Université libre de Bruxelles

About: Université libre de Bruxelles is a education organization based out in Brussels, Belgium. It is known for research contribution in the topics: Population & Breast cancer. The organization has 24974 authors who have published 56969 publications receiving 2084303 citations. The organization is also known as: ULB.

Diversity of bacterial type II toxin–antitoxin systems: a comprehensive search and functional analysis of novel families

Abstract: Type II toxin-antitoxin (TA) systems are generally composed of two genes organized in an operon, encoding a labile antitoxin and a stable toxin. They were first discovered on plasmids where they contribute to plasmid stability by a phenomenon denoted as 'addiction', and subsequently in bacterial chromosomes. To discover novel families of antitoxins and toxins, we developed a bioinformatics approach based on the 'guilt by association' principle. Extensive experimental validation in Escherichia coli of predicted antitoxins and toxins increased significantly the number of validated systems and defined novel toxin and antitoxin families. Our data suggest that toxin families as well as antitoxin families originate from distinct ancestors that were assembled multiple times during evolution. Toxin and antitoxin families found on plasmids tend to be promiscuous and widespread, indicating that TA systems move through horizontal gene transfer. We propose that due to their addictive properties, TA systems are likely to be maintained in chromosomes even though they do not necessarily confer an advantage to their bacterial hosts. Therefore, addiction might play a major role in the evolutionary success of TA systems both on mobile genetic elements and in bacterial chromosomes.

Calibrating Probability with Undersampling for Unbalanced Classification

Abstract: Under sampling is a popular technique for unbalanced datasets to reduce the skew in class distributions. However, it is well-known that under sampling one class modifies the priors of the training set and consequently biases the posterior probabilities of a classifier. In this paper, we study analytically and experimentally how under sampling affects the posterior probability of a machine learning model. We formalize the problem of under sampling and explore the relationship between conditional probability in the presence and absence of under sampling. Although the bias due to under sampling does not affect the ranking order returned by the posterior probability, it significantly impacts the classification accuracy and probability calibration. We use Bayes Minimum Risk theory to find the correct classification threshold and show how to adjust it after under sampling. Experiments on several real-world unbalanced datasets validate our results.

Pancreatic duct : morphologic and functional evaluation with dynamic MR pancreatography after secretin stimulation

Abstract: PURPOSE: To assess the utility of dynamic MR pancreatography in the evaluation of the behavior of the pancreatic duct after secretin stimulation and to estimate pancreatic exocrine reserve in patients suspected of having acute recurrent or chronic pancreatitis. MATERIALS AND METHODS: Ten healthy volunteers and 13 patients suspected of having pancreatic disease and no obvious markers of chronic pancreatitis were studied. Single-shot turbo spin-echo T2-weighted dynamic MR pancreatograms were obtained before and every 30 seconds during the 10 minutes after secretin administration. Morphologic features and diameter of the pancreatic duct were monitored before and during secretin stimulation. Duodenal filling volume was graded. Results were compared with those of endoscopic retrograde cholangiopancreatography and secretin stimulation testing with collection of pancreatic fluid. RESULTS: Secretin improved the delineation of ductal morphologic features in both groups. Persistent dilatation of the pancreatic duct...

XPS characterization of Au/TiO2 catalysts: Binding energy assessment and irradiation effects

Abstract: X-ray photoelectron spectroscopy (XPS) was employed to study the surface composition and electronic structure of Au/TiO2 catalysts in comparison with TiO2 (anatase) and to reveal time-dependent X-ray irradiation damage of the samples. The occurrence of Au nano-sized particles on a TiO2 support was found to result in a slight shift of Ti 2p core-level spectrum and in changes of the valence band and X-ray induced Auger spectra, compared to TiO2-only. It was shown that for different means of energy referencing the charge-corrected Au 4f7/2 binding energy in Au/TiO2 catalysts was 0.15–0.45 eV lower than that in pure bulk Au. Exposure to X-rays of Au/TiO2 catalysts and pure TiO2 caused a reduction of Ti 4+ oxidation state and desorption of oxygen from the surface. As a result, the surface chemical composition and electronic structure of the samples changed with time. The X-ray irradiation affected charge transfer processes in Au/TiO2 so that the pattern of X-ray induced damage in the Au-based catalyst turned out to be quite different from that in TiO2, with some characteristics displaying the very opposite features. Decreasing of the Au 4f7/2 binding energy and concurrent increasing of the fraction of Ti3+ species observed in the beginning of X-ray irradiation of Au/TiO2 may be taken as direct evidence for charge transfer from oxygen vacancies created by irradiation to Au particles.