16,979 research outputs found

    ICF core sets for low back pain: do they include what matters to patients?

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    To investigate whether the International Classification of Functioning Disability and Health (ICF) Core Sets for low back pain encompass the key functional problems of patients

    Tissue eosinophilia and eosinophil degranulation in Riedel's invasive fibrous thyroiditis.

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    The etiology of Riedel's invasive fibrous thyroiditis (IFT) has remained obscure. This rare disorder has been confused in the past with the more common fibrous variant of Hashimoto's disease. The typical histological features of IFT, in particular the presence of an invasive fibrosclerotic process in conjunction with a prominent chronic inflammatory infiltrate, suggest that the release of fibrogenic cytokines and other factors from these cellular infiltrates may play an important role in the pathogenesis of this condition. Our observations in routinely processed tissue sections obtained from patients with documented IFT of striking tissue eosinophilia led us to hypothesize that eosinophils and their products may play a role in the evolution of this disease. Immunofluorescence staining with affinity-purified polyclonal rabbit antibody directed against human eosinophil granule major basic protein revealed marked tissue eosinophilia and abundant extracellular deposition of major basic protein in all specimens from 16 patients with IFT. By contrast, only occasional eosinophils and no extracellular major basic protein were detected in control thyroid tissues obtained from patients with multinodular goiter, Graves' disease, Hashimoto's disease, and normal thyroid tissue. The presence of marked eosinophil infiltration and extracellular major basic protein deposition in IFT and other associated fibrosclerotic conditions suggests a role for eosinophils and their products in propagating the fibrogenesis seen in IFT

    Labeling research in support of through-the-season area estimation

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    The development of LANDSAT-based through-the-season labeling procedures for corn and soybeans is discussed. A model for predicting labeling accuracy within key time periods throughout the growing season is outlined. Two methods for establishing the starting point of one key time period, viz., early season, are described. In addition, spectral-temporal characteristics for separating crops in the early season time period are discussed

    Agaricomycetes of Ontario Tallgrass Prairies

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    This study provides the first characterization of the Agaricomycetes of Ontario tallgrass prairies, assesses the influence of various environmental factors, and compares results of aboveground mushroom surveys with belowground high-throughput DNA sequencing. Overall, the Mycenaceae, Ceratobasidiaceae and Polyporaceae were the most abundant, and the Clavariaceae, Entolomataceae and Sebacinaceae the richest in species. Position along a transect (geographic region) was the primary factor differentiating Agaricomycete composition of sites whereas tillage history and soil organic carbon content were secondary. The Hygrophoraceae and Clavariaceae were associated with pristine sites, and Minimedusa spp. associated with tillage. The belowground method captured most of the minor clades found aboveground and several more unique ones. The aboveground method retrieved 74 species and the belowground method 256 OTUs, with only eight shared between them

    Users manual for the US baseline corn and soybean segment classification procedure

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    A user's manual for the classification component of the FY-81 U.S. Corn and Soybean Pilot Experiment in the Foreign Commodity Production Forecasting Project of AgRISTARS is presented. This experiment is one of several major experiments in AgRISTARS designed to measure and advance the remote sensing technologies for cropland inventory. The classification procedure discussed is designed to produce segment proportion estimates for corn and soybeans in the U.S. Corn Belt (Iowa, Indiana, and Illinois) using LANDSAT data. The estimates are produced by an integrated Analyst/Machine procedure. The Analyst selects acquisitions, participates in stratification, and assigns crop labels to selected samples. In concert with the Analyst, the machine digitally preprocesses LANDSAT data to remove external effects, stratifies the data into field like units and into spectrally similar groups, statistically samples the data for Analyst labeling, and combines the labeled samples into a final estimate
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