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Heavy flavour decay muon production at forward rapidity in proton–proton collisions at √s=7 TeV
(2012)
The production of muons from heavy flavour decays is measured at forward rapidity in proton–proton collisions at √s=7 TeV collected with the ALICE experiment at the LHC. The analysis is carried out on a data sample corresponding to an integrated luminosity Lint=16.5 nb−1. The transverse momentum and rapidity differential production cross sections of muons from heavy flavour decays are measured in the rapidity range 2.5<y<4, over the transverse momentum range 2<pt<12 GeV/c. The results are compared to predictions based on perturbative QCD calculations.
Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the Xchromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p = 5.87×10-9; odds ratio = 1.12) and markers within ERBB2 (rs2517959, p = 4.53×10-9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
It is proposed to install an experimental setup in the fixed-target hall of the Nuclotron with the final goal to perform a research program focused on the production of strange matter in heavyion collisions at beam energies between 2 and 6 A GeV. The basic setup will comprise a large acceptance dipole magnet with inner tracking detector modules based on double-sided Silicon micro-strip sensors and GEMs. The outer tracking will be based on the drift chambers and straw tube detector. Particle identification will be based on the time-of-flight measurements. This setup will be sufficient perform a comprehensive study of strangeness production in heavy-ion collisions, including multi-strange hyperons, multi-strange hypernuclei, and exotic multi-strange heavy objects. These pioneering measurements would provide the first data on the production of these particles in heavy-ion collisions at Nuclotron beam energies, and would open an avenue to explore the third (strangeness) axis of the nuclear chart. The extension of the experimental program is related with the study of in-medium effects for vector mesons decaying in hadronic modes. The studies of the NN and NA reactions for the reference is assumed.
HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders
(2021)
Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10−3; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
Phylogenetic relationships of the primarily wingless insects are still considered unresolved. Even the most comprehensive phylogenomic studies that addressed this question did not yield congruent results. In order to get a grip on these problems, we here analyzed the sources of incongruence in these phylogenomic studies using an extended transcriptome dataset.Our analyses showed that unevenly distributed missing data can be severely misleading by inflating node support despite the absence of phylogenetic signal. In consequence, only decisive datasets should be used which exclusively comprise data blocks containing all taxa whose relationships are addressed. Additionally, we employed Four-cluster Likelihood-Mapping (FcLM) to measure the degree of congruence among genes of a dataset, as a measure of support alternative to bootstrap. FcLM showed incongruent signal among genes, which in our case is correlated with neither functional class assignment of these genes, nor with model misspecification due to unpartitioned analyses. The herein analyzed dataset is the currently largest dataset covering primarily wingless insects, but failed to elucidate their interordinal phylogenetic relationships. While this is unsatisfying from a phylogenetic perspective, we try to show that the analyses of structure and signal within phylogenomic data can protect us from biased phylogenetic inferences due to analytical artefacts.
Background: Previously, we showed that glioma pathogenesis related protein (GliPR) is induced in CEM T cells upon HIV-1 infection in vitro. To examine whether GliPR plays a role as HIV dependency factor (HDF), we tested the effect of GliPR suppression by siRNA on HIV-1 replication. Results: Induction of GliPR expression by HIV-1 was confirmed in P4-CCR5 cells. When GliPR was suppressed by siRNA, HIV-1 replication was significantly reduced as measured by HIV-1 transcript levels, HIV-1 p24 protein levels, and HIV-1 LTR-driven reporter gene expression, suggesting that GliPR is a cellular co-factor of HIV-1. Microarray analysis of uninfected HeLa cells following knockdown of GliPR revealed, among a multitude of gene expression alterations, a down-regulation of syndecan-1, syndecan-2, protein kinase C alpha (PRKCA), the catalytic subunit beta of cAMP-dependent protein kinase (PRKACB), nuclear receptor co-activator 3 (NCOA3), and cell surface protein CD59 (protectin), all genes having relevance for HIV-1 pathology. Conclusions: The up-regulation of GliPR by HIV-1 and the early significant inhibition of HIV-1 replication mediated by knockdown of GliPR reveal GliPR as an important HIV-1 dependency factor (HDF), which may be exploited for HIV-1 inhibition.
Background: The epidermal growth factor receptor (EGFR) signaling pathway is genetically activated in approximately 50% of glioblastomas (GBs). Its inhibition has been explored clinically but produced disappointing results, potentially due to metabolic effects that protect GB cells against nutrient deprivation and hypoxia. Here, we hypothesized that EGFR activation could disable metabolic adaptation and define a GB cell population sensitive to starvation.
Methods: Using genetically engineered GB cells to model different types of EGFR activation, we analyzed changes in metabolism and cell survival under conditions of the tumor microenvironment.
Results: We found that expression of mutant EGFRvIII as well as EGF stimulation of EGFR-overexpressing cells impaired physiological adaptation to starvation and rendered cells sensitive to hypoxia-induced cell death. This was preceded by adenosine triphosphate (ATP) depletion and an increase in glycolysis. Furthermore, EGFRvIII mutant cells had higher levels of mitochondrial superoxides potentially due to decreased metabolic flux into the serine synthesis pathway which was associated with a decrease in the NADPH/NADP+ ratio.
Conclusions: The finding that EGFR activation renders GB cells susceptible to starvation could help to identify a subgroup of patients more likely to benefit from starvation-inducing therapies.
Long-range angular correlations on the near and away side in p–Pb collisions at √sNN=5.02 TeV
(2013)
Angular correlations between charged trigger and associated particles are measured by the ALICE detector in p–Pb collisions at a nucleon–nucleon centre-of-mass energy of 5.02 TeV for transverse momentum ranges within 0.5<pT,assoc<pT,trig<4 GeV/c. The correlations are measured over two units of pseudorapidity and full azimuthal angle in different intervals of event multiplicity, and expressed as associated yield per trigger particle. Two long-range ridge-like structures, one on the near side and one on the away side, are observed when the per-trigger yield obtained in low-multiplicity events is subtracted from the one in high-multiplicity events. The excess on the near-side is qualitatively similar to that recently reported by the CMS Collaboration, while the excess on the away-side is reported for the first time. The two-ridge structure projected onto azimuthal angle is quantified with the second and third Fourier coefficients as well as by near-side and away-side yields and widths. The yields on the near side and on the away side are equal within the uncertainties for all studied event multiplicity and pT bins, and the widths show no significant evolution with event multiplicity or pT. These findings suggest that the near-side ridge is accompanied by an essentially identical away-side ridge.
Background: Alternative splicing is a key regulatory mechanism in eukaryotic cells and increases the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied across human tissues and in genetically diverse populations. This has identified disease-relevant splicing events, as well as associations between splicing and genomic features, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue or cell type and its determinants remains poorly understood.
Results: We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results show that variation in single-cell splicing can be accurately predicted based on local sequence composition and genomic features. We observe moderate but consistent contributions from local DNA methylation profiles to splicing variation across cells. A combined model that is built based on genomic features as well as DNA methylation information accurately predicts different splicing modes of individual cassette exons. These categories include the conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation.
Conclusions: Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated link between DNA methylation variation and splicing.
Background: Alternative splicing is a key mechanism in eukaryotic cells to increase the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied both across human tissues and in genetically diverse individuals. This has identified disease-relevant splicing events, as well as associations between splicing and genomic variations, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue and its determinants remain poorly understood.
Results: We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results shows that splicing rates in single cells can be accurately predicted based on sequence composition and other genomic features. We also identified a moderate but significant contribution from DNA methylation to splicing variation across cells. By combining sequence information and DNA methylation, we derived an accurate model (AUC=0.85) for predicting different splicing modes of individual cassette exons. These explain conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation.
Conclusions: Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated component of DNA methylation variation on splicing.