52 research outputs found

    Evaluation of structure specification in linear mixed models for modeling the spatial effects in tree height-diamater relationships

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    In recent years, linear mixed models (LMM) have become more popularto deal with spatial effects in forestry and ecological data. In this study, different structure specifications of linear mixed model were applied to model tree height-diameter relationships, including LMM with random blocks only (LMM-block), LMM with spatial covariance only (LMM-covariance), and the combination of the last two (LMM-block-covariance). Further, the between group heterogeneous variances were incorporated into LMM-covariance and LMM-block-covariance. The results indicated that, in general, LMM-covariance significantly reduced spatial autocorrelation in model residuals, while LMM-block was effective in dealing with spatial heterogeneity. LMM-blocktreated the blocks as random effects and avoided the estimation of parameters of the variogram model. Thus, it produced better model predictions than LMM-covariance. LMM-block-covariance took both block effects and spatial covariance into account, and significantly improve model fitting. However, it did not produce better model predictions due to the increase of model complexity and estimation of the local variogram within each block

    Rifaximin Alters Intestinal Microbiota and Prevents Progression of Ankylosing Spondylitis in Mice

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    Recently, accumulating evidence has suggested that gut microbiota may be involved in the occurrence and development of ankylosing spondylitis (AS). It has been suggested that rifaximin have the ability to modulate the gut bacterial communities, prevent inflammatory response, and modulate gut barrier function. The goal of this work is to evaluate the protective effects of rifaximin in fighting AS and to elucidate the potential underlying mechanism. Rifaximin were administered to the proteoglycan (PG)-induced AS mice for 4 consecutive weeks. The disease severity was measured with the clinical and histological of arthritis and spondylitis. Intestinal histopathological, pro-inflammatory cytokine levels and the intestinal mucosal barrier were evaluated. Then, western blot was performed to explore the toll-like receptor 4 (TLR-4) signal transducer and NF-κB expression. Stool samples were collected to analyze the differences in the gut microbiota via next-generation sequencing of 16S rDNA. We found that rifaximin significantly reduced the severity of AS and resulted in down-regulation of inflammatory factors, such as TNF-α, IL-6, IL-17A, and IL-23. Meanwhile, rifaximin prevented ileum histological alterations, restored intestinal barrier function and inhibited TLR-4/NF-κB signaling pathway activation. Rifaximin also changed the gut microbiota composition with increased Bacteroidetes/Firmicutes phylum ratio, as well as selectively promoting some probiotic populations, including Lactobacillales. Our results suggest that rifaximin suppressed progression of AS and regulated gut microbiota in AS mice. Rifaximin might be useful as a novel treatment for AS

    Evaluation of structure specification in linear mixed models for modeling the spatial effects in tree height-diamater relationships

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    ., 2013. Evaluation of structure specifi cation in linear mixed models for modeling the spatial effects in tree height-diamater relationships. Ann. For. Res. 56(1): 137-148, 2013. Abstract. In recent years, linear mixed models (LMM) have become more popular to deal with spatial effects in forestry and ecological data. In this study, different structure specifications of linear mixed model were applied to model tree height-diameter relationships, including LMM with random blocks only (LMM-block), LMM with spatial covariance only (LMM-covariance), and the combination of the last two (LMM-block-covariance). Further, the betweengroup heterogeneous variances were incorporated into LMM-covariance and LMM-block-covariance. The results indicated that, in general, LMM-covariance significantly reduced spatial autocorrelation in model residuals, while LMM-block was effective in dealing with spatial heterogeneity. LMM-block treated the blocks as random effects and avoided the estimation of parameters of the variogram model. Thus, it produced better model predictions than LMM-covariance. LMM-block-covariance took both block effects and spatial covariance into account, and significantly improve model fitting. However, it did not produce better model predictions due to the increase of model complexity and estimation of the local variogram within each block

    A Possible Role of Intestinal Microbiota in the Pathogenesis of Ankylosing Spondylitis

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    Ankylosing spondylitis (AS) is a chronic inflammatory disease primarily affecting the sacroiliac joints and the spine, for which the pathogenesis is thought to be a result of the combination of host genetic factors and environmental triggers. However, the precise factors that determine one’s susceptibility to AS remain to be unraveled. With 100 trillion bacteria residing in the mammalian gut having established a symbiotic relation with their host influencing many aspects of host metabolism, physiology, and immunity, a growing body of evidence suggests that intestinal microbiota may play an important role in AS. Several mechanisms have been suggested to explain the potential role of the microbiome in the etiology of AS, such as alterations of intestinal permeability, stimulation of immune responses, and molecular mimicry. In this review, the existing evidence for the involvement of the microbiome in AS pathogenesis was discussed and the potential of intestinal microbiome-targeting strategies in the prevention and treatment of AS was evaluated
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