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Studies of the fragmentation of jets into charged particles in heavy-ion collisions can help in understanding the mechanism of jet quenching by the hot and dense QCD matter created in such collisions, the quark-gluon plasma. These proceedings present a measurement of the angular distribution of charged particles around the jet axis in root s(NN) = 5.02 TeV Pb+Pb and pp collisions, done using the ATLAS detector at the LHC. The measurement is performed inside jets reconstructed with the anti-k(t) algorithm with radius parameter R = 0.4, and is extended to regions outside the jet cone. Results are presented as a function of Pb+Pb collision centrality, and both jet and charged-particle transverse momenta.
DNA methylation acts as a major epigenetic modification in mammals, characterized by the transfer of a methyl group to a cytosine. DNA methylation plays a pivotal role in regulating normal development, and misregulation in cells leads to an abnormal phenotype as is seen in several cancers. Any mutations or expression anomalies of genes encoding regulators of DNA methylation may lead to abnormal expression of critical molecules. A comprehensive genomic study encompassing all the genes related to DNA methylation regulation in relation to breast cancer is lacking. We used genomic and transcriptomic datasets from the Cancer Genome Atlas (TGCA) Pan-Cancer Atlas, Genotype-Tissue Expression (GTEx) and microarray platforms and conducted in silico analysis of all the genes related to DNA methylation with respect to writing, reading and erasing this epigenetic mark. Analysis of mutations was conducted using cBioportal, while Xena and KMPlot were utilized for expression changes and patient survival, respectively. Our study identified multiple mutations in the genes encoding regulators of DNA methylation. The expression profiling of these showed significant differences between normal and disease tissues. Moreover, deregulated expression of some of the genes, namely DNMT3B, MBD1, MBD6, BAZ2B, ZBTB38, KLF4, TET2 and TDG, was correlated with patient prognosis. The current study, to our best knowledge, is the first to provide a comprehensive molecular and genetic profile of DNA methylation machinery genes in breast cancer and identifies DNA methylation machinery as an important determinant of the disease progression. The findings of this study will advance our understanding of the etiology of the disease and may serve to identify alternative targets for novel therapeutic strategies in cancer.