996 resultados para Functional trait
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CD44 is the major cell-surface receptor for hyaluronan, which is implicated in cell-cell and cell-matrix adhesion, cell migration, and signaling. Studies have shown that CD44-dependent migration requires CD44 to be shed from the cell surface and that matrix metalloproteinase-mediated cleavage may provide an underlying mechanism. However, the full spectrum of proteases that may participate in CD44 shedding has yet to be defined. In this issue, Anderegg et al. demonstrate that ADAM10, but not ADAM17 or MMP14, mediates constitutive shedding of CD44 in human melanoma cells and that knockdown of ADAM10 blocks the antiproliferative activity of the soluble proteolytic cleavage product of CD44.
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Contient : Préface ; Traité
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The combination of cardiac viability and functional information enhances the identification of different heart tissues in the setting of ischemic heart disease. A method has recently been proposed for obtaining black-blood delayed-enhancement (DE) viability images using the stimulated-echo acquisition mode (STEAM) MRI pulse sequence in a single short breathhold. The method was validated against conventional inversion-recovery (IR) DE images for identifying regions of myocardial infarction (MI). The method was based on the acquisition of three consecutive images of the same anatomical slice. One image has T(1)-weighted contrast in which infarction appears bright. The two other images are used to construct an anatomical image of the heart, which is combined with the first image to produce a black-blood viability image. However, using appropriate modulation and demodulation frequencies, the latter two images bear useful information about myocardial deformation that results in a cardiac strain-encoding (SENC) functional image. In this work, a method is proposed for obtaining three consecutive SENC images in a single acquisition that can be combined to produce a composite image of the heart, which shows both functional and viability information. The proposed technique reduces scan time by one-half, compared with separate acquisitions of functional and viability images, and alleviates misregistration problems caused by separate breathholds.
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Background/Purpose: Gout is a common and excruciatingly painful inflammatory arthritis caused by hyperuricemia. In addition to various lifestyle risk factors, a substantial genetic predisposition to gout has long been recognized. The Global Urate Genetics Consortium (GUGC) has aimed to comprehensively investigate the genetics of serum uric acid and gout using data from _ 140,000 individuals of European-ancestry, 8,340 individuals of Indian ancestry, 5,820 African-Americans, and 15,286 Japanese. Methods: We performed discovery GWAS meta-analyses of serum urate levels (n_110,347 individuals) followed by replication analyses (n_32,813 different individuals). Our gout analysis involved 3,151 cases and 68,350 controls, including 1,036 incident gout cases that met the American College of Rheumatology Criteria. We also examined the association of gout with fractional excretion of uric acid (n_6,799). A weighted genetic urate score was constructed based on the number of risk alleles across urate-associated loci, and their association with the risk of gout was evaluated. Furthermore, we examined implicated transcript expression in cis (expression quantitative trait loci databases) for potential insights into the gene underlying the association signal. Finally, in order to further identify urate-associated genomic regions, we performed functional network analyses that incorporated prior knowledge on molecular interactions in which the gene products of implicated genes operate. Results: We identified and replicated 28 genome-wide significant loci in association with serum urate (P 5_10_8), including all previously-reported loci as well as 18 novel genetic loci. Unlike the majority of previouslyidentified loci, none of the novel loci appeared to be obvious candidates for urate transport. Rather, they were mapped to genes that encode for purine production, transcription, or growth factors with broad downstream responses. Besides SLC2A9 and ABCG2, no additional regions contained SNPs that differed significantly (P _ 5_10_8) between sexes. Urateincreasing alleles were associated with an increased risk of gout for all loci. The urate genetic risk score (ranging from 10 to 45) was significantly associated with an increased odds of prevalent gout (OR per unit increase, 1.11; 95% CI, 1.09-1.14) and incident gout (OR, 1.10; 95% CI, 1.08-1.13). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. Detailed characterization of the loci revealed associations with transcript expression and the fractional excretion of urate. Network analyses implicated the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. Conclusion: The novel genetic candidates identified in this urate/gout consortium study, the largest to date, highlight the importance of metabolic control of urate production and urate excretion. The modulation by signaling processes that influence metabolic pathways such as glycolysis and the pentose phosphate pathway appear to be central mechanisms underpinned by the novel GWAS candidates. These findings may have implications for further research into urate-lowering drugs to treat and prevent gout.