974 research outputs found

    Moving from evidence-based medicine to evidence-based health.

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    While evidence-based medicine (EBM) has advanced medical practice, the health care system has been inconsistent in translating EBM into improvements in health. Disparities in health and health care play out through patients' limited ability to incorporate the advances of EBM into their daily lives. Assisting patients to self-manage their chronic conditions and paying attention to unhealthy community factors could be added to EBM to create a broader paradigm of evidence-based health. A perspective of evidence-based health may encourage physicians to consider their role in upstream efforts to combat socially patterned chronic disease

    Interaction and filling induced quantum phases of dual Mott insulators of bosons and fermions

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    Many-body effects are at the very heart of diverse phenomena found in condensed-matter physics. One striking example is the Mott insulator phase where conductivity is suppressed as a result of a strong repulsive interaction. Advances in cold atom physics have led to the realization of the Mott insulating phases of atoms in an optical lattice, mimicking the corresponding condensed matter systems. Here, we explore an exotic strongly-correlated system of Interacting Dual Mott Insulators of bosons and fermions. We reveal that an inter-species interaction between bosons and fermions drastically modifies each Mott insulator, causing effects that include melting, generation of composite particles, an anti-correlated phase, and complete phase-separation. Comparisons between the experimental results and numerical simulations indicate intrinsic adiabatic heating and cooling for the attractively and repulsively interacting dual Mott Insulators, respectively

    Evaluation of machine-learning methods for ligand-based virtual screening

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    Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed

    Composite structural motifs of binding sites for delineating biological functions of proteins

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    Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs which represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.Comment: 34 pages, 7 figure

    The implications of the United Nations Paris Agreement on climate change for globally significant biodiversity areas

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    Climate change is already affecting species and their distributions. Distributional range changes have occurred and are projected to intensify for many widespread plants and animals, creating associated risks to many ecosystems. Here, we estimate the climate change-related risks to the species in globally significant biodiversity conservation areas over a range of climate scenarios, assessing their value as climate refugia. In particular, we quantify the aggregated benefit of countries’ emission reduction pledges (Intended Nationally Determined Contributions and Nationally Determined Contributions under the Paris Agreement), and also of further constraining global warming to 2 °C above pre-industrial levels, against an unmitigated scenario of 4.5 °C warming. We also quantify the contribution that can be made by using smart spatial conservation planning to facilitate some levels of autonomous (i.e. natural) adaptation to climate change by dispersal. We find that without mitigation, on average 33% of each conservation area can act as climate refugium (or 18% if species are unable to disperse), whereas if warming is constrained to 2 °C, the average area of climate refuges doubles to 67% of each conservation area (or, without dispersal, more than doubles to 56% of each area). If the country pledges are fulfilled, an intermediate estimate of 47–52% (or 31–38%, without dispersal) is obtained. We conclude that the Nationally Determined Contributions alone have important but limited benefits for biodiversity conservation, with larger benefits accruing if warming is constrained to 2 °C. Greater benefits would result if warming was constrained to well below 2 °C as set out in the Paris Agreement

    The Rewiring of Ubiquitination Targets in a Pathogenic Yeast Promotes Metabolic Flexibility, Host Colonization and Virulence

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    Funding: This work was funded by the European Research Council [http://erc.europa.eu/], AJPB (STRIFE Advanced Grant; C-2009-AdG-249793). The work was also supported by: the Wellcome Trust [www.wellcome.ac.uk], AJPB (080088, 097377); the UK Biotechnology and Biological Research Council [www.bbsrc.ac.uk], AJPB (BB/F00513X/1, BB/K017365/1); the CNPq-Brazil [http://cnpq.br], GMA (Science without Borders fellowship 202976/2014-9); and the National Centre for the Replacement, Refinement and Reduction of Animals in Research [www.nc3rs.org.uk], DMM (NC/K000306/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments We thank Dr. Elizabeth Johnson (Mycology Reference Laboratory, Bristol) for providing strains, and the Aberdeen Proteomics facility for the biotyping of S. cerevisiae clinical isolates, and to Euroscarf for providing S. cerevisiae strains and plasmids. We are grateful to our Microscopy Facility in the Institute of Medical Sciences for their expert help with the electron microscopy, and to our friends in the Aberdeen Fungal Group for insightful discussions.Peer reviewedPublisher PD

    Exertional rhabdomyolysis in a 21-year-old, healthy female after performing three sets of the biceps curl exercise to failure with 30% 1RM: A case report

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    Background: The optimal resistance training program to elicit muscle hypertrophy has been consistently debated and researched. Although 3 sets of 10 repetitions at 70-80% of the 1-repetition maximum (1RM) is widely recommended, recent studies have shown that low-load (~30% 1RM), high-repetition (3 sets of 30-40 repetitions) resistance training can elicit similar muscular hypertrophy. Therefore, this type of resistance training has gained popularity, perhaps because less weight is lifted for a longer duration. In the process of testing this hypothesis in a research study in our laboratory, a subject diagnosed with exertional rhabdomyolysis after completing a single resistance training session that involved 3 sets to failure at 30% 1RM. Exertional rhabdomyolysis is a condition characterized by the excessive breakdown of striated skeletal muscle that releases proteins from the muscle cell, particularly myoglobin, into the blood that can be toxic to the kidneys and is a significant health concern. Case Report: Reviewed were the events leading up to and throughout the diagnosis of exertional rhabdomyolysis in a healthy, recreationally-trained, 21-year-old female that was enrolled in a study that compared the acute effects of the traditional high-load, low-repetition versus low-load, high-repetition resistance training. The subject completed a total of 143 repetitions of the bilateral dumbbell bicep curl exercise. Three days post-exercise she reported excessive muscle soreness and swelling and sought medical attention. She was briefly hospitalized and then discharged with instructions to take acetaminophen for soreness, drink plenty of water, rest, and monitor her creatine kinase (CK) concentrations. Changes in the subject’s CK concentrations, ultrasound-determined muscle thickness and echo intensity were monitored over a 14-day period are reported. Discussion: This case illustrates the potential risk of developing exertional rhabdomyolysis after a low-load, high-repetition resistance training session in healthy, young, recreationally-trained women. The fact that exertional rhabdomyolysis is a possible outcome is enough to warrant caution when prescribing this type of resistance exercise

    The deuteron: structure and form factors

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    A brief review of the history of the discovery of the deuteron in provided. The current status of both experiment and theory for the elastic electron scattering is then presented.Comment: 80 pages, 33 figures, submited to Advances in Nuclear Physic

    The inevitable QSAR renaissance

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    QSAR approaches, including recent advances in 3D-QSAR, are advantageous during the lead optimization phase of drug discovery and complementary with bioinformatics and growing data accessibility. Hints for future QSAR practitioners are also offered

    Accessible quantification of multiparticle entanglement

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    Entanglement is a key ingredient for quantum technologies and a fundamental signature of quantumness in a broad range of phenomena encompassing many-body physics, thermodynamics, cosmology and life sciences. For arbitrary multiparticle systems, entanglement quantification typically involves nontrivial optimisation problems, and it may require demanding tomographical techniques. Here, we develop an experimentally feasible approach to the evaluation of geometric measures of multiparticle entanglement. Our framework provides analytical results for particular classes of mixed states of N qubits, and computable lower bounds to global, partial, or genuine multiparticle entanglement of any general state. For global and partial entanglement, useful bounds are obtained with minimum effort, requiring local measurements in just three settings for any N. For genuine entanglement, a number of measurements scaling linearly with N are required. We demonstrate the power of our approach to estimate and quantify different types of multiparticle entanglement in a variety of N-qubit states useful for uantum information processing and recently engineered in laboratories with quantum optics and trapped ion setups
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