66 research outputs found

    Cytokine gene polymorphisms and serum cytokine levels in patients with idiopathic pulmonary fibrosis

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    BACKGROUND: Studies have demonstrated associations between cytokine gene polymorphisms and the risk of idiopathic pulmonary fibrosis (IPF). We therefore examined polymorphisms in the genes encoding interleukin (IL)-6, IL-10, interferon gamma (IFN-γ), tumor necrosis factor alpha (TNF-α), and transforming growth factor-beta 1 (TGF-β(1)), and compared the serum levels of these cytokines in IPF patients and healthy controls. Furthermore, we examined the association of the studied genotypes and serum cytokine levels with physiological parameters and the extent of parenchymal involvement determined by high-resolution computed tomography (HRCT). METHODS: Sixty patients with IPF and 150 healthy controls were included. Cytokine genotyping was performed using the polymerase chain reaction sequence specific primer (PCR-SSP) method. In a subset of patients and controls, serum cytokine levels were determined by enzyme-linked immunosorbent assay. RESULTS: There was no difference between IPF patients and controls in the genotype and allele distributions of polymorphisms in TNF-α, IFN-γ, IL-6, IL-10, and TGF-β(1) (all p > 0.05). The TNF-α (−308) GG, IL-6 (−174) GG and CG, and IL-10 (−1082, -819, -592) ACC ATA genotypes were significantly associated with HRCT scores (all p < 0.05). IL-10 (−1082, -819, -592) ACC haplotype was associated with the diffusion capacity of the lung for carbon monoxide, and ATA haplotype was associated with the partial pressure of oxygen (PaO(2)) (all p < 0.05). The TGF-β(1) (codons 10 and 25) TC GG, TC GC, CC GG and CC GC genotypes were significantly associated with the PaO(2) and HRCT scores (p < 0.05). The TGF-β(1) (codons 10 and 25) CC GG genotype (5 patients) was significantly associated with higher PaO(2) value and less parenchymal involvement (i.e., a lower total extent score) compared to the other TGF-β(1) genotypes (81.5 ± 11.8 mm Hg vs. 67.4 ± 11.1 mm Hg, p = 0.009 and 5.60 ± 1.3 vs. 8.51 ± 2.9, p = 0.037, respectively). Significant differences were noted between patients (n = 38) and controls (n = 36) in the serum levels of IL-6 and IL-10 (both, p < 0.0001), but not in the levels of TNF-α and TGF-β(1) (both, p > 0.05). CONCLUSION: The studied genotypes and alleles do not predispose to the development of IPF but appear to play an important role in disease severity. Our results suggest that the TGF-β(1) (codons 10 and 25) CC GG genotype could be a useful genetic marker for identifying a subset of IPF patients with a favorable prognosis; however, validation in a larger sample is required

    Overview of recent TJ-II stellarator results

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    The main results obtained in the TJ-II stellarator in the last two years are reported. The most important topics investigated have been modelling and validation of impurity transport, validation of gyrokinetic simulations, turbulence characterisation, effect of magnetic configuration on transport, fuelling with pellet injection, fast particles and liquid metal plasma facing components. As regards impurity transport research, a number of working lines exploring several recently discovered effects have been developed: the effect of tangential drifts on stellarator neoclassical transport, the impurity flux driven by electric fields tangent to magnetic surfaces and attempts of experimental validation with Doppler reflectometry of the variation of the radial electric field on the flux surface. Concerning gyrokinetic simulations, two validation activities have been performed, the comparison with measurements of zonal flow relaxation in pellet-induced fast transients and the comparison with experimental poloidal variation of fluctuations amplitude. The impact of radial electric fields on turbulence spreading in the edge and scrape-off layer has been also experimentally characterized using a 2D Langmuir probe array. Another remarkable piece of work has been the investigation of the radial propagation of small temperature perturbations using transfer entropy. Research on the physics and modelling of plasma core fuelling with pellet and tracer-encapsulated solid-pellet injection has produced also relevant results. Neutral beam injection driven Alfvénic activity and its possible control by electron cyclotron current drive has been examined as well in TJ-II. Finally, recent results on alternative plasma facing components based on liquid metals are also presentedThis work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 under Grant Agreement No. 633053. It has been partially funded by the Ministerio de Ciencia, Inovación y Universidades of Spain under projects ENE2013-48109-P, ENE2015-70142-P and FIS2017-88892-P. It has also received funds from the Spanish Government via mobility grant PRX17/00425. The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by the Barcelona S.C. It has been supported as well by The Science and Technology Center in Ukraine (STCU), Project P-507F

    Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

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    Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

    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 hospitalization2–4 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

    SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

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    Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

    The Importance of Getting Names Right: The Myth of Markets for Water

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