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Long- and short-range correlations for pairs of charged particles are studied via two-particle angular correlations in pp collisions at s√=13 TeV and p−Pb collisions at sNN−−−√=5.02 TeV. The correlation functions are measured as a function of relative azimuthal angle Δφ and pseudorapidity separation Δη for pairs of primary charged particles within the pseudorapidity interval |η|<0.9 and the transverse-momentum interval 1<pT<4 GeV/c. Flow coefficients are extracted for the long-range correlations (1.6<|Δη|<1.8) in various high-multiplicity event classes using the low-multiplicity template fit method. The method is used to subtract the enhanced yield of away-side jet fragments in high-multiplicity events. These results show decreasing flow signals toward lower multiplicity events. Furthermore, the flow coefficients for events with hard probes, such as jets or leading particles, do not exhibit any significant changes compared to those obtained from high-multiplicity events without any specific event selection criteria. The results are compared with hydrodynamic-model calculations, and it is found that a better understanding of the initial conditions is necessary to describe the results, particularly for low-multiplicity events.
Long- and short-range correlations for pairs of charged particles are studied via two-particle angular correlations in pp collisions at √s = 13 TeV and p–Pb collisions at √sNN = 5.02 TeV. The correlation functions are measured as a function of relative azimuthal angle ∆φ and pseudorapidity separation ∆η for pairs of primary charged particles within the pseudorapidity interval |η| < 0.9 and the transverse-momentum interval 1 < pT < 4 GeV/c. Flow coefficients are extracted for the long-range correlations (1.6 < |∆η| < 1.8) in various high-multiplicity event classes using the low-multiplicity template fit method. The method is used to subtract the enhanced yield of away-side jet fragments in high-multiplicity events. These results show decreasing flow signals toward lower multiplicity events. Furthermore, the flow coefficients for events with hard probes, such as jets or leading particles, do not exhibit any significant changes compared to those obtained from high-multiplicity events without any specific event selection criteria. The results are compared with hydrodynamic-model calculations, and it is found that a better understanding of the initial conditions is necessary to describe the results, particularly for low-multiplicity events.
The measurement of the production of deuterons, tritons and 3He and their antiparticles in Pb-Pb collisions at √sNN = 5.02 TeV is presented in this article. The measurements are carried out at midrapidity (y|< 0.5) as a function of collision centrality using the ALICE detector. The pT-integrated yields, the coalescence parameters and the ratios to protons and antiprotons are reported and compared with nucleosynthesis models. The comparison of these results in different collision systems at different center-of-mass collision energies reveals a suppression of nucleus production in small systems. In the Statistical Hadronisation Model framework, this can be explained by a small correlation volume where the baryon number is conserved, as already shown in previous fluctuation analyses. However, a different size of the correlation volume is required to describe the proton yields in the same data sets. The coalescence model can describe this suppression by the fact that the wave functions of the nuclei are large and the fireball size starts to become comparable and even much smaller than the actual nucleus at low multiplicities.
The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.
The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.
Dielectrons are unique observables in ultra-relativistic heavy-ion collisions. Thanks to their penetrating nature, they carry information from all stages of the collision and can provide knowledge about pre-equilibirium dynamics, QGP temperature and transport coefficients, and chiral symmetry restoration. On the other hand, experimental challenges are enormous because production cross sections are small and the signal of interest is eclipsed by a huge combinatorial and physics background from light- and heavy-flavour hadron decays. In this talk the status of dielectron measurements with ALICE is shown and the perspectives with the recently installed and planned ALICE detector upgrades are discussed.
The G2A receptor (GPR132) contributes to oxaliplatin-induced mechanical pain hypersensitivity
(2017)
Chemotherapy-induced peripheral neuropathic pain (CIPN) is a common and severe debilitating side effect of many widely used cytostatics. However, there is no approved pharmacological treatment for CIPN available. Among other substances, oxaliplatin causes CIPN in up to 80% of treated patients. Here, we report the involvement of the G-protein coupled receptor G2A (GPR132) in oxaliplatin-induced neuropathic pain in mice. We found that mice deficient in the G2A-receptor show decreased mechanical hypersensitivity after oxaliplatin treatment. Lipid ligands of G2A were found in increased concentrations in the sciatic nerve and dorsal root ganglia of oxaliplatin treated mice. Calcium imaging and patch-clamp experiments show that G2A activation sensitizes the ligand-gated ion channel TRPV1 in sensory neurons via activation of PKC. Based on these findings, we conclude that targeting G2A may be a promising approach to reduce oxaliplatin-induced TRPV1-sensitization and the hyperexcitability of sensory neurons and thereby to reduce pain in patients treated with this chemotherapeutic agent.
Keystone mutualisms, such as corals, lichens or mycorrhizae, sustain fundamental ecosystem functions. Range dynamics of these symbioses are, however, inherently difficult to predict because host species may switch between different symbiont partners in different environments, thereby altering the range of the mutualism as a functional unit. Biogeographic models of mutualisms thus have to consider both the ecological amplitudes of various symbiont partners and the abiotic conditions that trigger symbiont replacement. To address this challenge, we here investigate 'symbiont turnover zones'--defined as demarcated regions where symbiont replacement is most likely to occur, as indicated by overlapping abundances of symbiont ecotypes. Mapping the distribution of algal symbionts from two species of lichen-forming fungi along four independent altitudinal gradients, we detected an abrupt and consistent β-diversity turnover suggesting parallel niche partitioning. Modelling contrasting environmental response functions obtained from latitudinal distributions of algal ecotypes consistently predicted a confined altitudinal turnover zone. In all gradients this symbiont turnover zone is characterized by approximately 12°C average annual temperature and approximately 5°C mean temperature of the coldest quarter, marking the transition from Mediterranean to cool temperate bioregions. Integrating the conditions of symbiont turnover into biogeographic models of mutualisms is an important step towards a comprehensive understanding of biodiversity dynamics under ongoing environmental change.
Bioactive small molecules are used in many research areas as important tools to uncover biological pathways, interpret phenotypic changes, deconvolute protein functions and explore new therapeutic strategies in disease relevant cellular model systems. To unlock the full potential of these small molecules and to ensure reliability of results obtained in cellular assays, it is crucial to understand the properties of these small molecules. These properties encompass their activity and potency on their designated target(s), their selectivity towards unintended off-targets and their phenotypic effects in a cellular system. Approved drugs often engage with multiple targets, which can be beneficial for some applications such as treatment of cancer where several pathways need to be inhibited for treatment efficacy. However, targeting multiple key proteins in diverse pathways also increases the possibility for unspecific or unwanted side effects. For many drugs the entire target space that they modulate is not known. This makes it difficult to use these drugs for target deconvolution or functional assays with the aim to understand the underlying biological processes. In contrast to drugs, for mechanistic studies, a good alternative are chemical tool compounds so called chemical probes that are usually exclusively selective as well as chemogenomic compounds, that inhibit several targets but have narrow selectivity profiles. Because they are mechanistic tools, chemical tool compounds must meet stringent quality criteria and they are therefore well characterized in terms of their potency, selectivity and cellular on-target activity. To ensure that an observed phenotypic effect caused by a compound can be attributed to the described target(s), it is essential to study also properties of chemical tools leading to unspecific cellular effects. There are a variety of unspecific effects that can be caused by physiochemical compound properties that can interfere with phenotypic assays as well as functional compound evaluations. One of these effects is low solubility causing toxicity or intrinsic fluorescence potentially interfering with assay readouts. But unanticipated cellular responses can also arise from unspecific binding, accumulation in cellular compartments or damage caused to organelles such as mitochondria or the cytoskeleton that can result in the induction of diverse forms of cell death.
In this study, we investigated the influence of a variety of small molecules on distinct cell states, by establishing and validating high-content imaging assays, which we called Multiplex assay. This assay portfolio enabled us to detect different cellular responses using diverse fluorescent reporters, such as the influence of a compound on cell viability, induction of cell death programs and modulation of the cell cycle. Additionally, general compound properties such as precipitation and intrinsic fluorescence were simultaneously detected. The assay is adaptable to assess other cellular properties of interest, such as mitochondrial health, changes in cytoskeletal morphology or phospholipidosis. A significant advantage of the assay is that we are using live cells, so we can capture dynamic cellular changes and fluctuations that can be crucial for the understanding of cellular responses.