194 research outputs found

    The disruption of proteostasis in neurodegenerative diseases

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    Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio

    Effects of rapid urbanisation on the urban thermal environment between 1990 and 2011 in Dhaka Megacity, Bangladesh

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    This study investigates the influence of land-use/land-cover (LULC) change on land surface temperature (LST) in Dhaka Megacity, Bangladesh during a period of rapid urbanisation. LST was derived from Landsat 5 TM scenes captured in 1990, 2000 and 2011 and compared to contemporaneous LULC maps. We compared index-based and linear spectral mixture analysis (LSMA) techniques for modelling LST. LSMA derived biophysical parameters corresponded more strongly to LST than those produced using index-based parameters. Results indicated that vegetation and water surfaces had relatively stable LST but it increased by around 2 °C when these surfaces were converted to built-up areas with extensive impervious surfaces. Knowledge of the expected change in LST when one land-cover is converted to another can inform land planners of the potential impact of future changes and urges the development of better management strategies

    Cancer Biomarker Discovery: The Entropic Hallmark

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    Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Measurement of Higgs boson production in the diphoton decay channel in pp collisions at center-of-mass energies of 7 and 8 TeV with the ATLAS detector

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    A measurement of the production processes of the recently discovered Higgs boson is performed in the two-photon final state using 4.5  fb[superscript −1] of proton-proton collisions data at √s=7  TeV and 20.3  fb[superscript −1] at √s=8  TeV collected by the ATLAS detector at the Large Hadron Collider. The number of observed Higgs boson decays to diphotons divided by the corresponding Standard Model prediction, called the signal strength, is found to be ÎŒ=1.17±0.27 at the value of the Higgs boson mass measured by ATLAS, m[subscript H]=125.4  GeV. The analysis is optimized to measure the signal strengths for individual Higgs boson production processes at this value of m[subscript H]. They are found to be ÎŒ[subscript ggF]=1.32±0.38, ÎŒ[subscript VBF]=0.8±0.7, ÎŒ[subscript WH]=1.0±1.6, ÎŒ[subscript ZH]=0.1[superscript +3.7 subscript −0.1], and ÎŒ[subscript t [bar over t] H] =1.6[superscript +2.7 subscript −1.8], for Higgs boson production through gluon fusion, vector-boson fusion, and in association with a W or Z boson or a top-quark pair, respectively. Compared with the previously published ATLAS analysis, the results reported here also benefit from a new energy calibration procedure for photons and the subsequent reduction of the systematic uncertainty on the diphoton mass resolution. No significant deviations from the predictions of the Standard Model are found.European Organization for Nuclear ResearchUnited States. Dept. of EnergyNational Science Foundation (U.S.)Brookhaven National Laborator

    Measurement of the W±Z boson pair-production cross section in pp collisions at √s=13TeV with the ATLAS detector

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    Measurement of W+W− production in association with one jet in proton–proton collisions at sqrt(s) = 8TeV with the ATLAS detector

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    The production of W boson pairs in association with one jet in pp collisions at View the MathML sources=8 TeV is studied using data corresponding to an integrated luminosity of 20.3 fb−1 collected by the ATLAS detector during 2012 at the CERN Large Hadron Collider. The cross section is measured in a fiducial phase-space region defined by the presence of exactly one electron and one muon, missing transverse momentum and exactly one jet with a transverse momentum above 25 GeV and a pseudorapidity of |η|<4.5|η|<4.5. The leptons are required to have opposite electric charge and to pass transverse momentum and pseudorapidity requirements. The fiducial cross section is found to be View the MathML sourceσWWfid,1-jet=136±6(stat)±14(syst)±3(lumi) fb. In combination with a previous measurement restricted to leptonic final states with no associated jets, the fiducial cross section of WW production with zero or one jet is measured to be View the MathML sourceσWWfid,≀1-jet=511±9(stat)±26(syst)±10(lumi) fb. The ratio of fiducial cross sections in final states with one and zero jets is determined to be 0.36±0.050.36±0.05. Finally, a total cross section extrapolated from the fiducial measurement of WW production with zero or one associated jet is reported. The measurements are compared to theoretical predictions and found in good agreement

    Measurement of the inelastic proton-proton cross section at √s=13 TeV with the ATLAS detector at the LHC

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    This Letter presents a measurement of the inelastic proton-proton cross section using 60  Όb −1 of pp collisions at a center-of-mass energy √s of 13 TeV with the ATLAS detector at the LHC. Inelastic interactions are selected using rings of plastic scintillators in the forward region (2.0710 −6 , where M X is the larger invariant mass of the two hadronic systems separated by the largest rapidity gap in the event. In this Ο range the scintillators are highly efficient. For diffractive events this corresponds to cases where at least one proton dissociates to a system with M X >13  GeV . The measured cross section is compared with a range of theoretical predictions. When extrapolated to the full phase space, a cross section of 78.1±2.9  mb is measured, consistent with the inelastic cross section increasing with center-of-mass energy

    Measurement of the transverse polarization of Λ and Λ¯ hyperons produced in proton-proton collisions at √s=7  TeV using the ATLAS detector

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    The transverse polarization of Λ and Λ¯ hyperons produced in proton-proton collisions at a center-of-mass energy of 7 TeV is measured. The analysis uses 760  Όb−1 of minimum bias data collected by the ATLAS detector at the LHC in the year 2010. The measured transverse polarization averaged over Feynman xF from 5×10−5 to 0.01 and transverse momentum pT from 0.8 to 15 GeV is −0.010±0.005(stat)±0.004(syst) for Λ and 0.002±0.006(stat)±0.004(syst) for Λ¯. It is also measured as a function of xF and pT, but no significant dependence on these variables is observed. Prior to this measurement, the polarization was measured at fixed-target experiments with center-of-mass energies up to about 40 GeV. The ATLAS results are compatible with the extrapolation of a fit from previous measurements to the xF range covered by this measurement

    Charged-particle distributions at low transverse momentum in √s=13 13 TeV pp interactions measured with the ATLAS detector at the LHC

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    Measurements of distributions of charged particles produced in proton–proton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 ÎŒb −1 ÎŒb−1 . The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators
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