279 research outputs found

    Disentangling interventions to reduce fear of falling in community-dwelling older people: a systematic review and meta-analysis of intervention components

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    © 2021 The Author(s). Purpose: Fear of falling (FoF) is a common and debilitating problem for older people. Most multicomponent interventions show only moderate effects. Exploring the effective components may help in the optimization of treatments for FoF. Materials and methods: In a systematic review of five scientific literature databases, we identified randomized controlled trials with older community-dwelling people that included FoF as an outcome. There was no restriction on types of interventions. Two reviewers extracted information about outcomes and content of interventions. Intervention content was coded with a coding scheme of 68 intervention components. We compared all studies with a component to those without using univariate meta-regressions. Results: Sixty-six studies, reporting on 85 interventions, were included in the systematic review. In the meta-regressions (n = 49), few components were associated with intervention effects at the first available follow up after the intervention, but interventions with meditation, holistic exercises (such as Tai Chi or Pilates) or body awareness were significantly more effective than interventions without these components. Interventions with self-monitoring, balance exercises, or tailoring were less effective compared to those without these components. Conclusions: The identified components may be important for the design and optimization of treatments to reduce FoF.Implications for rehabilitation Fear of falling (FoF) is a common and debilitating issue among older people and multicomponent interventions usually show only small to moderate effects on FoF. This review and meta-analysis investigated 68 intervention components and their relation to intervention effects on FoF. Interventions with meditation, holistic exercises (such as Tai Chi), or body awareness are more effective than interventions without these components. Clinicians aiming to reduce FoF may recommend selected interventions to older people taking into account the current knowledge of intervention components.Maastricht University

    Evaluation of copy-number variants as modifiers of breast and ovarian cancer risk for BRCA1 pathogenic variant carriers.

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    Genome-wide studies of patients carrying pathogenic variants (mutations) in BRCA1 or BRCA2 have reported strong associations between single-nucleotide polymorphisms (SNPs) and cancer risk. To conduct the first genome-wide association analysis of copy-number variants (CNVs) with breast or ovarian cancer risk in a cohort of 2500 BRCA1 pathogenic variant carriers, CNV discovery was performed using multiple calling algorithms and Illumina 610k SNP array data from a previously published genome-wide association study. Our analysis, which focused on functionally disruptive genomic deletions overlapping gene regions, identified a number of loci associated with risk of breast or ovarian cancer for BRCA1 pathogenic variant carriers. Despite only including putative deletions called by at least two or more algorithms, detection of selected CNVs by ancillary molecular technologies only confirmed 40% of predicted common (>1% allele frequency) variants. These include four loci that were associated (unadjusted P<0.05) with breast cancer (GTF2H2, ZNF385B, NAALADL2 and PSG5), and two loci associated with ovarian cancer (CYP2A7 and OR2A1). An interesting finding from this study was an association of a validated CNV deletion at the CYP2A7 locus (19q13.2) with decreased ovarian cancer risk (relative risk=0.50, P=0.007). Genomic analysis found this deletion coincides with a region displaying strong regulatory potential in ovarian tissue, but not in breast epithelial cells. This study highlighted the need to verify CNVs in vitro, but also provides evidence that experimentally validated CNVs (with plausible biological consequences) can modify risk of breast or ovarian cancer in BRCA1 pathogenic variant carriers.European Journal of Human Genetics advance online publication, 1 February 2017; doi:10.1038/ejhg.2016.203.Multiple funders listed in the article

    Quantifying fracture geometry with X-ray tomography: Technique of Iterative Local Thresholding (TILT) for 3D image segmentation

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    This paper presents a new method—the Technique of Iterative Local Thresholding (TILT)—for processing 3D X-ray computed tomography (xCT) images for visualization and quantification of rock fractures. The TILT method includes the following advancements. First, custom masks are generated by a fracture-dilation procedure, which significantly amplifies the fracture signal on the intensity histogram used for local thresholding. Second, TILT is particularly well suited for fracture characterization in granular rocks because the multi-scale Hessian fracture (MHF) filter has been incorporated to distinguish fractures from pores in the rock matrix. Third, TILT wraps the thresholding and fracture isolation steps in an optimized iterative routine for binary segmentation, minimizing human intervention and enabling automated processing of large 3D datasets. As an illustrative example, we applied TILT to 3D xCT images of reacted and unreacted fractured limestone cores. Other segmentation methods were also applied to provide insights regarding variability in image processing. The results show that TILT significantly enhanced separability of grayscale intensities, outperformed the other methods in automation, and was successful in isolating fractures from the porous rock matrix. Because the other methods are more likely to misclassify fracture edges as void and/or have limited capacity in distinguishing fractures from pores, those methods estimated larger fracture volumes (up to 80 %), surface areas (up to 60 %), and roughness (up to a factor of 2). These differences in fracture geometry would lead to significant disparities in hydraulic permeability predictions, as determined by 2D flow simulations
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