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https://www.selleckchem.com/products/alexidine-dihydrochloride.html We aimed to use data-driven glucose pattern analysis to unveil the correlation between the metrics reflecting glucose fluctuation and beta-cell function, and to identify the possible role of this metric in diabetes classification. In total, 78 participants with type 1 diabetes and 59 with type 2 diabetes were enrolled in this study. All participants wore a flash glucose monitoring system, and glucose data were collected. A detrended fluctuation function (DFF) was utilized to extract glucose fluctuation information from flash glucose monitoring data and a DFF-based glucose fluctuation metric was proposed. For the entire study population, a significant negative correlation between the DFF-based glucose fluctuation metric and fasting C-peptide was observed (r = -0.667; P <.001), which was larger than the correlation coefficient between the fasting C-peptide and mean amplitude of plasma glucose excursions (r = -0.639; P < .001), standard deviation (r = -0.649; P <.001), mean blood glucose (r = -0.5fication, and a large-scale, multicentre study will be needed in the future. Our study first proposed the possible role of data-driven analysis acquired glucose metric in predicting beta-cell function and diabetes classification, and a large-scale, multicentre study will be needed in the future.Red pitaya (Hylocereus polyrhizus) is widely cultivated in southern and southwestern China. To provide a basis for studying the molecular mechanisms of the ripening of this fruit, we carried out RNA-seq analysis to identify differentially and stably expressed unigenes. The latter may serve as a resource of potential reference genes for normalization of target gene expression determined using qRT-PCR. We selected 11 candidate reference genes from our RNA-seq analysis of red pitaya fruit ripening (ACT7, EF-1α, IF-4α, PTBP, PP2A, EF2, Hsp70, GAPDH, DNAJ, TUB and CYP), as well as β-ACT, which has been used as a reference ge

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