Shah Deleon (motherthomas9)

Subclinical thyroid disorders have been associated with atherosclerosis and increased cardiovascular risk. As triglyceride-rich lipoprotein particles (TRLPs) have recently emerged as a casual factor for atherogenesis, the aim of this study was to evaluate the relationship between subclinical hypo- and hyperthyroidism and TRLP subfractions. We selected 5066 participants from the ELSA-Brasil cohort with available data of thyroid function and lipid profile measured by nuclear magnetic resonance (NMR) spectroscopy. Individuals were divided into 3 groups by baseline thyroid function (subclinical hypothyroidism, euthyroidism, and subclinical hyperthyroidism). Triglyceride-rich lipoprotein particle subfractions were analyzed through NMR spectroscopy. To examine the association between TRLP subfractions and thyroid function, we conducted univariate and multivariate linear regression models adjusted for demographic characteristics, body mass index, diabetes, smoking status, and alcohol use. Of 3304 individuals, 54% were women, with a mean age of 50.6 ± 8.7 years, 51% white, and 53% with at least a college education. Of these individuals, 92% were euthyroid, whereas 6.8% had subclinical hypothyroidism and 1.2% had subclinical hyperthyroidism. The univariate linear regression showed that very small TRLPs (P = 0.026) and very large TRLPs (P = 0.008) were statistically increased in subclinical hypothyroidism when compared with euthyroidism. In subclinical hyperthyroidism, there was a reduction in total TRLPs (P = 0.003), seemingly driven by reduced very small TRLPs (P = 0.067). The findings were confirmed when adjusted for demographic characteristics, as well as comorbidities. This study suggests that subclinical hypothyroidism is associated with very small and very large TRLPs, which are related to an unfavorable atherogenic profile. Subclinical hyperthyroidism is associated to lower very small TRLPs. Cancer somatic driver mutations associated with genes within a pathway often show a mutually exclusive pattern across a cohort of patients. This mutually exclusive mutational signal has been frequently used to distinguish driver from passenger mutations and to investigate relationships among driver mutations. Current methods for de novo discovery of mutually exclusive mutational patterns are limited because the heterogeneity in background mutation rate can confound mutational patterns, and the presence of highly mutated genes can lead to spurious patterns. In addition, most methods only focus on a limited number of pre-selected genes and are unable to perform genome-wide analysis due to computational inefficiency. We introduce a statistical framework, MEScan, for accurate and efficient mutual exclusivity analysis at the genomic scale. Our framework contains a fast and powerful statistical test for mutual exclusivity with adjustment of the background mutation rate and impact of highly mutated genes, and a multi-step procedure for genome-wide screening with the control of false discovery rate. We demonstrate that MEScan more accurately identifies mutually exclusive gene sets than existing methods and is at least two orders of magnitude faster than most methods. By applying MEScan to data from four different cancer types and pan-cancer, we have identified several biologically meaningful mutually exclusive gene sets. MEScan is available as an R package at https//github.com/MarkeyBBSRF/MEScan. Supplementary data are available at Bioinformatics online. Supplementary data are available at Bioinformatics online.The focus of this review is maternal nutrition during the periconceptual period and offspring developmental outcomes in beef cattle, with an emphasis on the first 50 d of gestation, which represents the embryonic period. Animal agriculture in general, and specifically the beef cattle industry, currently faces immense challenges. The world needs to significantly increase its output of animal foo