Discovery of inverse-Compton X-ray emission and estimate of the volume-averaged magnetic field in a galaxy group

Observed in a significant fraction of clusters and groups of galaxies, diffuse radio synchrotron emission reveals the presence of relativistic electrons and magnetic fields permeating large-scale systems of galaxies. Although these non-thermal electrons are expected to upscatter cosmic microwave background photons up to hard X-ray energies, such inverse-Compton (IC) X-ray emission has so far not been unambiguously detected on cluster/group scales. Using deep, new proprietary XMM-Newton observations ($\sim$200 ks of clean exposure), we report a 4.6$\sigma$ detection of extended IC X-ray emission in MRC 0116+111, an extraordinary group of galaxies at $z = 0.131$. Assuming a spectral slope derived from low-frequency radio data, the detection remains robust to systematic uncertainties. Together with low-frequency radio data from GMRT, this detection provides an estimate for the volume-averaged magnetic field of $(1.9 \pm 0.3)$ $\mu$G within the central part of the group. This value can serve as an anchor for studies of magnetic fields in the largest gravitationally bound systems in the Universe.Comment: 11 pages, 7 figures, accepted for publication in MNRA

II Congrés Internacional sobre Traducció : abril 1994 : actes

Machine learning-based approach unravels distinct pathological signatures induced by patient-derived α-synuclein seeds in monkeys. Dopaminergic neuronal cell death, associated with intracellular α-synuclein (α-syn)-rich protein aggregates [termed "Lewy bodies" (LBs)], is a well-established characteristic of Parkinson's disease (PD). Much evidence, accumulated from multiple experimental models, has suggested that α-syn plays a role in PD pathogenesis, not only as a trigger of pathology but also as a mediator of disease progression through pathological spreading. Here, we have used a machine learning-based approach to identify unique signatures of neurodegeneration in monkeys induced by distinct α-syn pathogenic structures derived from patients with PD. Unexpectedly, our results show that, in nonhuman primates, a small amount of singular α-syn aggregates is as toxic as larger amyloid fibrils present in the LBs, thus reinforcing the need for preclinical research in this species. Furthermore, our results provide evidence supporting the true multifactorial nature of PD, as multiple causes can induce a similar outcome regarding dopaminergic neurodegeneratio

RNA motif search with data-driven element ordering

BACKGROUND: In this paper, we study the problem of RNA motif search in long genomic sequences. This approach uses a combination of sequence and structure constraints to uncover new distant homologs of known functional RNAs. The problem is NP-hard and is traditionally solved by backtracking algorithms. RESULTS: We have designed a new algorithm for RNA motif search and implemented a new motif search tool RNArobo. The tool enhances the RNAbob descriptor language, allowing insertions in helices, which enables better characterization of ribozymes and aptamers. A typical RNA motif consists of multiple elements and the running time of the algorithm is highly dependent on their ordering. By approaching the element ordering problem in a principled way, we demonstrate more than 100-fold speedup of the search for complex motifs compared to previously published tools. CONCLUSIONS: We have developed a new method for RNA motif search that allows for a significant speedup of the search of complex motifs that include pseudoknots. Such speed improvements are crucial at a time when the rate of DNA sequencing outpaces growth in computing. RNArobo is available at http://compbio.fmph.uniba.sk/rnarobo. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1074-x) contains supplementary material, which is available to authorized users

BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits

BACterial Hosts for production of Bioactive phenolics from bERRY fruits (BacHBerry) was a 3-year project funded by the Seventh Framework Programme (FP7) of the European Union that ran between November 2013 and October 2016. The overall aim of the project was to establish a sustainable and economically-feasible strategy for the production of novel high-value phenolic compounds isolated from berry fruits using bacterial platforms. The project aimed at covering all stages of the discovery and pre-commercialization process, including berry collection, screening and characterization of their bioactive components, identification and functional characterization of the corresponding biosynthetic pathways, and construction of Gram-positive bacterial cell factories producing phenolic compounds. Further activities included optimization of polyphenol extraction methods from bacterial cultures, scale-up of production by fermentation up to pilot scale, as well as societal and economic analyses of the processes. This review article summarizes some of the key findings obtained throughout the duration of the project

Comprehensive modeling of chloride ion and water ingress into concrete considering thermal and carbonation state for real climate

This article presents a comprehensive modeling of temperature, carbonation, water and chloride ions transport in cover concrete using the transport model "TransChlor". The TransChlor transport model employs weather data and chloride ion concentrations present on the concrete surface to predict the temporal and spatial evolution of the presence of chloride ion concentrations in the cover concrete pores. The main features of the TransChlor model are presented and validated