8 research outputs found
Quantitative Analysis of Angle-Resolved XPS Spectra Recorded in Parallel Data Acquisition Mode
The Formation of Passive Films on Magnesium in Alkaline Solutions and Adsorption of Anions of Organic Acids on Them
A multi-criteria decision-making analysis for the selection of fibres aimed at reinforcing asphalt concrete mixtures
In the last few years, fibers have been proposed as one of the most important additives for the development of reinforced asphalt mixtures. The optimal fiber selection is a very complex task, as an extensive range of criteria and alternatives have to be taken into account. Decision support systems have been applied in the construction sector, but not for selecting fibers for bituminous mixtures. To fill this gap, two Multi-Criteria Decision-Making Analysis methodologies for the selection of the best fiber to be used in Asphalt Concretes are presented in this paper. The Weighted Aggregate Sum Product Assessment (WASPAS) methodology and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) integrated with Fuzzy Analytic Hierarchy Process (FAHP) are used to evaluate the effect of various types of fibers on the mechanical performance of bituminous mixtures. Given the uncertainty involved, a stochastic simulation is proposed using the Monte Carlo method. A statistical analysis is carried out to verify the results obtained. Both methods of multi-criteria analysis were effective, with TOPSIS being slightly more conservative in the assignment of performance scores. Synthetic fibers proved to be a suitable option as did fibers with high tensile strength and elastic modulus
CSNK2B
CSNK2B has recently been implicated as a disease gene for neurodevelopmental disability (NDD) and epilepsy. Information about developmental outcomes has been limited by the young age and short follow up for many of the previously reported cases, and further delineation of the spectrum of associated phenotypes is needed. We present 25 new patients with variants in CSNK2B and refine the associated NDD and epilepsy phenotypes. CSNK2B variants were identified by research or clinical exome sequencing, and investigators from different centers were connected via GeneMatcher. Most individuals had developmental delay and generalized epilepsy with onset in the first two years. However, we found a broad spectrum of phenotypic severity, ranging from early normal development with pharmacoresponsive seizures to profound intellectual disability with intractable epilepsy and recurrent refractory status epilepticus. These findings suggest that CSNK2B should be considered in the diagnostic evaluation of patients with a broad range of NDD with treatable or intractable seizures
CSNK2B: A broad spectrum of neurodevelopmental disability and epilepsy severity
CSNK2B has recently been implicated as a disease gene for neurodevelopmental disability (NDD) and epilepsy. Information about developmental outcomes has been limited by the young age and short follow-up for many of the previously reported cases, and further delineation of the spectrum of associated phenotypes is needed. We present 25 new patients with variants in CSNK2B and refine the associated NDD and epilepsy phenotypes. CSNK2B variants were identified by research or clinical exome sequencing, and investigators from different centers were connected via GeneMatcher. Most individuals had developmental delay and generalized epilepsy with onset in the first 2 years. However, we found a broad spectrum of phenotypic severity, ranging from early normal development with pharmacoresponsive seizures to profound intellectual disability with intractable epilepsy and recurrent refractory status epilepticus. These findings suggest that CSNK2B should be considered in the diagnostic evaluation of patients with a broad range of NDD with treatable or intractable seizures
A Surface Scientist's view on Spectroscopic Ellipsometry
none1noneMaurizio CanepaCanepa, Maurizi
Whole-genome sequencing reveals host factors underlying critical COVID-19
Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization 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