An evaluation of strategies used by the Landscapes and Policy Hub to achieve interdisciplinary and transdisciplinary research

The report presents an evaluation of the Landscapes and Policy Hub's approach to interdisciplinary and transdisciplinary research. The hub was a national, four year, $15 million collaborative research program. The focus of the evaluation was for researchers to reflect on the effectiveness of strategies used by the hub to facilitate interdisciplinarity (where researchers from different disciplines work together to solve problems) and transdisciplinarity (where researchers from different disciplines work in partnership with research users to solve problems). The evaluation was commissioned in the final phase of the hub’s life in the interests of improving performance of future interdisciplinary and transdisciplinary research. It was based on a number of strategies that had been implemented by the hub to encourage and facilitate interdisciplinary research occurring in partnership with research users. The aim of the evaluation was to improve performance of future interdisciplinary and transdisciplinary research. Six recommendations are presented

MultiSig: a new high-precision approach to the analysis of complex biomolecular systems

MultiSig is a newly developed mode of analysis of sedimentation equilibrium (SE) experiments in the analytical ultracentrifuge, having the capability of taking advantage of the remarkable precision (~0.1 % of signal) of the principal optical (fringe) system employed, thus supplanting existing methods of analysis through reducing the ‘noise’ level of certain important parameter estimates by up to orders of magnitude. Long-known limitations of the SE method, arising from lack of knowledge of the true fringe number in fringe optics and from the use of unstable numerical algorithms such as numerical differentiation, have been transcended. An approach to data analysis, akin to ‘spatial filtering’, has been developed, and shown by both simulation and practical application to be a powerful aid to the precision with which near-monodisperse systems can be analysed, potentially yielding information on protein-solvent interaction. For oligo- and poly-disperse systems the information returned includes precise average mass distributions over both cell radial and concentration ranges and mass-frequency histograms at fixed radial positions. The application of MultiSig analysis to various complex heterogenous systems and potentially multiply-interacting carbohydrate oligomers is described

A transcriptome-driven analysis of epithelial brushings and bronchial biopsies to define asthma phenotypes in U-BIOPRED

RATIONALE AND OBJECTIVES: Asthma is a heterogeneous disease driven by diverse immunologic and inflammatory mechanisms. We used transcriptomic profiling of airway tissues to help define asthma phenotypes. METHODS: The transcriptome from bronchial biopsies and epithelial brushings of 107 moderate-to-severe asthmatics were annotated by gene-set variation analysis (GSVA) using 42 gene-signatures relevant to asthma, inflammation and immune function. Topological data analysis (TDA) of clinical and histological data was used to derive clusters and the nearest shrunken centroid algorithm used for signature refinement. RESULTS: 9 GSVA signatures expressed in bronchial biopsies and airway epithelial brushings distinguished two distinct asthma subtypes associated with high expression of T-helper type 2 (Th-2) cytokines and lack of corticosteroid response (Group 1 and Group 3). Group 1 had the highest submucosal eosinophils, high exhaled nitric oxide (FeNO) levels, exacerbation rates and oral corticosteroid (OCS) use whilst Group 3 patients showed the highest levels of sputum eosinophils and had a high BMI. In contrast, Group 2 and Group 4 patients had an 86% and 64% probability of having non-eosinophilic inflammation. Using machine-learning tools, we describe an inference scheme using the currently-available inflammatory biomarkers sputum eosinophilia and exhaled nitric oxide levels along with OCS use that could predict the subtypes of gene expression within bronchial biopsies and epithelial cells with good sensitivity and specificity. CONCLUSION: This analysis demonstrates the usefulness of a transcriptomic-driven approach to phenotyping that segments patients who may benefit the most from specific agents that target Th2-mediated inflammation and/or corticosteroid insensitivity

Realistic loophole-free Bell test with atom-photon entanglement

The establishment of nonlocal correlations, obtained through the violation of a Bell inequality, is not only important from a fundamental point of view, but constitutes the basis for device-independent quantum information technologies. Although several nonlocality tests have been performed so far, all of them suffered from either the locality or the detection loopholes. Recent studies have suggested that the use of atom-photon entanglement can lead to Bell inequality violations with moderate transmission and detection efficiencies. In this paper we propose an experimental setup realizing a simple atom-photon entangled state that, under realistic experimental parameters available to date, achieves a significant violation of the Clauser-Horn-Shimony-Holt inequality. Most importantly, the violation remains when considering typical detection efficiencies and losses due to required propagation distances.Comment: 21 pages, 5 figures, 3 table, to appear in Nature Com

Moderate and heavy metabolic stress interval training improve arterial stiffness and heart rate dynamics in humans

Traditional continuous aerobic exercise training attenuates age-related increases of arterial stiffness, however, training studies have not determined whether metabolic stress impacts these favourable effects. Twenty untrained healthy participants (n = 11 heavy metabolic stress interval training, n = 9 moderate metabolic stress interval training) completed 6 weeks of moderate or heavy intensity interval training matched for total work and exercise duration. Carotid artery stiffness, blood pressure contour analysis, and linear and non-linear heart rate variability were assessed before and following training. Overall, carotid arterial stiffness was reduced (p  0.05). This study demonstrates the effectiveness of interval training at improving arterial stiffness and autonomic function, however, the metabolic stress was not a mediator of this effect. In addition, these changes were also independent of improvements in aerobic capacity, which were only induced by training that involved a high metabolic stress

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

The Yeast La Related Protein Slf1p Is a Key Activator of Translation during the Oxidative Stress Response

The mechanisms by which RNA-binding proteins control the translation of subsets of mRNAs are not yet clear. Slf1p and Sro9p are atypical-La motif containing proteins which are members of a superfamily of RNA-binding proteins conserved in eukaryotes. RIP-Seq analysis of these two yeast proteins identified overlapping and distinct sets of mRNA targets, including highly translated mRNAs such as those encoding ribosomal proteins. In paralell, transcriptome analysis of slf1Δ and sro9Δ mutant strains indicated altered gene expression in similar functional classes of mRNAs following loss of each factor. The loss of SLF1 had a greater impact on the transcriptome, and in particular, revealed changes in genes involved in the oxidative stress response. slf1Δ cells are more sensitive to oxidants and RIP-Seq analysis of oxidatively stressed cells enriched Slf1p targets encoding antioxidants and other proteins required for oxidant tolerance. To quantify these effects at the protein level, we used label-free mass spectrometry to compare the proteomes of wild-type and slf1Δ strains following oxidative stress. This analysis identified several proteins which are normally induced in response to hydrogen peroxide, but where this increase is attenuated in the slf1Δ mutant. Importantly, a significant number of the mRNAs encoding these targets were also identified as Slf1p-mRNA targets. We show that Slf1p remains associated with the few translating ribosomes following hydrogen peroxide stress and that Slf1p co-immunoprecipitates ribosomes and members of the eIF4E/eIF4G/Pab1p ‘closed loop’ complex suggesting that Slf1p interacts with actively translated mRNAs following stress. Finally, mutational analysis of SLF1 revealed a novel ribosome interacting domain in Slf1p, independent of its RNA binding La-motif. Together, our results indicate that Slf1p mediates a translational response to oxidative stress via mRNA-specific translational control

Dynamic changes in eIF4F-mRNA interactions revealed by global analyses of environmental stress responses

BACKGROUND: Translation factors eIF4E and eIF4G form eIF4F, which interacts with the messenger RNA (mRNA) 5' cap to promote ribosome recruitment and translation initiation. Variations in the association of eIF4F with individual mRNAs likely contribute to differences in translation initiation frequencies between mRNAs. As translation initiation is globally reprogrammed by environmental stresses, we were interested in determining whether eIF4F interactions with individual mRNAs are reprogrammed and how this may contribute to global environmental stress responses. RESULTS: Using a tagged-factor protein capture and RNA-sequencing (RNA-seq) approach, we have assessed how mRNA associations with eIF4E, eIF4G1 and eIF4G2 change globally in response to three defined stresses that each cause a rapid attenuation of protein synthesis: oxidative stress induced by hydrogen peroxide and nutrient stresses caused by amino acid or glucose withdrawal. We find that acute stress leads to dynamic and unexpected changes in eIF4F-mRNA interactions that are shared among each factor and across the stresses imposed. eIF4F-mRNA interactions stabilised by stress are predominantly associated with translational repression, while more actively initiating mRNAs become relatively depleted for eIF4F. Simultaneously, other mRNAs are insulated from these stress-induced changes in eIF4F association. CONCLUSION: Dynamic eIF4F-mRNA interaction changes are part of a coordinated early translational control response shared across environmental stresses. Our data are compatible with a model where multiple mRNA closed-loop complexes form with differing stability. Hence, unexpectedly, in the absence of other stabilising factors, rapid translation initiation on mRNAs correlates with less stable eIF4F interactions

WalkMore: a randomized controlled trial of pedometer-based interventions differing on intensity messages

Pedometer-based programs have elicited increased walking behaviors associated with improvements in blood pressure in sedentary/low active postmenopausal women, a population at increased risk of cardiovascular disease. Such programs typically encourage increasing the volume of physical activity with little regard for its intensity. Recent advances in commercially available pedometer technology now permit tracking of both steps/day and time in moderate (or greater) intensity physical activity on a daily basis. It is not known whether the dual message to increase steps/day while also increasing time spent at higher intensity walking will elicit additional improvements in blood pressure relative to a message to only focus on increasing steps/day. The purpose of this paper is to present the rationale, study design, and protocols employed in WalkMore, a 3-arm 3-month blinded and randomized controlled trial (RCT) designed to compare the effects of two community pedometer-based walking interventions (reflecting these separate and combined messages) relative to a control group on blood pressure in sedentary/low active post-menopausal women, a population at increased risk of cardiovascular disease. 120 sedentary/low active post-menopausal women (45-74 years of age) will be randomly assigned (computer-generated) to 1 of 3 groups: A) 10,000 steps/day (with no guidance on walking intensity/speed/cadence; BASIC intervention, n = 50); B) 10,000 steps/day and at least 30 minutes in moderate intensity (i.e., a cadence of at least 100 steps/min; ENHANCED intervention, n = 50); or a Control group (n = 20). An important strength of the study is the strict control and quantification of the pedometer-based physical activity interventions. The primary outcome is systolic blood pressure. Secondary outcomes include diastolic blood pressure, anthropometric measurements, fasting blood glucose and insulin, flow mediated dilation, gait speed, and accelerometer-determined physical activity and sedentary behavior. This study can make important contributions to our understanding of the relative benefits that walking volume and/or intensity may have on blood pressure in a population at risk of cardiovascular disease. ClinicalTrials.gov Record NCT01519583, January 18, 2012

Genetic contributions to stability and change in intelligence from childhood to old age

Understanding the determinants of healthy mental ageing is a priority for society today1,2. So far, we know that intelligence differences show high stability from childhood to old age3,4 and there are estimates of the genetic contribution to intelligence at different ages5,6. However, attempts to discover whether genetic causes contribute to differences in cognitive ageing have been relatively uninformative7–10. Here we provide an estimate of the genetic and environmental contributions to stability and change in intelligence across most of the human lifetime. We used genome-wide single nucleotide polymorphism (SNP) data from 1,940 unrelated individuals whose intelligence was measured in childhood (age 11 years) and again in old age (age 65, 70 or 79 years)11,12. We use a statistical method that allows genetic (co)variance to be estimated from SNP data on unrelated individuals13–17. We estimate that causal genetic variants in linkage disequilibrium with common SNPs account for 0.24 of the variation in cognitive ability change from childhood to old age. Using bivariate analysis, we estimate a genetic correlation between intelligence at age 11 years and in old age of 0.62. These estimates, derived from rarely available data on lifetime cognitive measures, warrant the search for genetic causes of cognitive stability and change