UoL4.0 Challenge 2019: Challenge-Based Learning as an approach to develop students' 21st Century digital skills, through UoL and businesses technology-based co-production

UoL4.0 Challenge 2019 is a challenge-based teaching and research project aimed at bringing together University of Lincoln students and Lincolnshire businesses to tackle real-life industry challenges. For the first edition of the project, challenges were related to the impact of Industry 4.0 on Lincolnshire businesses. The main goal was to enable a collaborative learning platform where all participants (students, teachers, businesses) could work together to identify how digital technologies may positively impact Lincolnshire’s economy. The challenge allowed students to solve real-life technology-based challenges, develop 21st century skills and share the experience with academics and members of Lincolnshire industry

Double-peaked Narrow-Line Signatures of Dual Supermassive Black Holes in Galaxy Merger Simulations

We present a first attempt to model the narrow-line (NL) region of active galactic nuclei (AGN) in hydrodynamic simulations of galaxy mergers, using a novel physical prescription. This model is used to determine the origin of double-peaked NL (dNL) AGN in merging galaxies and their connection to supermassive black hole (SMBH) pairs, motivated by recent observations of such objects. We find that dNL AGN induced by the relative motion of SMBH pairs are a generic but short-lived feature of gaseous major mergers. dNL AGN should often be observed in late-stage mergers, during the kpc-scale phase of SMBH inspiral or soon after the SMBH merger. However, even within the kpc-scale phase, only a minority of dNL AGN are directly induced by SMBH motion; their lifetimes are typically a few Myr. Most double peaks arise from gas kinematics near the SMBH, although prior to the SMBH merger up to 80% of all dNL profiles may be influenced by SMBH motion via altered peak ratios or velocity offsets. The total lifetimes of dNL AGN depend strongly on viewing angle and on properties of the merging galaxies. Also, in a typical merger, at least 10-40% of the double peaks induced by SMBH motion have small projected separations, 0.1-1 kpc, such that dual peaks of stellar surface brightness are not easily resolved. Diffuse tidal features can indicate late-stage galaxy mergers, although they do not distinguish SMBH pairs from merged SMBHs. We show that dNL profiles with peak velocity splittings > 500 km s^-1 or with measurable overall velocity shifts are often associated with SMBH pairs. Our results support the notion that selection of dNL AGN is a promising method for identifying dual SMBH candidates, but demonstrate the critical importance of high-resolution, multi-wavelength follow-up observations, and the use of multiple lines of evidence, for confirming the dual nature of candidate SMBH pairs. (Abridged)Comment: 24 pages, 9 figures. Moderate revisions; accepted to MNRA

Dense matter with eXTP

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry (eXTP) mission for determining the nature of dense matter; neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Science, the eXTP mission is expected to be launched in the mid 2020s.Comment: Accepted for publication on Sci. China Phys. Mech. Astron. (2019

Occurence and Bioactivities of Funicone-Related Compounds

Studies on production of secondary metabolites by fungi have received a substantial boost lately, particularly with reference to applications of their biological properties in human medicine. Funicones represent a series of related compounds for which there is accumulating evidence supporting their possible use as pharmaceuticals. This paper provides a review on the current status of knowledge on these fungal extrolites, with special reference to aspects concerning their molecular structures and biological activities

Virome assembly and annotation: A surprise in the Namib Desert

Sequencing, assembly, and annotation of environmental virome samples is challenging. Methodological biases and differences in species abundance result in fragmentary read coverage; sequence reconstruction is further complicated by the mosaic nature of viral genomes. In this paper, we focus on biocomputational aspects of virome analysis, emphasizing latent pitfalls in sequence annotation. Using simulated viromes that mimic environmental data challenges we assessed the performance of five assemblers (CLC-Workbench, IDBA-UD, SPAdes, RayMeta, ABySS). Individual analyses of relevant scaffold length fractions revealed shortcomings of some programs in reconstruction of viral genomes with excessive read coverage (IDBA-UD, RayMeta), and in accurate assembly of scaffolds ?50 kb (SPAdes, RayMeta, ABySS). The CLC-Workbench assembler performed best in terms of genome recovery (including highly covered genomes) and correct reconstruction of large scaffolds; and was used to assemble a virome from a copper rich site in the Namib Desert. We found that scaffold network analysis and cluster-specific read reassembly improved reconstruction of sequences with excessive read coverage, and that strict data filtering for non-viral sequences prior to downstream analyses was essential. In this study we describe novel viral genomes identified in the Namib Desert copper site virome. Taxonomic affiliations of diverse proteins in the dataset and phylogenetic analyses of circovirus-like proteins indicated links to the marine habitat. Considering additional evidence from this dataset we hypothesize that viruses may have been carried from the Atlantic Ocean into the Namib Desert by fog and wind, highlighting the impact of the extended environment on an investigated niche in metagenome studies.IS

Thermodynamics of Surfactants, Block Copolymers and Their Mixtures in Water: The Role of the Isothermal Calorimetry

The thermodynamics of conventional surfactants, block copolymers and their mixtures in water was described to the light of the enthalpy function. The two methodologies, i.e. the van’t Hoff approach and the isothermal calorimetry, used to determine the enthalpy of micellization of pure surfactants and block copolymers were described. The van’t Hoff method was critically discussed. The aqueous copolymer+surfactant mixtures were analyzed by means of the isothermal titration calorimetry and the enthalpy of transfer of the copolymer from the water to the aqueous surfactant solutions. Thermodynamic models were presented to show the procedure to extract straightforward molecular insights from the bulk properties

Protease Activity Increases in Plasma, Peritoneal Fluid, and Vital Organs after Hemorrhagic Shock in Rats

Hemorrhagic shock (HS) is associated with high mortality. A severe decrease in blood pressure causes the intestine, a major site of digestive enzymes, to become permeable – possibly releasing those enzymes into the circulation and peritoneal space, where they may in turn activate other enzymes, e.g. matrix metalloproteinases (MMPs). If uncontrolled, these enzymes may result in pathophysiologic cleavage of receptors or plasma proteins. Our first objective was to determine, in compartments outside of the intestine (plasma, peritoneal fluid, brain, heart, liver, and lung) protease activities and select protease concentrations after hemorrhagic shock (2 hours ischemia, 2 hours reperfusion). Our second objective was to determine whether inhibition of proteases in the intestinal lumen with a serine protease inhibitor (ANGD), a process that improves survival after shock in rats, reduces the protease activities distant from the intestine. To determine the protease activity, plasma and peritoneal fluid were incubated with small peptide substrates for trypsin-, chymotrypsin-, and elastase-like activities or with casein, a substrate cleaved by multiple proteases. Gelatinase activities were determined by gelatin gel zymography and a specific MMP-9 substrate. Immunoblotting was used to confirm elevated pancreatic trypsin in plasma, peritoneal fluid, and lung and MMP-9 concentrations in all samples after hemorrhagic shock. Caseinolytic, trypsin-, chymotrypsin-, elastase-like, and MMP-9 activities were all significantly (p<0.05) upregulated after hemorrhagic shock regardless of enteral pretreatment with ANGD. Pancreatic trypsin was detected by immunoblot in the plasma, peritoneal space, and lungs after hemorrhagic shock. MMP-9 concentrations and activities were significantly upregulated after hemorrhagic shock in plasma, peritoneal fluid, heart, liver, and lung. These results indicate that protease activities, including that of trypsin, increase in sites distant from the intestine after hemorrhagic shock. Proteases, including pancreatic proteases, may be shock mediators and potential targets for therapy in shock

MALDI Profiling of Human Lung Cancer Subtypes

Proteomics is expected to play a key role in cancer biomarker discovery. Although it has become feasible to rapidly analyze proteins from crude cell extracts using mass spectrometry, complex sample composition hampers this type of measurement. Therefore, for effective proteome analysis, it becomes critical to enrich samples for the analytes of interest. Despite that one-third of the proteins in eukaryotic cells are thought to be phosphorylated at some point in their life cycle, only a low percentage of intracellular proteins is phosphorylated at a given time.In this work, we have applied chromatographic phosphopeptide enrichment techniques to reduce the complexity of human clinical samples. A novel method for high-throughput peptide profiling of human tumor samples, using Parallel IMAC and MALDI-TOF MS, is described. We have applied this methodology to analyze human normal and cancer lung samples in the search for new biomarkers. Using a highly reproducible spectral processing algorithm to produce peptide mass profiles with minimal variability across the samples, lineal discriminant-based and decision tree–based classification models were generated. These models can distinguish normal from tumor samples, as well as differentiate the various non–small cell lung cancer histological subtypes.A novel, optimized sample preparation method and a careful data acquisition strategy is described for high-throughput peptide profiling of small amounts of human normal lung and lung cancer samples. We show that the appropriate combination of peptide expression values is able to discriminate normal lung from non-small cell lung cancer samples and among different histological subtypes. Our study does emphasize the great potential of proteomics in the molecular characterization of cancer

Benchmarking natural-language parsers for biological applications using dependency graphs

BACKGROUND: Interest is growing in the application of syntactic parsers to natural language processing problems in biology, but assessing their performance is difficult because differences in linguistic convention can falsely appear to be errors. We present a method for evaluating their accuracy using an intermediate representation based on dependency graphs, in which the semantic relationships important in most information extraction tasks are closer to the surface. We also demonstrate how this method can be easily tailored to various application-driven criteria. RESULTS: Using the GENIA corpus as a gold standard, we tested four open-source parsers which have been used in bioinformatics projects. We first present overall performance measures, and test the two leading tools, the Charniak-Lease and Bikel parsers, on subtasks tailored to reflect the requirements of a system for extracting gene expression relationships. These two tools clearly outperform the other parsers in the evaluation, and achieve accuracy levels comparable to or exceeding native dependency parsers on similar tasks in previous biological evaluations. CONCLUSION: Evaluating using dependency graphs allows parsers to be tested easily on criteria chosen according to the semantics of particular biological applications, drawing attention to important mistakes and soaking up many insignificant differences that would otherwise be reported as errors. Generating high-accuracy dependency graphs from the output of phrase-structure parsers also provides access to the more detailed syntax trees that are used in several natural-language processing techniques