206 research outputs found

    Absence of system xc⁻ on immune cells invading the central nervous system alleviates experimental autoimmune encephalitis

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    Background: Multiple sclerosis (MS) is an autoimmune demyelinating disease that affects the central nervous system (CNS), leading to neurodegeneration and chronic disability. Accumulating evidence points to a key role for neuroinflammation, oxidative stress, and excitotoxicity in this degenerative process. System x(c)- or the cystine/glutamate antiporter could tie these pathological mechanisms together: its activity is enhanced by reactive oxygen species and inflammatory stimuli, and its enhancement might lead to the release of toxic amounts of glutamate, thereby triggering excitotoxicity and neurodegeneration. Methods: Semi-quantitative Western blotting served to study protein expression of xCT, the specific subunit of system x(c)-, as well as of regulators of xCT transcription, in the normal appearing white matter (NAWM) of MS patients and in the CNS and spleen of mice exposed to experimental autoimmune encephalomyelitis (EAE), an accepted mouse model of MS. We next compared the clinical course of the EAE disease, the extent of demyelination, the infiltration of immune cells and microglial activation in xCT-knockout (xCT(-/-)) mice and irradiated mice reconstituted in xCT(-/-) bone marrow (BM), to their proper wild type (xCT(+/+)) controls. Results: xCT protein expression levels were upregulated in the NAWM of MS patients and in the brain, spinal cord, and spleen of EAE mice. The pathways involved in this upregulation in NAWM of MS patients remain unresolved. Compared to xCT(+/+) mice, xCT(-/-) mice were equally susceptible to EAE, whereas mice transplanted with xCT(-/-) BM, and as such only exhibiting loss of xCT in their immune cells, were less susceptible to EAE. In none of the above-described conditions, demyelination, microglial activation, or infiltration of immune cells were affected. Conclusions: Our findings demonstrate enhancement of xCT protein expression in MS pathology and suggest that system x(c)- on immune cells invading the CNS participates to EAE. Since a total loss of system x(c)- had no net beneficial effects, these results have important implications for targeting system x(c)- for treatment of MS

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    An evaluation tool kit of air quality micro-sensing units.

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    Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors' capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors' performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25 MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors' performance. The SET was implemented in R and the code is available on the first author's website.CITI-SENSE, initiated in October 2012, is a four year Collaborative Project partly funded by the EU FP7-ENV-2012 under grant agreement 308524

    Search for strongly interacting massive particles generating trackless jets in proton-proton collisions at s = 13 TeV

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    A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton-proton collision data corresponding to an integrated luminosity of 16.1 fb - 1 , collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100 GeV are excluded and further sensitivity is explored towards higher masses

    Evidence for Top Quark Production in Nucleus-Nucleus Collisions

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    Search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks in proton-proton collisions at root s=13TeV

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    A search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks is performed in proton-proton collisions at a center-of-mass energy of 13 TeV collected with the CMS detector at the LHC. The analyzed data sample corresponds to an integrated luminosity of 35.9 fb(-1). The signal is characterized by a large missing transverse momentum recoiling against a bottom quark-antiquark system that has a large Lorentz boost. The number of events observed in the data is consistent with the standard model background prediction. Results are interpreted in terms of limits both on parameters of the type-2 two-Higgs doublet model extended by an additional light pseudoscalar boson a (2HDM+a) and on parameters of a baryonic Z simplified model. The 2HDM+a model is tested experimentally for the first time. For the baryonic Z model, the presented results constitute the most stringent constraints to date.Peer reviewe

    Observation of a New Excited Beauty Strange Baryon Decaying to Ξb- π+π-

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    The Ξb-π+π- invariant mass spectrum is investigated with an event sample of proton-proton collisions at s=13 TeV, collected by the CMS experiment at the LHC in 2016-2018 and corresponding to an integrated luminosity of 140 fb-1. The ground state Ξb- is reconstructed via its decays to J/ψΞ- and J/ψΛK-. A narrow resonance, labeled Ξb(6100)-, is observed at a Ξb-π+π- invariant mass of 6100.3±0.2(stat)±0.1(syst)±0.6(Ξb-) MeV, where the last uncertainty reflects the precision of the Ξb- baryon mass. The upper limit on the Ξb(6100)- natural width is determined to be 1.9 MeV at 95% confidence level. The low Ξb(6100)- signal yield observed in data does not allow a measurement of the quantum numbers of the new state. However, following analogies with the established excited Ξc baryon states, the new Ξb(6100)- resonance and its decay sequence are consistent with the orbitally excited Ξb- baryon, with spin and parity quantum numbers JP=3/2-

    A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

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    We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯
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