Interactions between cell surface protein disulphide isomerase and S-nitrosoglutathione during nitric oxide delivery

In this study, we investigated the role of protein disulphide isomerase (PDI) in rapid metabolism of S-nitrosoglutathione (GSNO) and S-nitrosoalbumin (albSNO) and in NO delivery from these compounds into cells. Incubation of GSNO or albSNO (1 μM) with the megakaryocyte cell line MEG-01 resulted in a cell-mediated removal of each compound which was inhibited by blocking cell surface thiols with 5,5′-dithiobis 2-nitrobenzoic acid (DTNB) (100 μM) or inhibiting PDI with bacitracin (5 mM). GSNO, but not albSNO, rapidly inhibited platelet aggregation and stimulated cyclic GMP (cGMP) accumulation (used as a measure of intracellular NO entry). cGMP accumulation in response to GSNO (1 μM) was inhibited by MEG-01 treatment with bacitracin or DTNB, suggesting a role for PDI and surface thiols in NO delivery. PDI activity was present in MEG-01 conditioned medium, and was inhibited by high concentrations of GSNO (500 μM). A number of cell surface thiol-containing proteins were labelled using the impermeable thiol specific probe 3-(N-maleimido-propionyl) biocytin (MPB). Pretreatment of cells with GSNO resulted in a loss of thiol reactivity on some but not all proteins, suggesting selective cell surface thiol modification. Immunoprecipitation experiments showed that GSNO caused a concentration-dependent loss of thiol reactivity of PDI. Our data indicate that PDI is involved in both rapid metabolism of GSNO and intracellular NO delivery and that during this process PDI is itself altered by thiol modification. In contrast, the relevance of PDI-mediated albSNO metabolism to NO signalling is uncertain

Trends in autoionization of Rydberg states converging to the 4s threshold in the Kr-Rb⁺-Sr²⁺ isoelectonic sequence: theory and experiment

We have measured the photoabsorption spectra of the Kr-like ions Rb+ and Sr2+ at photon energies corresponding to the excitation of 4s-np resonances using, the dual laser plasma photoabsorption technique. Dramatic changes in the line profiles, with increasing ionization and also proceeding along the Rydberg series of each ion, are observed and explained by the trends in 4s-transition amplitudes computed within a framework of configuration-interaction Pauli-Fock calculations. Total photoionization cross sections show very good agreement with relative absorption data extracted from the measured spectra

Multi-parametric MR Imaging Biomarkers Associated to Clinical Outcomes in Gliomas: A Systematic Review

[EN] Purpose: To systematically review evidence regarding the association of multi-parametric biomarkers with clinical outcomes and their capacity to explain relevant subcompartments of gliomas. Materials and Methods: Scopus database was searched for original journal papers from January 1st, 2007 to February 20th , 2017 according to PRISMA. Four hundred forty-nine abstracts of papers were reviewed and scored independently by two out of six authors. Based on those papers we analyzed associations between biomarkers, subcompartments within the tumor lesion, and clinical outcomes. From all the articles analyzed, the twenty-seven papers with the highest scores were highlighted to represent the evidence about MR imaging biomarkers associated with clinical outcomes. Similarly, eighteen studies defining subcompartments within the tumor region were also highlighted to represent the evidence of MR imaging biomarkers. Their reports were critically appraised according to the QUADAS-2 criteria. Results: It has been demonstrated that multi-parametric biomarkers are prepared for surrogating diagnosis, grading, segmentation, overall survival, progression-free survival, recurrence, molecular profiling and response to treatment in gliomas. Quantifications and radiomics features obtained from morphological exams (T1, T2, FLAIR, T1c), PWI (including DSC and DCE), diffusion (DWI, DTI) and chemical shift imaging (CSI) are the preferred MR biomarkers associated to clinical outcomes. Subcompartments relative to the peritumoral region, invasion, infiltration, proliferation, mass effect and pseudo flush, relapse compartments, gross tumor volumes, and high-risk regions have been defined to characterize the heterogeneity. For the majority of pairwise cooccurrences, we found no evidence to assert that observed co-occurrences were significantly different from their expected co-occurrences (Binomial test with False Discovery Rate correction, alpha=0.05). The co-occurrence among terms in the studied papers was found to be driven by their individual prevalence and trends in the literature. Conclusion: Combinations of MR imaging biomarkers from morphological, PWI, DWI and CSI exams have demonstrated their capability to predict clinical outcomes in different management moments of gliomas. Whereas morphologic-derived compartments have been mostly studied during the last ten years, new multi-parametric MRI approaches have also been proposed to discover specific subcompartments of the tumors. MR biomarkers from those subcompartments show the local behavior within the heterogeneous tumor and may quantify the prognosis and response to treatment of gliomas.This work was supported by the Spanish Ministry for Investigation, Development and Innovation project with identification number DPI2016-80054-R.Oltra-Sastre, M.; Fuster García, E.; Juan -Albarracín, J.; Sáez Silvestre, C.; Perez-Girbes, A.; Sanz-Requena, R.; Revert-Ventura, A.... (2019). 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Radiology 2016,281(3),907-918Roberto S-R.; Antonio R-V.; Luis M-B.; Angel A-B.; Gracián G-M.; Quantitative mr perfusion parameters related to survival time in high-grade gliomas. European Radiology 2013,23(12),3456-3465Jain R.; Poisson L.; Narang J.; Genomic mapping and survival prediction in glioblastoma: molecular subclassification strengthened by hemodynamic imaging biomarkers. Radiology 2013,267(1),212-220Fathi K.A.; Mohseni M.; Rezaei S.; Bakhshandehpour G.; Saligheh R.H.; Multi-parametric (ADC/PWI/T2-W) image fusion approach for accurate semi-automatic segmentation of tumorous regions in glioblastoma multiforme. MAGMA 2015,28(1),13-22Caulo M.; Panara V.; Tortora D.; Data-driven grading of brain gliomas: a multiparametric MR imaging study. Radiology 2014,272(2),494-503Alexiou G.A.; Zikou A.; Tsiouris S.; Comparison of diffusion tensor, dynamic susceptibility contrast MRI and (99m)Tc-Tetrofosmin brain SPECT for the detection of recurrent high-grade glioma. Magn Reson Imaging 2014,32(7),854-859Van Cauter S.; De Keyzer F.; Sima D.M.; Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. Neuro-oncol 2014,16(7),1010-1021Seeger A.; Braun C.; Skardelly M.; Comparison of three different MR perfusion techniques and MR spectroscopy for multiparametric assessment in distinguishing recurrent high-grade gliomas from stable disease. Acad Radiol 2013,20(12),1557-1565Chawalparit O.; Sangruchi T.; Witthiwej T.; Diagnostic performance of advanced mri in differentiating high-grade from low-grade gliomas in a setting of routine service. J Med Assoc Thai 2013,96(10),1365-1373Li Y.; Lupo J.M.; Parvataneni R.; Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging. Neuro-oncol 2013,15(5),607-617Shankar J.J.S.; Woulfe J.; Silva V.D.; Nguyen T.B.; Evaluation of perfusion CT in grading and prognostication of high-grade gliomas at diagnosis: a pilot study. AJR Am J Roentgenol 2013,200(5)Zinn P.O.; Mahajan B.; Sathyan P.; Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme. PLoS One 2011,6(10)Matsusue E.; Fink J.R.; Rockhill J.K.; Ogawa T.; Maravilla K.R.; Distinction between glioma progression and post-radiation change by combined physiologic MR imaging. Neuroradiology 2010,52(4),297-306Juan-Albarracín J.; Fuster-Garcia E.; Manjón J.V.; Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification. PLoS One 2015,10(5)Itakura H.; Achrol A.S.; Mitchell L.A.; Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities. Sci Transl Med 2015,7(303)Ion-Margineanu A.; Van Cauter S.; Sima D.M.; Tumour relapse prediction using multiparametric MR data recorded during follow-up of GBM patients. BioMed Res Int 2015,2015Durst C.R.; Raghavan P.; Shaffrey M.E.; Multimodal MR imaging model to predict tumor infiltration in patients with gliomas. Neuroradiology 2014,56(2),107-115Yoon J.H.; Kim J.H.; Kang W.J.; Grading of cerebral glioma with multi-parametric MR Imaging and 18F-FDG-PET: concordance and accuracy. European Radiol 2014,24(2),380-389Demerath T.; Simon-Gabriel C.P.; Kellner E.; Mesoscopic imaging of glioblastomas: are diffusion, perfusion and spectroscopic measures influenced by the radiogenetic phenotype? Neuroradiol J 2017,30(1),36-47Qin L.; Li X.; Stroiney A.; Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma. Neuroradiology 2017,59(2),135-145Boult J.K.R.; Borri M.; Jury A.; Investigating intracranial tumour growth patterns with multiparametric MRI incorporating Gd-DTPA and USPIO-enhanced imaging. NMR Biomed 2016,29(11),1608-1617Server A.; Kulle B.; Gadmar Ø.B.; Josefsen R.; Kumar T.; Nakstad P.H.; Measurements of diagnostic examination performance using quantitative apparent diffusion coefficient and proton MR spectroscopic imaging in the preoperative evaluation of tumor grade in cerebral gliomas. Eur J Radiol 2011,80(2),462-470Chang P.D.; Chow D.S.; Yang P.H.; Filippi C.G.; Lignelli A.; Predicting glioblastoma recurrence by early changes in the apparent diffusion coefficient value and signal intensity on FLAIR images. AJR Am J Roentgenol 2017,208(1),57-65Yi C.; Shangjie R.; Volume of high-risk intratumoralsubregions at multi-parametric MR imaging predicts overall survival and complements molecular analysis of glioblastoma. 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Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.</p

Search for single vector-like B quark production and decay via B → bH(b¯b) in pp collisions at √s = 13 TeV with the ATLAS detector

A search is presented for single production of a vector-like B quark decaying into a Standard Model b-quark and a Standard Model Higgs boson, which decays into a b¯b pair. The search is carried out in 139 fb−1 of √s = 13 TeV proton-proton collision data collected by the ATLAS detector at the LHC between 2015 and 2018. No significant deviation from the Standard Model background prediction is observed, and mass-dependent exclusion limits at the 95% confidence level are set on the resonance production cross-section in several theoretical scenarios determined by the couplings cW, cZ and cH between the B quark and the Standard Model W, Z and Higgs bosons, respectively. For a vector-like B occurring as an isospin singlet, the search excludes values of cW greater than 0.45 for a B resonance mass (mB) between 1.0 and 1.2 TeV. For 1.2 TeV < mB < 2.0 TeV, cW values larger than 0.50–0.65 are excluded. If the B occurs as part of a (B, Y) doublet, the smallest excluded cZ coupling values range between 0.3 and 0.5 across the investigated resonance mass range 1.0 TeV < mB < 2.0 TeV

Measurement of the top-quark mass using a leptonic invariant mass in pp collisions at s√ = 13 TeV with the ATLAS detector

A measurement of the top-quark mass (mt) in the tt¯ → lepton + jets channel is presented, with an experimental technique which exploits semileptonic decays of b-hadrons produced in the top-quark decay chain. The distribution of the invariant mass mℓμ of the lepton, ℓ (with ℓ = e, μ), from the W-boson decay and the muon, μ, originating from the b-hadron decay is reconstructed, and a binned-template profile likelihood fit is performed to extract mt. The measurement is based on data corresponding to an integrated luminosity of 36.1 fb−1 of s√ = 13 TeV pp collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. The measured value of the top-quark mass is mt = 174.41 ± 0.39 (stat.) ± 0.66 (syst.) ± 0.25 (recoil) GeV, where the third uncertainty arises from changing the PYTHIA8 parton shower gluon-recoil scheme, used in top-quark decays, to a recently developed setup

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Search for heavy resonances decaying into a Z or W boson and a Higgs boson in final states with leptons and b-jets in 139 fb−1 of pp collisions at s√ = 13 TeV with the ATLAS detector

This article presents a search for new resonances decaying into a Z or W boson and a 125 GeV Higgs boson h, and it targets the νν¯¯¯bb¯¯, ℓ+ℓ−bb¯¯, or ℓ±νbb¯¯ final states, where ℓ = e or μ, in proton-proton collisions at s√ = 13 TeV. The data used correspond to a total integrated luminosity of 139 fb−1 collected by the ATLAS detector during Run 2 of the LHC at CERN. The search is conducted by examining the reconstructed invariant or transverse mass distributions of Zh or Wh candidates for evidence of a localised excess in the mass range from 220 GeV to 5 TeV. No significant excess is observed and 95% confidence-level upper limits between 1.3 pb and 0.3 fb are placed on the production cross section times branching fraction of neutral and charged spin-1 resonances and CP-odd scalar bosons. These limits are converted into constraints on the parameter space of the Heavy Vector Triplet model and the two-Higgs-doublet model