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| http://dx.doi.org/10.46234/ccdcw2024.211 | DOI Listing |
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Coupling tree-ring and geomorphic analyses to reconstruct the 1950s massive Glacier Lake Outburst Flood at Grosse Glacier, Chilean Patagonia.
Sci Total Environ
January 2025
Climate Change Impacts and Risks in the Anthropocene (C-CIA), Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland; dendrolab.ch, Department of Earth Sciences, University of Geneva, Geneva, Switzerland; Department F.-A. Forel for Environmental and Aquatic Sciences, University of Geneva, Switzerland.
Over recent decades, global warming has led to sustained glacier mass reduction and the formation of glacier lakes dammed by potentially unstable moraines. When such dams break, devastating Glacial Lake Outburst Floods (GLOFs) can occur in high mountain environments with catastrophic effects on populations and infrastructure. To understand the occurrence of GLOFs in space and time, build frequency-magnitude relationships for disaster risk reduction or identify regional links between GLOF frequency and climate warming, comprehensive databases are critically needed.
View Article and Find Full Text PDFLeveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024).
JMIR Public Health Surveill
January 2025
Laboratoire AGEIS, Université Grenoble Alpes, La Tronche Cedex, France.
Background: Although agricultural health has gained importance, to date, much of the existing research relies on traditional epidemiological approaches that often face limitations related to sample size, geographic scope, temporal coverage, and the range of health events examined. To address these challenges, a complementary approach involves leveraging and reusing data beyond its original purpose. Administrative health databases (AHDs) are increasingly reused in population-based research and digital public health, especially for populations such as farmers, who face distinct environmental risks.
View Article and Find Full Text PDFThe potential role of machine learning and deep learning in differential diagnosis of Alzheimer's disease and FTD using imaging biomarkers: A review.
Neuroradiol J
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Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Iran.
Introduction: The prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies. Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are two prominent neurodegenerative conditions that present diagnostic challenges due to overlapping symptoms. To address these challenges, experts utilize a range of imaging techniques, including magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT).
View Article and Find Full Text PDFAccurate Enthalpies of Formation for Bioactive Compounds from High-Level Ab Initio Calculations with Detailed Conformational Treatment: A Case of Cannabinoids.
J Chem Theory Comput
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Thermodynamics Research Center, National Institute of Standards and Technology, Boulder, Colorado 80305-3337, United States.
Our recently developed approach based on the local coupled-cluster with single, double, and perturbative triple excitation [LCCSD(T)] model gives very efficient means to compute the ideal-gas enthalpies of formation. The expanded uncertainty (95% confidence) of the method is about 3 kJ·mol for medium-sized compounds, comparable to typical experimental measurements. Larger compounds of interest often exhibit many conformations that can significantly differ in intramolecular interactions.
View Article and Find Full Text PDFA conserved fungal Knr4/Smi1 protein is crucial for maintaining cell wall stress tolerance and host plant pathogenesis.
PLoS Pathog
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Strategic Area: Protecting Crops and the Environment, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.
Filamentous plant pathogenic fungi pose significant threats to global food security, particularly through diseases like Fusarium Head Blight (FHB) and Septoria Tritici Blotch (STB) which affects cereals. With mounting challenges in fungal control and increasing restrictions on fungicide use due to environmental concerns, there is an urgent need for innovative control strategies. Here, we present a comprehensive analysis of the stage-specific infection process of Fusarium graminearum in wheat spikes by generating a dual weighted gene co-expression network (WGCN).
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