrading, such that maintaining environmental flow1 (EF) in river networks is critical to their preservation. The relationship between streamflow alterations (subsequent EF violations2) and the freshwater biodiversity response is well established at the scale of stream reaches or small basins (∼&lt;100 km2). However, it is unclear if this relationship is robust at larger scales, even though there are large-scale initiatives to legalize the EF requirement. Moreover, EFs have been used in assessing a planetary boundary3 for freshwater. Therefore, this study intends to conduct an exploratory evaluation of the relationship between EF violation and freshwater biodiversity at globally aggregated scales and for freshwater ecoregions. Four EF violation indices (severity, frequency, probability of shifting to a violated state, and probability of staying violated) and seven independent freshwater biodiversity indicators (calculated from observed biota data) were used for correlation analysis. No statistically significant negative relationship between EF violation and freshwater biodiversity was found at global or ecoregion scales. These findings imply the need for a holistic bio-geo-hydro-physical approach in determining the environmental flows. While our results thus suggest that streamflow and EF may not be the only determinant of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods (e.g., including water temperature, water quality, intermittency, connectivity, etc.) or with other biodiversity data or metrics.</p

    Integrating the Water Planetary Boundary With Water Management From Local to Global Scales

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    The planetary boundaries framework defines the "safe operating space for humanity" represented by nine global processes that can destabilize the Earth System if perturbed. The water planetary boundary attempts to provide a global limit to anthropogenic water cycle modifications, but it has been challenging to translate and apply it to the regional and local scales at which water problems and management typically occur. We develop a cross-scale approach by which the water planetary boundary could guide sustainable water management and governance at subglobal contexts defined by physical features (e.g., watershed or aquifer), political borders (e.g., city, nation, or group of nations), or commercial entities (e.g., corporation, trade group, or financial institution). The application of the water planetary boundary at these subglobal contexts occurs via two approaches: (i) calculating fair shares, in which local water cycle modifications are compared to that context's allocation of the global safe operating space, taking into account biophysical, socioeconomic, and ethical considerations; and (ii) defining a local safe operating space, in which interactions between water stores and Earth System components are used to define local boundaries required for sustaining the local water system in stable conditions, which we demonstrate with a case study of the Cienaga Grande de Santa Marta wetlands in Colombia. By harmonizing these two approaches, the water planetary boundary can ensure that water cycle modifications remain within both local and global boundaries and complement existing water management and governance approaches

    Model-based parametric study of frontostriatal abnormalities in schizophrenia patients

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    <p>Abstract</p> <p>Background</p> <p>Several studies have suggested that the activity of the prefrontal cortex (PFC) and the dopamine (DA) release in the striatum has an inverse relationship. One would attribute this relationship primarily to the circuitry comprised of the glutamatergic projection from the PFC to the striatum and the GABAergic projection from the striatum to the midbrain DA nucleus. However, this circuitry has not characterized satisfactorily yet, so that no quantitative analysis has ever been made on the activities of the PFC and the striatum and also the DA release in the striatum.</p> <p>Methods</p> <p>In this study, a system dynamics model of the corticostriatal system with dopaminergic innervations is constructed to describe the relationships between the activities of the PFC and the striatum and the DA release in the striatum. By taking published receptor imaging data from schizophrenia patients and healthy subjects into this model, this article analyzes the effects of striatal D2 receptor activation on the balance of the activity and neurotransmission in the frontostriatal system of schizophrenic patients in comparison with healthy controls.</p> <p>Results</p> <p>The model predicts that the suppressive effect by D2 receptors at the terminals of the glutamatergic afferents to the striatum from the PFC enhances the hypofrontality-induced elevation of striatal DA release by at most 83%. The occupancy-based estimation of the 'optimum' D2 receptor occupancy by antipsychotic drugs is 52%. This study further predicts that patients with lower PFC activity tend to have greater improvement of positive symptoms following antipsychotic medication.</p> <p>Conclusion</p> <p>This model-based parametric study would be useful for system-level analysis of the brains with psychiatric diseases. It will be able to make reliable prediction of clinical outcome when sufficient data will be available.</p

    Neutrophil depletion reduces edema formation and tissue loss following traumatic brain injury in mice

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    Background: Brain edema as a result of secondary injury following traumatic brain injury (TBI) is a major clinical concern. Neutrophils are known to cause increased vascular permeability leading to edema formation in peripheral tissue, but their role in the pathology following TBI remains unclear. Methods: In this study we used controlled cortical impact (CCI) as a model for TBI and investigated the role of neutrophils in the response to injury. The outcome of mice that were depleted of neutrophils using an anti-Gr-1 antibody was compared to that in mice with intact neutrophil count. The effect of neutrophil depletion on blood-brain barrier function was assessed by Evan's blue dye extravasation, and analysis of brain water content was used as a measurement of brain edema formation (24 and 48 hours after CCI). Lesion volume was measured 7 and 14 days after CCI. Immunohistochemistry was used to assess cell death, using a marker for cleaved caspase-3 at 24 hours after injury, and microglial/macrophage activation 7 days after CCI. Data were analyzed using Mann-Whitney test for non-parametric data. Results: Neutrophil depletion did not significantly affect Evan's blue extravasation at any time-point after CCI. However, neutrophil-depleted mice exhibited a decreased water content both at 24 and 48 hours after CCI indicating reduced edema formation. Furthermore, brain tissue loss was attenuated in neutropenic mice at 7 and 14 days after injury. Additionally, these mice had a significantly reduced number of activated microglia/macrophages 7 days after CCI, and of cleaved caspase-3 positive cells 24 h after injury. Conclusion: Our results suggest that neutrophils are involved in the edema formation, but not the extravasation of large proteins, as well as contributing to cell death and tissue loss following TBI in mice

    What scans we will read: imaging instrumentation trends in clinical oncology

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    Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging
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