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In ultrarelativistic heavy-ion collisions, the event-by-event variation of the elliptic flow v2 reflects fluctuations in the shape of the initial state of the system. This allows to select events with the same centrality but different initial geometry. This selection technique, Event Shape Engineering, has been used in the analysis of charge-dependent two- and three-particle correlations in Pb–Pb collisions at √sNN=2.76 TeV. The two-particle correlator 〈cos(φα−φβ)〉, calculated for different combinations of charges α and β, is almost independent of v2 (for a given centrality), while the three-particle correlator 〈cos(φα+φβ−2Ψ2)〉 scales almost linearly both with the event v2 and charged-particle pseudorapidity density. The charge dependence of the three-particle correlator is often interpreted as evidence for the Chiral Magnetic Effect (CME), a parity violating effect of the strong interaction. However, its measured dependence on v2 points to a large non-CME contribution to the correlator. Comparing the results with Monte Carlo calculations including a magnetic field due to the spectators, the upper limit of the CME signal contribution to the three-particle correlator in the 10–50% centrality interval is found to be 26–33% at 95% confidence level.
The production of muons from heavy-flavour hadron decays in p–Pb collisions at t √sNN=5.02 TeV was studied for 2<pT<16 GeV/c with the ALICE detector at the CERN LHC. The measurement was performed at forward (p-going direction) and backward (Pb-going direction) rapidity, in the ranges of rapidity in the centre-of-mass system (cms) 2.03<ycms<3.53 and −4.46<ycms<−2.96, respectively. The production cross sections and nuclear modification factors are presented as a function of transverse momentum (pT). At forward rapidity, the nuclear modification factor is compatible with unity while at backward rapidity, in the interval 2.5<pT<3.5 GeV/c, it is above unity by more than 2σ. The ratio of the forward-to-backward production cross sections is also measured in the overlapping interval 2.96<|ycms|<3.53 and is smaller than unity by 3.7σ in 2.5<pT<3.5 GeV/c. The data are described by model calculations including cold nuclear matter effects.
As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.