255 research outputs found

    Differential Sulfation Remodelling of Heparan Sulfate by Extracellular 6-O-Sulfatases Regulates Fibroblast Growth Factor-Induced Boundary Formation by Glial Cells: Implications for Glial Cell Transplantation

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    Previously, it has been shown that rat Schwann cells (SCs), but not olfactory ensheathing cells (OECs), form a boundary with astrocytes, due to a SC-specific secreted factor. Here, we identify highly sulfated heparan sulfates (HSs) and fibroblast growth factors (FGFs) 1 and 9 as possible determinants of boundary formation induced by rat SCs. Disaccharide analysis of HS in SC-conditioned and rat OEC-conditioned media showed that SCs secrete more highly sulfated HS than OECs. The dependence of the boundary-forming activity on high levels of sulfation was confirmed using a panel of semisynthetic modified heparins with variable levels of sulfation. Furthermore, extracellular HS 6-O-endosulfatase enzymes, Sulf 1 and Sulf 2, were expressed at a significantly lower level by SCs compared with OECs, and siRNA reduction of Sulfs in OECs was, in itself, sufficient to induce boundary formation. This demonstrates a key role for remodelling (reduction) of HS 6-O-sulfation by OECs, compared with SCs, to suppress boundary formation. Furthermore, specific anti-FGF1 and anti-FGF9 antibodies disrupted SC–astrocyte boundary formation, supporting a role for an HS sulfation-dependent FGF signaling mechanism via FGF receptors on astrocytes. We propose a model in which FGF1 and FGF9 signaling is differentially modulated by patterns of glial cell HS sulfation, dependent on Sulf 1 and Sulf 2 expression, to control FGF receptor 3-IIIb-mediated astrocytic responses. Moreover, these data suggest manipulation of HS sulfation after CNS injury as a potential novel approach for therapeutic intervention in CNS repair

    Fatigue Crack Growth Mechanisms At the Microstructure Scale in Al-Si-Mg Cast Alloys: Mechanisms in Regions II and III

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    The fatigue crack growth behavior in Regions 11 and III of crack growth was investigated for hypoeutectic and eutectic Al-Si-Mg cast alloys. To isolate and establish the mechanistic contributions of characteristic microstructural features (dendritic α-Al matrix, eutectic phases, Mg-Si strengthening precipitates), alloys with various Si content/morphology, grain size level, and matrix strength were studied; the effect of secondary dendrite arm spacing (SDAS) was also assessed. In Regions 11 and III of crack growth, the observed changes in the fracture surface appearance were associated with changes in crack growth mechanisms at the microstructural scale (from a linear advance predominantly through primary α-Al to a tortuous advance exclusively through AI-Si eutectic Regions). The extent of the plastic zone ahead of the crack tip was successfully used to explain the changes in growth mechanisms. The fatigue crack growth tests were conducted on compact tension specimens under constant stress ratio, R = 0.1, in ambient conditions

    Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

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    The B0B^0-Bˉ0\bar B^0 oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives Δmd=0.493±0.012(stat)±0.009(syst)\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)} ps1^{-1}.Comment: 7 pages, 1 figure, submitted to Physical Review Letter

    Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus.

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    BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.UK funding includes Cancer Research UK and NIH.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13058-016-0718-

    Measurement of the CP-Violating Asymmetry Amplitude sin2β\beta

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    We present results on time-dependent CP-violating asymmetries in neutral B decays to several CP eigenstates. The measurements use a data sample of about 88 million Y(4S) --> B Bbar decays collected between 1999 and 2002 with the BABAR detector at the PEP-II asymmetric-energy B Factory at SLAC. We study events in which one neutral B meson is fully reconstructed in a final state containing a charmonium meson and the other B meson is determined to be either a B0 or B0bar from its decay products. The amplitude of the CP-violating asymmetry, which in the Standard Model is proportional to sin2beta, is derived from the decay-time distributions in such events. We measure sin2beta = 0.741 +/- 0.067 (stat) +/- 0.033 (syst) and |lambda| = 0.948 +/- 0.051 (stat) +/- 0.017 (syst). The magnitude of lambda is consistent with unity, in agreement with the Standard Model expectation of no direct CP violation in these modes

    Lung adenocarcinoma promotion by air pollutants

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    A complete understanding of how exposure to environmental substances promotes cancer formation is lacking. More than 70 years ago, tumorigenesis was proposed to occur in a two-step process: an initiating step that induces mutations in healthy cells, followed by a promoter step that triggers cancer development1. Here we propose that environmental particulate matter measuring ≤2.5 μm (PM2.5), known to be associated with lung cancer risk, promotes lung cancer by acting on cells that harbour pre-existing oncogenic mutations in healthy lung tissue. Focusing on EGFR-driven lung cancer, which is more common in never-smokers or light smokers, we found a significant association between PM2.5 levels and the incidence of lung cancer for 32,957 EGFR-driven lung cancer cases in four within-country cohorts. Functional mouse models revealed that air pollutants cause an influx of macrophages into the lung and release of interleukin-1β. This process results in a progenitor-like cell state within EGFR mutant lung alveolar type II epithelial cells that fuels tumorigenesis. Ultradeep mutational profiling of histologically normal lung tissue from 295 individuals across 3 clinical cohorts revealed oncogenic EGFR and KRAS driver mutations in 18% and 53% of healthy tissue samples, respectively. These findings collectively support a tumour-promoting role for PM2.5 air pollutants and provide impetus for public health policy initiatives to address air pollution to reduce disease burden

    The Physics of the B Factories

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

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    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
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