177 research outputs found

    An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis

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    Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis (M. tuberculosis), is a major cause of morbidity and mortality worldwide and efforts to control TB are hampered by difficulties with diagnosis, prevention and treatment 1,2. Most people infected with M. tuberculosis remain asymptomatic, termed latent TB, with a 10% lifetime risk of developing active TB disease, but current tests cannot identify which individuals will develop disease 3. The immune response to M. tuberculosis is complex and incompletely characterized, hindering development of new diagnostics, therapies and vaccines 4,5. We identified a whole blood 393 transcript signature for active TB in intermediate and high burden settings, correlating with radiological extent of disease and reverting to that of healthy controls following treatment. A subset of latent TB patients had signatures similar to those in active TB patients. We also identified a specific 86-transcript signature that discriminated active TB from other inflammatory and infectious diseases. Modular and pathway analysis revealed that the TB signature was dominated by a neutrophil-driven interferon (IFN)-inducible gene profile, consisting of both IFN-γ and Type I IFNαβ signalling. Comparison with transcriptional signatures in purified cells and flow cytometric analysis, suggest that this TB signature reflects both changes in cellular composition and altered gene expression. Although an IFN signature was also observed in whole blood of patients with Systemic Lupus Erythematosus (SLE), their complete modular signature differed from TB with increased abundance of plasma cell transcripts. Our studies demonstrate a hitherto under-appreciated role of Type I IFNαβ signalling in TB pathogenesis, which has implications for vaccine and therapeutic development. Our study also provides a broad range of transcriptional biomarkers with potential as diagnostic and prognostic tools to combat the TB epidemic

    The tuberculosis necrotizing toxin kills macrophages by hydrolyzing NAD.

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    Mycobacterium tuberculosis (Mtb) induces necrosis of infected cells to evade immune responses. Recently, we found that Mtb uses the protein CpnT to kill human macrophages by secreting its C-terminal domain, named tuberculosis necrotizing toxin (TNT), which induces necrosis by an unknown mechanism. Here we show that TNT gains access to the cytosol of Mtb-infected macrophages, where it hydrolyzes the essential coenzyme NAD(+). Expression or injection of a noncatalytic TNT mutant showed no cytotoxicity in macrophages or in zebrafish zygotes, respectively, thus demonstrating that the NAD(+) glycohydrolase activity is required for TNT-induced cell death. To prevent self-poisoning, Mtb produces an immunity factor for TNT (IFT) that binds TNT and inhibits its activity. The crystal structure of the TNT-IFT complex revealed a new NAD(+) glycohydrolase fold of TNT, the founding member of a toxin family widespread in pathogenic microorganisms

    Multipion Bose-Einstein correlations in pp,p -Pb, and Pb-Pb collisions at energies available at the CERN Large Hadron Collider

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    First measurement of the |t|-dependence of coherent J/ψ photonuclear production

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    The first measurement of the cross section for coherent J/ψ photoproduction as a function of |t|, the square of the momentum transferred between the incoming and outgoing target nucleus, is presented. The data were measured with the ALICE detector in ultra-peripheral Pb–Pb collisions at a centre-of-mass energy per nucleon pair sNN=5.02TeV with the J/ψ produced in the central rapidity region |y|<0.8, which corresponds to the small Bjorken-x range (0.3−1.4)×10−3. The measured |t|-dependence is not described by computations based only on the Pb nuclear form factor, while the photonuclear cross section is better reproduced by models including shadowing according to the leading-twist approximation, or gluon-saturation effects from the impact-parameter dependent Balitsky–Kovchegov equation. These new results are therefore a valid tool to constrain the relevant model parameters and to investigate the transverse gluonic structure at very low Bjorken-x.publishedVersio

    Programmed cell death and its role in inflammation

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    Cell death plays an important role in the regulation of inflammation and may be the result of inflammation. The maintenance of tissue homeostasis necessitates both the recognition and removal of invading microbial pathogens as well as the clearance of dying cells. In the past few decades, emerging knowledge on cell death and inflammation has enriched our molecular understanding of the signaling pathways that mediate various programs of cell death and multiple types of inflammatory responses. This review provides an overview of the major types of cell death related to inflammation. Modification of cell death pathways is likely to be a logical therapeutic target for inflammatory diseases

    Lipid metabolism and Type VII secretion systems dominate the genome scale virulence profile of Mycobacterium tuberculosis in human dendritic cells

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    Resolving the strange behavior of extraterrestrial potassium in the upper atmosphere

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    It has been known since the 1960s that the layers of Na and K atoms, which occur between 80 and 105 km in the Earth's atmosphere as a result of meteoric ablation, exhibit completely different seasonal behavior. In the extratropics Na varies annually, with a pronounced wintertime maximum and summertime minimum. However, K varies semiannually with a small summertime maximum and minima at the equinoxes. This contrasting behavior has never been satisfactorily explained. Here we use a combination of electronic structure and chemical kinetic rate theory to determine two key differences in the chemistries of K and Na. First, the neutralization of K+ ions is only favored at low temperatures during summer. Second, cycling between K and its major neutral reservoir KHCO3 is essentially temperature independent. A whole atmosphere model incorporating this new chemistry, together with a meteor input function, now correctly predicts the seasonal behavior of the K layer

    Particle identification in ALICE : a Bayesian approach

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