A Year in the Life of the EU-CardioRNA COST Action: CA17129 Catalysing Transcriptomics Research in Cardiovascular Disease

The EU-CardioRNA Cooperation in Science and Technology (COST) Action is a European-wide consortium established in 2018 with 31 European country members and four associate member countries to build bridges between translational researchers from academia and industry who conduct research on non-coding RNAs, cardiovascular diseases and similar research areas. EU-CardioRNA comprises four core working groups (WG1-4). In the first year since its launch, EU-CardioRNA met biannually to exchange and discuss recent findings in related fields of scientific research, with scientific sessions broadly divided up according to WG. These meetings are also an opportunity to establish interdisciplinary discussion groups, brainstorm ideas and make plans to apply for joint research grants and conduct other scientific activities, including knowledge transfer. Following its launch in Brussels in 2018, three WG meetings have taken place. The first of these in Lisbon, Portugal, the second in Istanbul, Turkey, and the most recent in Maastricht, The Netherlands. Each meeting includes a scientific session from each WG. This meeting report briefly describes the highlights and key take-home messages from each WG session in this first successful year of the EU-CardioRNA COST Action. © 2020 by the authors

Concurrent validity of self-rating scale of self-directed learning and self-directed learning instrument among Italian nursing students

BACKGROUND: Self-Directed Learning develops when students take the initiative for their learning, recognising needs, formulating goals, identifying resources, implementing appropriate strategies and evaluating learning outcomes. This should be seen as a collaborative process between the nurse educator and the learner. At the international level, various instruments have been used to measure Self-Directed Learning abilities (SDL), both in original and in culturally-adapted versions. However, few instruments have been subjected to full validation, and no gold standard reference has been established to date. In addition, few researchers have adopted the established tools to assess the concurrent validity of the emerging new tools. Therefore, the aim of this study was to measure the concurrent validity between the Self-Rating Scale of Self-Directed Learning (SRSSDL_Ita) - Italian version and the Self-Directed Learning Instruments (SDLI) in undergraduate nursing students. METHODS: A concurrent validity study design was conducted in a Bachelor level nursing degree programme located in Italy. All nursing students attending the first, second or third year (n=428) were the target sample. The SRSSDL_Ita, and the SDLI were used. The Pearson correlation was used to determine the concurrent validity between the instruments; the confidence of intervals (CI 95%) bias-corrected and accelerated bootstrap (BCa), were also calculated. RESULTS: The majority of participants were students attending their first year (47.9%), and were predominately female (78.5%). Their average age was 22.5\ub14.1. The SDL abilities scores, as measured with the SRSSDL_Ita (min 40, max 200), were, on average, 160.79 (95% CI 159.10-162.57; median 160); while with the SDLI (min 20, max 100), they were on average 82.57 (95% CI 81.79-83.38; median 83). The Pearson correlation between the SRSSDL_Ita and SDLI instruments was 0.815 (CI BCa 95% 0.774-0.848), (p=0.000). CONCLUSIONS: The findings confirm the concurrent validity of the SRSSDL_Ita with the SDLI. The SRSSDL_Ita instrument can be useful in the process of identifying Self-Directed Learning abilities, which are essential for students to achieve the expected learning goals and become lifelong learners

Cocaine by-product detection with metal oxide semiconductor sensor arrays

A range of n-type and p-type metal oxide semiconductor gas sensors based on SnO2 and Cr2O3 materials have been modified with zeolites H-ZSM-5, Na-A and H–Y to create a gas sensor array able to successfully detect a cocaine by-product, methyl benzoate, which is commonly targeted by detection dogs. Exposure to vapours was carried out with eleven sensors. Upon data analysis, four of these that offered promising qualities for detection were subsequently selected to understand whether machine learning methods would enable successful and accurate classification of gases. The capability of discrimination of the four sensor array was assessed against nine different vapours of interest; methyl benzoate, ethane, ethanol, nitrogen dioxide, ammonia, acetone, propane, butane, and toluene. When using the polykernel function (C = 200) in the Weka software – and just five seconds into the gas injection – the model was 94.1% accurate in successfully classifying the data. Although further work is necessary to bring the sensors to a standard of detection that is competitive with that of dogs, these results are very encouraging because they show the potential of metal oxide semiconductor sensors to rapidly detect a cocaine by-product in an inexpensive way

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

ReRep: Computational detection of repetitive sequences in genome survey sequences (GSS)

<p>Abstract</p> <p>Background</p> <p>Genome survey sequences (GSS) offer a preliminary global view of a genome since, unlike ESTs, they cover coding as well as non-coding DNA and include repetitive regions of the genome. A more precise estimation of the nature, quantity and variability of repetitive sequences very early in a genome sequencing project is of considerable importance, as such data strongly influence the estimation of genome coverage, library quality and progress in scaffold construction. Also, the elimination of repetitive sequences from the initial assembly process is important to avoid errors and unnecessary complexity. Repetitive sequences are also of interest in a variety of other studies, for instance as molecular markers.</p> <p>Results</p> <p>We designed and implemented a straightforward pipeline called ReRep, which combines bioinformatics tools for identifying repetitive structures in a GSS dataset. In a case study, we first applied the pipeline to a set of 970 GSSs, sequenced in our laboratory from the human pathogen <it>Leishmania braziliensis</it>, the causative agent of leishmaniosis, an important public health problem in Brazil. We also verified the applicability of ReRep to new sequencing technologies using a set of 454-reads of an <it>Escheria coli</it>. The behaviour of several parameters in the algorithm is evaluated and suggestions are made for tuning of the analysis.</p> <p>Conclusion</p> <p>The ReRep approach for identification of repetitive elements in GSS datasets proved to be straightforward and efficient. Several potential repetitive sequences were found in a <it>L. braziliensis </it>GSS dataset generated in our laboratory, and further validated by the analysis of a more complete genomic dataset from the EMBL and Sanger Centre databases. ReRep also identified most of the <it>E. coli </it>K12 repeats prior to assembly in an example dataset obtained by automated sequencing using 454 technology. The parameters controlling the algorithm behaved consistently and may be tuned to the properties of the dataset, in particular to the length of sequencing reads and the genome coverage. ReRep is freely available for academic use at <url>http://bioinfo.pdtis.fiocruz.br/ReRep/</url>.</p

Endoscopic Ultrasound in the Diagnosis and Staging of Pancreatic Cancer

Pancreatic cancer is one of the digestive cancers with the poorest prognosis, so an early and correct diagnosis is of utmost importance. With the development of new therapeutic options an accurate staging is essential. Endoscopic ultrasonography (EUS) has a major role in all stages of the management of these patients. EUS has a high accuracy in the diagnosis of pancreatic adenocarcinoma and the possibility to perform fine-needle aspiration/biopsy (FNA/FNB) increases the diagnostic yield of EUS. There is still no consensus on the several technical aspects of FNA, namely on the rapid on-site evaluation (ROSE), the diameter and type of needle, the number of passes and the use of stylet and suction. Contrast-enhanced EUS (CE-EUS) and EUS elastography (EUS-E) have been used in recent years as an adjunct to EUS-FNA. Given the higher sensitivity of these techniques a negative cytology by EUS-FNA should not exclude malignancy when CE-EUS and/or EUS-E are suggestive of pancreatic neoplasia. EUS remains one of the main methods in the staging of pancreatic adenocarcinoma, namely to further evaluate patients with non-metastatic disease that appears resectable on initial imaging. EUS is crucial for an accurate preoperative evaluation of pancreatic cancer which is essential to choose the correct management strategy. The possibility to obtain samples from suspicious lesions or lymph nodes, by means of EUS-guided fine-needle aspiration as well as the use of contrast-enhanced and elastography, makes EUS an ideal modality for the diagnosis and staging of pancreatic cancer.info:eu-repo/semantics/publishedVersio

Screening, production and biochemical characterization of a new fibrinolytic enzyme produced by Streptomyces sp. (Streptomycetaceae) isolated from Amazonian lichens

Thrombosis is a pathophysiological disorder caused by accumulation of fibrin in the blood. Fibrinolytic proteases with potent thrombolytic activity have been produced by diverse microbial sources. Considering the microbial biodiversity of the Amazon region, this study aimed at the screening, production and biochemical characterization of a fibrinolytic enzyme produced by Streptomyces sp. isolated from Amazonian lichens. The strain Streptomyces DPUA1576 showed the highest fibrinolytic activity, which was 283 mm2. Three variables at two levels were used to assess their effects on the fibrinolytic production. The parameters studied were agitation (0.28 - 1.12 g), temperature (28 - 36 ºC) and pH (6.0 - 8.0); all of them had significant effects on the fibrinolytic production. The maximum fibrinolytic activity (304 mm2) was observed at 1.12 g, 28 ºC, and pH of 8.0. The crude extract of the fermentation broth was used to assess the biochemical properties of the enzyme. Protease and fibrinolytic activities were stable during 6 h, at a pH ranging from 6.8 to 8.4 and 5.8 to 9.2, respectively. Optimum temperature for protease activity ranged between 35 and 55 °C, while the highest fibrinolytic activity was observed at 45 ºC. Proteolytic activity was inhibited by Cu2+ and Co2+ ions, phenylmethylsulfonyl fluoride (PMSF) and pepstatin A, which suggests that the enzyme is a serine protease. Enzymatic extract cleaved fibrinogen at the subunits A-chain, A-chain, and -chain. The results indicated that Streptomyces sp. DPUA 1576 produces enzymes with fibrinolytic and fibrinogenolytic activity, enzymes with an important application in the pharmaceutical industry.The authors grateful acknowledge the financial support of Fundação de Amparo a Pesquisa do Estado de Pernambuco (FACEPE, Pernambuco, Brazil, N. 0158-2.12/11), CNPq/ RENORBIO (National Counsel of Technological and Scientific Development, N.55146/2010-3) and National Council for the Improvement of Higher Education (CAPES, Brazil) for the scholarship. The author thanks editor and reviewers for their review and comments.info:eu-repo/semantics/publishedVersio

NMDA Receptor Stimulation Induces Reversible Fission of the Neuronal Endoplasmic Reticulum

With few exceptions the endoplasmic reticulum (ER) is considered a continuous system of endomembranes within which proteins and ions can move. We have studied dynamic structural changes of the ER in hippocampal neurons in primary culture and organotypic slices. Fluorescence recovery after photobleaching (FRAP) was used to quantify and model ER structural dynamics. Ultrastructure was assessed by electron microscopy. In live cell imaging experiments we found that, under basal conditions, the ER of neuronal soma and dendrites was continuous. The smooth and uninterrupted appearance of the ER changed dramatically after glutamate stimulation. The ER fragmented into isolated vesicles in a rapid fission reaction that occurred prior to overt signs of neuronal damage. ER fission was found to be independent of ER calcium levels. Apart from glutamate, the calcium ionophore ionomycin was able to induce ER fission. The N-methyl, D-aspartate (NMDA) receptor antagonist MK-801 inhibited ER fission induced by glutamate as well as by ionomycin. Fission was not blocked by either ifenprodil or kinase inhibitors. Interestingly, sub-lethal NMDA receptor stimulation caused rapid ER fission followed by fusion. Hence, ER fission is not strictly associated with cellular damage or death. Our results thus demonstrate that neuronal ER structure is dynamically regulated with important consequences for protein mobility and ER luminal calcium tunneling