534 research outputs found

    The epidemiology of teaching and training general practices in England

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    There is no national picture of teaching and training practices or the communities they serve. We aimed to describe the association between general practices’ engagement with education and their characteristics, locality and patients’ health-status and satisfaction. This data linkage study of all English practices calculated odds ratios for teaching and training status and practice, locality and patient variables. Teaching and training practices are larger than practices which do neither (mean list size (SD) 7074 (3736), 10112 (4934), and 5327 (3368) respectively, p < 0.001 and have fewer patients per GP (1932 (951), 1838 (544), and 2117 (1585) respectively, p < 0.001). Their localities have a higher proportion of White British residents (77.99% (24.17), 81.66% (20.81), 73.07% (26.91), p < 0.001). Practices with more GPs (OR 1.21 (95%CI 1.18–1.20)), fewer male GPs (0.45 (0.36–0.55)) and a higher proportion of White British people in their locality (1.30 (1.06–1.60)) were more likely to teach. Practices in rural areas (1.68 (1.43–1.98)), with more GPs (1.22 (1.27–1.39)), more full time equivalent GPs (2.68 (1.64–4.40)), fewer male GPs (0.17 (0.13–0.22)) and a higher proportion of White British people in their locality (1.34 (1.02–1.75)) were more likely to train. Teaching and training practices had higher patient satisfaction (0.293 (0.190, 0.397) and (0.563 (0.442, 0.685)) respectively and quality and outcomes framework scores (0.507 (0.211, 0.804)) and (0.996 (0.650, 1.342)) respectively than those which did not. Educationally engaged practices are unrepresentative in serving less ethnically diverse and (for training practices) less urban environments. Investment is needed to increase the proportion of educational practices in diverse urban localities

    Opportunity cost determines free-operant action initiation latency and predicts apathy

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    Background Apathy, a disabling and poorly understood neuropsychiatric symptom, is characterised by impaired self-initiated behaviour. It has been hypothesised that the opportunity cost of time (OCT) may be a key computational variable linking self-initiated behaviour with motivational status. OCT represents the amount of reward which is foregone per second if no action is taken. Using a novel behavioural task and computational modelling, we investigated the relationship between OCT, self-initiation and apathy. We predicted that higher OCT would engender shorter action latencies, and that individuals with greater sensitivity to OCT would have higher behavioural apathy. Methods We modulated the OCT in a novel task called the 'Fisherman Game', Participants freely chose when to self-initiate actions to either collect rewards, or on occasion, to complete non-rewarding actions. We measured the relationship between action latencies, OCT and apathy for each participant across two independent non-clinical studies, one under laboratory conditions (n = 21) and one online (n = 90). 'Average-reward' reinforcement learning was used to model our data. We replicated our findings across both studies. Results We show that the latency of self-initiation is driven by changes in the OCT. Furthermore, we demonstrate, for the first time, that participants with higher apathy showed greater sensitivity to changes in OCT in younger adults. Our model shows that apathetic individuals experienced greatest change in subjective OCT during our task as a consequence of being more sensitive to rewards. Conclusions Our results suggest that OCT is an important variable for determining free-operant action initiation and understanding apathy

    Gene expression and matrix turnover in overused and damaged tendons

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    Chronic, painful conditions affecting tendons, frequently known as tendinopathy, are very common types of sporting injury. The tendon extracellular matrix is substantially altered in tendinopathy, and these changes are thought to precede and underlie the clinical condition. The tendon cell response to repeated minor injuries or “overuse” is thought to be a major factor in the development of tendinopathy. Changes in matrix turnover may also be effected by the cellular response to physical load, altering the balance of matrix turnover and changing the structure and composition of the tendon. Matrix turnover is relatively high in tendons exposed to high mechanical demands, such as the supraspinatus and Achilles, and this is thought to represent either a repair or tissue maintenance function. Metalloproteinases are a large family of enzymes capable of degrading all of the tendon matrix components, and these are thought to play a major role in the degradation of matrix during development, adaptation and repair. It is proposed that some metalloproteinase enzymes are required for the health of the tendon, and others may be damaging, leading to degeneration of the tissue. Further research is required to investigate how these enzyme activities are regulated in tendon and altered in tendinopathy. A profile of all the metalloproteinases expressed and active in healthy and degenerate tendon is required and may lead to the development of new drug therapies for these common and debilitating sports injuries

    Breakdown of the adiabatic limit in low dimensional gapless systems

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    It is generally believed that a generic system can be reversibly transformed from one state into another by sufficiently slow change of parameters. A standard argument favoring this assertion is based on a possibility to expand the energy or the entropy of the system into the Taylor series in the ramp speed. Here we show that this argumentation is only valid in high enough dimensions and can break down in low-dimensional gapless systems. We identify three generic regimes of a system response to a slow ramp: (A) mean-field, (B) non-analytic, and (C) non-adiabatic. In the last regime the limits of the ramp speed going to zero and the system size going to infinity do not commute and the adiabatic process does not exist in the thermodynamic limit. We support our results by numerical simulations. Our findings can be relevant to condensed-matter, atomic physics, quantum computing, quantum optics, cosmology and others.Comment: 11 pages, 5 figures, to appear in Nature Physics (originally submitted version

    Tendinopathy—from basic science to treatment

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    Chronic tendon pathology (tendinopathy), although common, is difficult to treat. Tendons possess a highly organized fibrillar matrix, consisting of type I collagen and various 'minor' collagens, proteoglycans and glycoproteins. The tendon matrix is maintained by the resident tenocytes, and there is evidence of a continuous process of matrix remodeling, although the rate of turnover varies at different sites. A change in remodeling activity is associated with the onset of tendinopathy. Major molecular changes include increased expression of type III collagen, fibronectin, tenascin C, aggrecan and biglycan. These changes are consistent with repair, but they might also be an adaptive response to changes in mechanical loading. Repeated minor strain is thought to be the major precipitating factor in tendinopathy, although further work is required to determine whether it is mechanical overstimulation or understimulation that leads to the change in tenocyte activity. Metalloproteinase enzymes have an important role in the tendon matrix, being responsible for the degradation of collagen and proteoglycan in both healthy patients and those with disease. Metalloproteinases that show increased expression in painful tendinopathy include ADAM (a disintegrin and metalloproteinase)-12 and MMP (matrix metalloproteinase)-23. The role of these enzymes in tendon pathology is unknown, and further work is required to identify novel and specific molecular targets for therapy

    The Formation and Evolution of the First Massive Black Holes

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    The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

    Upper atmospheres and ionospheres of planets and satellites

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    The upper atmospheres of the planets and their satellites are more directly exposed to sunlight and solar wind particles than the surface or the deeper atmospheric layers. At the altitudes where the associated energy is deposited, the atmospheres may become ionized and are referred to as ionospheres. The details of the photon and particle interactions with the upper atmosphere depend strongly on whether the object has anintrinsic magnetic field that may channel the precipitating particles into the atmosphere or drive the atmospheric gas out to space. Important implications of these interactions include atmospheric loss over diverse timescales, photochemistry and the formation of aerosols, which affect the evolution, composition and remote sensing of the planets (satellites). The upper atmosphere connects the planet (satellite) bulk composition to the near-planet (-satellite) environment. Understanding the relevant physics and chemistry provides insight to the past and future conditions of these objects, which is critical for understanding their evolution. This chapter introduces the basic concepts of upper atmospheres and ionospheres in our solar system, and discusses aspects of their neutral and ion composition, wind dynamics and energy budget. This knowledge is key to putting in context the observations of upper atmospheres and haze on exoplanets, and to devise a theory that explains exoplanet demographics.Comment: Invited Revie

    The Formation of the First Massive Black Holes

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    Supermassive black holes (SMBHs) are common in local galactic nuclei, and SMBHs as massive as several billion solar masses already exist at redshift z=6. These earliest SMBHs may grow by the combination of radiation-pressure-limited accretion and mergers of stellar-mass seed BHs, left behind by the first generation of metal-free stars, or may be formed by more rapid direct collapse of gas in rare special environments where dense gas can accumulate without first fragmenting into stars. This chapter offers a review of these two competing scenarios, as well as some more exotic alternative ideas. It also briefly discusses how the different models may be distinguished in the future by observations with JWST, (e)LISA and other instruments.Comment: 47 pages with 306 references; this review is a chapter in "The First Galaxies - Theoretical Predictions and Observational Clues", Springer Astrophysics and Space Science Library, Eds. T. Wiklind, V. Bromm & B. Mobasher, in pres

    The taxonomic name resolution service : an online tool for automated standardization of plant names

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    © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Bioinformatics 14 (2013): 16, doi:10.1186/1471-2105-14-16.The digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this ‘names problem’ has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science. The TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets. We show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ webcite and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/ webcite.BJE was supported by NSF grant DBI 0850373 and TR by CSIRO Marine and Atmospheric Research, Australia,. BB and BJE acknowledge early financial support from Conservation International and TEAM who funded the development of early prototypes of taxonomic name resolution. The iPlant Collaborative (http://www.iplantcollaborative.org) is funded by a grant from the National Science Foundation (#DBI-0735191)
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