Multi-centre evaluation of real-time multiplex PCR for detection of carbapenemase genes OXA-48, VIM, IMP, NDM and KPC

Background: Resistance to carbapenem antibiotics is emerging worldwide among Enterobacteriaceae. To prevent hospital transmission due to unnoticed carriage of carbapenemase producing micro-organisms in newly admitted patients, or follow-up of patients in an outbreak setting, a molecular screening method was developed for detection of the most prevalent carbapenemase genes; blaOXA-48, blaVIM, blaIMP, blaNDM and blaKPC.Methods: A real-time multiplex PCR assay was evaluated using a collection of 86 Gram negative isolates, including 62 carbapenemase producers. Seven different laboratories carried out this method and used the assay for detection of the carbapenemase genes on a selection of 20 isolates.Results: Both sensitivity and specificity of the multiplex PCR assay was 100%, as established by results on the strain collection and the inter-laboratory comparisons.Conclusions: In this study, we present a multiplex real-time PCR that is a robust, reliable and rapid method for the detection of the most prevalent carbapenemases blaOXA-48, blaVIM, blaIMP, blaNDM and blaKPC, and is suitable for screening of broth cultured rectal swabs and for identification of carbapenemase genes in cultures

Spallative ablation of dielectrics by X-ray laser

Short laser pulse in wide range of wavelengths, from infrared to X-ray, disturbs electron-ion equilibrium and rises pressure in a heated layer. The case where pulse duration $\tau_L$ is shorter than acoustic relaxation time $t_s$ is considered in the paper. It is shown that this short pulse may cause thermomechanical phenomena such as spallative ablation regardless to wavelength. While the physics of electron-ion relaxation on wavelength and various electron spectra of substances: there are spectra with an energy gap in semiconductors and dielectrics opposed to gapless continuous spectra in metals. The paper describes entire sequence of thermomechanical processes from expansion, nucleation, foaming, and nanostructuring to spallation with particular attention to spallation by X-ray pulse

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

Stress testing and non-invasive coronary angiography in patients with suspected coronary artery disease: time for a new paradigm

Diagnosis and management of coronary artery disease represents major challenges to our health care system, affecting millions of patients each year. Until recently, the diagnosis of coronary artery disease was possible only through cardiac catheterization and invasive coronary angiography. To avoid the risks of an invasive procedure, stress testing is often employed for an initial assessment of patients with suspected coronary artery disease, serving as a gatekeeper for cardiac catheterization. With the emergence of non-invasive coronary angiography, the question arises if such a strategy is still sensible, particularly, in view of only a modest agreement between stress testing results and the presence of coronary artery disease established by cardiac catheterization. Much data in support of the diagnostic accuracy and prognostic value of non-invasive coronary angiography by computed tomography have emerged within the last few years. These data challenge the role of stress testing as the initial imaging modality in patients with suspected coronary artery disease. This article reviews the clinical utility, limitations, as well as the hazards of stress testing compared with non-invasive coronary artery imaging by computed tomography. Finally, the implications of this review are discussed in relation to clinical practice

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

Motivation for physical activity in young people: entity and incremental beliefs about athletic ability

Contains fulltext : 151628.pdf (publisher's version ) (Open Access)Radboud Universiteit Nijmegen, 14 december 2015Promotores : Busch, D., Grundmann-van de Krol, C.M.XXVI, 431 p