NamesforLife Semantic Resolution Services for the Life Sciences

A major challenge in bioinformatics, life sciences, and medicine is using correct and informative names. While this sounds simple enough, many different naming conventions exist in the life sciences and medicine that may be either complementary or competitive with other naming conventions. For a variety of reasons, proper names are not always used, leading to an accumulated semantic ambiguity that readers of the literature and end users of databases are left to resolve on their own. This ambiguity is a growing problem and the biocuration community is aware of its consequences. 

To assist those confronted with ambiguous names (which not only includes researchers but clinicians, manufacturers, patent attorneys, and others who use biological data in their routine work), we developed a generalizable semantic model that represents names, concepts, and exemplars (representations of biological entities) as distinct objects. By identifying each object with a Digital Object Identifier (DOI) it becomes possible to place forward-pointing links in the published literature, in databases, and vector graphics that can be used as part of a mechanism for resolving ambiguities, thereby “future proofing” a nomenclature or terminology. A full implementation of the N4L model for the _Bacteria_ and _Archaea_ was released in April, 2010. The system is professionally curated and represents a Tier III resource in Parkhill’s view of bioinformatic services. A variety of tools and web services have been developed for readers, publishers, and others (N4L Guide, N4L Autotagger, N4L Semantic Search, N4L Taxonomic Abstracts) and we are incorporating other taxonomies into the N4L data model, as well as adding additional phenotypic, genotypic, and genomic information to the existing exemplars to add greater value to end users

Soft topographic map for clustering and classification of bacteria

In this work a new method for clustering and building a topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria class by means of the 16S rRNA housekeeping gene. Complete sequences of the gene have been retrieved from the NCBI public database. In the experimental tests the maps show clusters of homologous type strains and present some singular cases potentially due to incorrect classification or erroneous annotations in the database

Duality and hidden equilibrium in transport models

A large family of diffusive models of transport that have been considered in the past years admit a transformation into the same model in contact with an equilibrium bath. This mapping holds at the full dynamical level, and is independent of dimension or topology. It provides a good opportunity to discuss questions of time reversal in out of equilibrium contexts. In particular, thanks to the mapping one may define the free energy in the non-equilibrium states very naturally as the (usual) free energy of the mapped system

Spectroscopic and Mechanistic Studies of Heterodimetallic Forms of Metallo-β-lactamase NDM-1

In an effort to characterize the roles of each metal ion in metallo-β-lactamase NDM-1, heterodimetallic analogues (CoCo-, ZnCo-, and CoCd-) of the enzyme were generated and characterized. UV–vis, 1H NMR, EPR, and EXAFS spectroscopies were used to confirm the fidelity of the metal substitutions, including the presence of a homogeneous, heterodimetallic cluster, with a single-atom bridge. This marks the first preparation of a metallo-β-lactamase selectively substituted with a paramagnetic metal ion, Co(II), either in the Zn1 (CoCd-NDM-1) or in the Zn2 site (ZnCo-NDM-1), as well as both (CoCo-NDM-1). We then used these metal-substituted forms of the enzyme to probe the reaction mechanism, using steady-state and stopped-flow kinetics, stopped-flow fluorescence, and rapid-freeze-quench EPR. Both metal sites show significant effects on the kinetic constants, and both paramagnetic variants (CoCd- and ZnCo-NDM-1) showed significant structural changes on reaction with substrate. These changes are discussed in terms of a minimal kinetic mechanism that incorporates all of the data

Resonant phonon coupling across the La{1-x}Sr{x}MnO{3}/SrTiO{3} interface

The transport and magnetic properties of correlated La{0.53}Sr{0.47}MnO{3} ultrathin films, grown epitaxially on SrTiO{3}, show a sharp cusp at the structural transition temperature of the substrate. Using a combination of experiment and theory we show that the cusp is a result of resonant coupling between the charge carriers in the film and a soft phonon mode in the SrTiO{3}, mediated through oxygen octahedra in the film. The amplitude of the mode diverges towards the transition temperature, and phonons are launched into the first few atomic layers of the film affecting its electronic state

Association between inflammation and post-intensive care syndrome: a systematic review

Post-intensive care syndrome describes the physical, cognitive and emotional symptoms which persist following critical illness. At present there is limited understanding of the pathological mechanisms contributing to the development of post-intensive care syndrome. The aim of this systematic review was to synthesise current evidence exploring the association between inflammation and features of post-intensive care syndrome in survivors of critical illness. Relevant databases were systematically searched for studies of human participants exposed to critical illness. We sought studies that reported results for biomarkers with an identified role in the pathophysiology of inflammation obtained at any time-point in the patient journey and an outcome measure of any feature of post-intensive care syndrome at any point following hospital discharge. We included 32 studies, with 23 in the primary analysis and nine in a brain injury subgroup analysis. In the primary analysis, 47 different biomarkers were sampled and 44 different outcome measures were employed. Of the biomarkers which were sampled in five or more studies, interleukin-8, C-reactive protein and interleukin-10 most frequently showed associations with post-intensive care syndrome outcomes in 71%, 62% and 60% of studies, respectively. There was variability in terms of which biomarkers were sampled, time-points of sampling and outcome measures reported. Overall, there was mixed evidence of a potential association between an inflammatory process and long-term patient outcomes following critical illness. Further high-quality research is required to develop a longitudinal inflammatory profile of survivors of critical illness over the recovery period and evaluate the association with outcomes

Overview of mathematical approaches used to model bacterial chemotaxis I: the single cell

Mathematical modeling of bacterial chemotaxis systems has been influential and insightful in helping to understand experimental observations. We provide here a comprehensive overview of the range of mathematical approaches used for modeling, within a single bacterium, chemotactic processes caused by changes to external gradients in its environment. Specific areas of the bacterial system which have been studied and modeled are discussed in detail, including the modeling of adaptation in response to attractant gradients, the intracellular phosphorylation cascade, membrane receptor clustering, and spatial modeling of intracellular protein signal transduction. The importance of producing robust models that address adaptation, gain, and sensitivity are also discussed. This review highlights that while mathematical modeling has aided in understanding bacterial chemotaxis on the individual cell scale and guiding experimental design, no single model succeeds in robustly describing all of the basic elements of the cell. We conclude by discussing the importance of this and the future of modeling in this area

Ring-Exchange Interaction Effects on Magnons in Dirac Magnet CoTiO3_3

In magnetically ordered materials with localized electrons, the fundamental magnetic interactions are due to exchange of electrons [1-3]. Typically, only the interaction between pairs of electrons' spins is considered to explain the nature of the ground state and its excitations, whereas three-, four-, and six-spin interactions are ignored. When these higher order processes occur in a loop they are called cyclic or ring exchange. The ring-exchange interaction is required to explain low temperature behavior in bulk and thin films of solid $^3$He [4-8]. It also plays a crucial role in the quantum magnet La$_2$CuO$_4$ [9,10]. Here, we use a combination of time domain THz (TDTS) and magneto-Raman spectroscopies to measure the low energy magnetic excitations in CoTiO$_3$, a proposed Dirac topological magnon material [11,12] where the origin of the energy gap in the magnon spectrum at the Brillouin zone center remains unclear. We measured the magnetic field dependence of the energies of the two lowest energy magnons and determine that the gap opens due to the ring-exchange interaction between the six spins in a hexagon. This interaction also explains the selection rules of the THz magnon absorption. Finally, we clarify that topological surface magnons are not expected in CoTiO$_3$. Our study demonstrates the power of combining TDTS and Raman spectroscopies with theory to identify the microscopic origins of the magnetic excitations in quantum magnets.Comment: 7 pages, 4 figures in main text, 26 pages and 11 figures in supplemen

Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

Biophysical and electrochemical studies of protein-nucleic acid interactions

This review is devoted to biophysical and electrochemical methods used for studying protein-nucleic acid (NA) interactions. The importance of NA structure and protein-NA recognition for essential cellular processes, such as replication or transcription, is discussed to provide background for description of a range of biophysical chemistry methods that are applied to study a wide scope of protein-DNA and protein-RNA complexes. These techniques employ different detection principles with specific advantages and limitations and are often combined as mutually complementary approaches to provide a complete description of the interactions. Electrochemical methods have proven to be of great utility in such studies because they provide sensitive measurements and can be combined with other approaches that facilitate the protein-NA interactions. Recent applications of electrochemical methods in studies of protein-NA interactions are discussed in detail