55 research outputs found

    Pancreatitis after percutaneous ethanol injection into HCC: a minireview of the literature

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    Deaths after percutaneous ethanol injection (PEI) into hepatocellular carcinoma (HCC) may occur within a few hours to a few days following the procedure because of hemoperitoneum and haemorrhage from oesophageal varices or hepatic insufficiency. Pancreatitis has been recently reported as a rare lethal complication of intra-arterial PEI, another modality for treating HCCs. In this minireview, we analyze the literature concerning the development of acute pancreatitis after PEI. Pathogenesis of pancreatitis from opioids and ethanol is also addressed. Treatment with opioids to reduce the patient's abdominal pain after PEI in combination with the PEI itself may lead to direct toxic effects, thus favouring the development of pancreatitis

    Summer warming explains widespread but not uniform greening in the Arctic tundra biome

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    Arctic warming can influence tundra ecosystem function with consequences for climate feedbacks, wildlife and human communities. Yet ecological change across the Arctic tundra biome remains poorly quantified due to field measurement limitations and reliance on coarse-resolution satellite data. Here, we assess decadal changes in Arctic tundra greenness using time series from the 30 m resolution Landsat satellites. From 1985 to 2016 tundra greenness increased (greening) at ~37.3% of sampling sites and decreased (browning) at ~4.7% of sampling sites. Greening occurred most often at warm sampling sites with increased summer air temperature, soil temperature, and soil moisture, while browning occurred most often at cold sampling sites that cooled and dried. Tundra greenness was positively correlated with graminoid, shrub, and ecosystem productivity measured at field sites. Our results support the hypothesis that summer warming stimulated plant productivity across much, but not all, of the Arctic tundra biome during recent decades

    Shape description and matching using integral invariants on eccentricity transformed images

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    Matching occluded and noisy shapes is a problem frequently encountered in medical image analysis and more generally in computer vision. To keep track of changes inside the breast, for example, it is important for a computer aided detection system to establish correspondences between regions of interest. Shape transformations, computed both with integral invariants (II) and with geodesic distance, yield signatures that are invariant to isometric deformations, such as bending and articulations. Integral invariants describe the boundaries of planar shapes. However, they provide no information about where a particular feature lies on the boundary with regard to the overall shape structure. Conversely, eccentricity transforms (Ecc) can match shapes by signatures of geodesic distance histograms based on information from inside the shape; but they ignore the boundary information. We describe a method that combines the boundary signature of a shape obtained from II and structural information from the Ecc to yield results that improve on them separately

    ICAR: endoscopic skull‐base surgery

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    Pancreatic Physiology

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    Precision medicine in pancreatic disease-knowledge gaps and research opportunities: Summary of a national institute of diabetes and digestive and kidney diseases workshop

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    A workshop on research gaps and opportunities for Precision Medicine in Pancreatic Disease was sponsored by the National Institute of Diabetes and Digestive Kidney Diseases on July 24, 2019, in Pittsburgh. The workshop included an overview lecture on precision medicine in cancer and 4 sessions: (1) general considerations for the application of bioinformatics and artificial intelligence; (2) omics, the combination of risk factors and biomarkers; (3) precision imaging; and (4) gaps, barriers, and needs to move from precision to personalized medicine for pancreatic disease. Current precision medicine approaches and tools were reviewed, and participants identified knowledge gaps and research needs that hinder bringing precision medicine to pancreatic diseases. Most critical were (a) multicenter efforts to collect large-scale patient data sets from multiple data streams in the context of environmental and social factors; (b) new information systems that can collect, annotate, and quantify data to inform disease mechanisms; (c) novel prospective clinical trial designs to test and improve therapies; and (d) a framework for measuring and assessing the value of proposed approaches to the health care system. With these advances, precision medicine can identify patients early in the course of their pancreatic disease and prevent progression to chronic or fatal illness
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