Big data-led cancer research, applications and insights

Insights distilled from integratingmultiple big-data or "omic" datasets have revealed functional hierarchies of molecular networks driving tumorigenesis and modifiers of treatment response. Identifying these novel key regulatory and dysregulated elements is now informing personalized medicine. Crucially, although there are many advantages to this approach, there are several key considerations to address. Here, we examine how this big data-led approach is impacting many diverse areas of cancer research, through review of the key presentations given at the Irish Association for Cancer Research Meeting and importantly how the results may be applied to positively affect patient outcomes

Dimers, Effective Interactions, and Pauli Blocking Effects in a Bilayer of Cold Fermionic Polar Molecules

We consider a bilayer setup with two parallel planes of cold fermionic polar molecules when the dipole moments are oriented perpendicular to the planes. The binding energy of two-body states with one polar molecule in each layer is determined and compared to various analytic approximation schemes in both coordinate- and momentum-space. The effective interaction of two bound dimers is obtained by integrating out the internal dimer bound state wave function and its robustness under analytical approximations is studied. Furthermore, we consider the effect of the background of other fermions on the dimer state through Pauli blocking, and discuss implications for the zero-temperature many-body phase diagram of this experimentally realizable system.Comment: 18 pages, 10 figures, accepted versio

Crystal field potential and short range order effects in inelastic neutron scattering, magnetization, and heat capacity of the cage glass compound HoB12

The strongly correlated system Ho11B12 with boron sublattice Jahn Teller instability and nanoscale electronic phase separation dynamic charge stripes was studied in detail by inelastic neutron scattering INS , magnetometry, and heat capacity measurements at temperatures in the range of 3 300 K. From the analysis of registered INS spectra, we determined parameters of the cubic crystal field CF at holmium sites B4 amp; 8722;0.333 meV and B6 amp; 8722;2.003 meV in Stevens notations , with an unconventional large ratio B6 B4 pointing to the dominant role of conduction electrons in the formation of a CF potential. The molecular field in the antiferromagnetic AFM state Bloc 1.75 0.1 T has been directly determined from the INS spectra together with short range order effects detected in the paramagnetic state. A comparison of measured magnetization in diluted Lu0.99Ho0.01B12 and concentrated HoB12 single crystals showed a strong suppression of Ho magnetic moments by AFM exchange interactions in holmium dodecaboride. To account explicitly for the short range AFM correlations, a self consistent holmium dimer model was developed that allowed us to reproduce successfully field and temperature variations of the magnetization and heat capacity in the cage glass phase of HoB12 in external magnetic field

Anomalous Heat Conduction and Anomalous Diffusion in Low Dimensional Nanoscale Systems

Thermal transport is an important energy transfer process in nature. Phonon is the major energy carrier for heat in semiconductor and dielectric materials. In analogy to Ohm's law for electrical conductivity, Fourier's law is a fundamental rule of heat transfer in solids. It states that the thermal conductivity is independent of sample scale and geometry. Although Fourier's law has received great success in describing macroscopic thermal transport in the past two hundreds years, its validity in low dimensional systems is still an open question. Here we give a brief review of the recent developments in experimental, theoretical and numerical studies of heat transport in low dimensional systems, include lattice models, nanowires, nanotubes and graphenes. We will demonstrate that the phonon transports in low dimensional systems super-diffusively, which leads to a size dependent thermal conductivity. In other words, Fourier's law is breakdown in low dimensional structures

Large-scale magnetic fields from inflation due to a CPTCPT-even Chern-Simons-like term with Kalb-Ramond and scalar fields

We investigate the generation of large-scale magnetic fields due to the breaking of the conformal invariance in the electromagnetic field through the $CPT$-even dimension-six Chern-Simons-like effective interaction with a fermion current by taking account of the dynamical Kalb-Ramond and scalar fields in inflationary cosmology. It is explicitly demonstrated that the magnetic fields on 1Mpc scale with the field strength of $\sim 10^{-9}$G at the present time can be induced.Comment: 18 pages, 6 figures, version accepted for publication in Eur. Phys. J.

Procyanidins are potent inhibitors of LOX-1: a new player in the French Paradox

Lectin-like oxidized LDL receptor-1 (LOX-1) is an endothelial receptor for oxidized LDL (oxLDL) and plays multiple roles in the development of cardiovascular diseases. We screened more than 400 foodstuff extracts for identifying materials that inhibit oxLDL binding to LOX-1. Results showed that 52 extracts inhibited LOX-1 by more than 70% in cell-free assays. Subsequent cell-based assays revealed that a variety of foodstuffs known to be rich in procyanidins such as grape seed extracts and apple polyphenols, potently inhibited oxLDL uptake in Chinese hamster ovary (CHO) cells expressing LOX-1. Indeed, purified procyanidins significantly inhibited oxLDL binding to LOX-1 while other ingredients of apple polyphenols did not. Moreover, chronic administration of oligomeric procyanidins suppressed lipid accumulation in vascular wall in hypertensive rats fed with high fat diet. These results suggest that procyanidins are LOX-1 inhibitors and LOX-1 inhibition might be a possible underlying mechanism of the well-known vascular protective effects of red wine, the French Paradox

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives