693 research outputs found

    Designing Engaging Learning Experiences in Programming

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    In this paper we describe work to investigate the creation of engaging programming learning experiences. Background research informed the design of four fieldwork studies to explore how programming tasks could be framed to motivate learners. Our empirical findings from these four field studies are summarized here, with a particular focus upon one – Whack a Mole – which compared the use of a physical interface with the use of a screen-based equivalent interface to obtain insights into what made for an engaging learning experience. Emotions reported by two sets of participant undergraduate students were analyzed, identifying the links between the emotions experienced during programming and their origin. Evidence was collected of the very positive emotions experienced by learners programming with a physical interface (Arduino) in comparison with a similar program developed using a screen-based equivalent interface. A follow-up study provided further evidence of the motivation of personalized design of programming tangible physical artefacts. Collating all the evidence led to the design of a set of ‘Learning Dimensions’ which may provide educators with insights to support key design decisions for the creation of engaging programming learning experiences

    Spinoza

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    "Spinoza", second edition. Encyclopedia entry for the Springer Encyclopedia of EM Phil and the Sciences, ed. D. Jalobeanu and C. T. Wolfe

    Glucocorticoids regulate AKR1D1 activity in human liver in vitro and in vivo

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    Steroid 5β-reductase (AKR1D1) is highly expressed in human liver where it inactivates endogenous glucocorticoids and catalyses an important step in bile acid synthesis. Endogenous and synthetic glucocorticoids are potent regulators of metabolic phenotype and play a crucial role in hepatic glucose metabolism. However, the potential of synthetic glucocorticoids to be metabolised by AKR1D1 as well as to regulate its expression and activity has not been investigated. The impact of glucocorticoids on AKR1D1 activity was assessed in human liver HepG2 and Huh7 cells; AKR1D1 expression was assessed by qPCR and Western blotting. Genetic manipulation of AKR1D1 expression was conducted in HepG2 and Huh7 cells and metabolic assessments were made using qPCR. Urinary steroid metabolite profiling in healthy volunteers was performed pre- and post-dexamethasone treatment, using gas chromatography-mass spectrometry. AKR1D1 metabolised endogenous cortisol, but cleared prednisolone and dexamethasone less efficiently. In vitro and in vivo, dexamethasone decreased AKR1D1 expression and activity, further limiting glucocorticoid clearance and augmenting action. Dexamethasone enhanced gluconeogenic and glycogen synthesis gene expression in liver cell models and these changes were mirrored by genetic knockdown of AKR1D1 expression. The effects of AKR1D1 knockdown were mediated through multiple nuclear hormone receptors, including the glucocorticoid, pregnane X and farnesoid X receptors. Glucocorticoids down-regulate AKR1D1 expression and activity and thereby reduce glucocorticoid clearance. In addition, AKR1D1 down-regulation alters the activation of multiple nuclear hormone receptors to drive changes in gluconeogenic and glycogen synthesis gene expression profiles, which may exacerbate the adverse impact of exogenous glucocorticoids

    Radiative Transfer for Exoplanet Atmospheres

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    Remote sensing of the atmospheres of distant worlds motivates a firm understanding of radiative transfer. In this review, we provide a pedagogical cookbook that describes the principal ingredients needed to perform a radiative transfer calculation and predict the spectrum of an exoplanet atmosphere, including solving the radiative transfer equation, calculating opacities (and chemistry), iterating for radiative equilibrium (or not), and adapting the output of the calculations to the astronomical observations. A review of the state of the art is performed, focusing on selected milestone papers. Outstanding issues, including the need to understand aerosols or clouds and elucidating the assumptions and caveats behind inversion methods, are discussed. A checklist is provided to assist referees/reviewers in their scrutiny of works involving radiative transfer. A table summarizing the methodology employed by past studies is provided.Comment: 7 pages, no figures, 1 table. Filled in missing information in references, main text unchange

    Using genetics to understand the causal influence of higher BMI on depression

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     This is the final version. Available on open access from OUP via the DOI in this record.Background: Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women. Methods: We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to 'uncouple' the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways. Results: Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P < 0.05. Using a metabolically favourable adiposity genetic risk score, and meta-analysing data from the UK biobank and PGC, a genetically determined 1 SD higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals (OR: 1.26, 95% CI: 1.06, 1.50], P = 0.010), but with weaker statistical confidence. Conclusions: Higher BMI, with and without its adverse metabolic consequences, is likely to have a causal role in determining the likelihood of an individual developing depression.Diabetes Research and Wellness FoundationAustralian Research Training ProgramMedical Research CouncilWellcome TrustEuropean Research CouncilRoyal SocietyGillings Family FoundationDiabetes UKNational Institute for Health Research (NIHR

    Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes

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    This is the final version. Available on open access from Wiley via the DOI in this recordAims: Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes. Methods: We classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non-type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin-containing islets along with multiple insulin-deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data [autoantibodies, type 1 diabetes genetic risk score (T1D-GRS)], and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC-ROC). Results: Diagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D-GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC-ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C-peptide [median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non-type 1 diabetes; P < 0.0001]. Conclusions: Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C-peptide-based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible. Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19–22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6–8 March 2019.Diabetes UKNational Institutes of Health (NIH)National Institute for Health Research (NIHR)JDRFHelmsley Charitable Trus

    Ram pressure feeding super-massive black holes

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    When supermassive black holes at the center of galaxies accrete matter (usually gas), they give rise to highly energetic phenomena named Active Galactic Nuclei (AGN). A number of physical processes have been proposed to account for the funneling of gas towards the galaxy centers to feed the AGN. There are also several physical processes that can strip gas from a galaxy, and one of them is ram pressure stripping in galaxy clusters due to the hot and dense gas filling the space between galaxies. We report the discovery of a strong connection between severe ram pressure stripping and the presence of AGN activity. Searching in galaxy clusters at low redshift, we have selected the most extreme examples of jellyfish galaxies, which are galaxies with long tentacles of material extending for dozens of kpc beyond the galaxy disk. Using the MUSE spectrograph on the ESO Very Large Telescope, we find that 6 out of the 7 galaxies of this sample host a central AGN, and two of them also have galactic-scale AGN ionization cones. The high incidence of AGN among the most striking jellyfishes may be due to ram pressure causing gas to flow towards the center and triggering the AGN activity, or to an enhancement of the stripping caused by AGN energy injection, or both. Our analysis of the galaxy position and velocity relative to the cluster strongly supports the first hypothesis, and puts forward ram pressure as another, yet unforeseen, possible mechanism for feeding the central supermassive black hole with gas.Comment: published in Nature, Vol.548, Number 7667, pag.30

    Measuring the psychosocial burden in women with low-grade abnormal cervical cytology in the TOMBOLA trial: psychometric properties of the Process and Outcome Specific Measure (POSM)

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    Background There is a need for an instrument to measure the psychosocial burden of receiving an abnormal cervical cytology result which can be used regardless of the clinical management women receive. Methods 3331 women completed the POSM as part of baseline psychosocial assessment in a trial of management of low grade cervical cytological abnormalities. Factor analysis and reliability assessment of the POSM were conducted. Results Two factors were extracted from the POSM: Factor 1, containing items related to worry; and Factor 2 containing items relating to satisfaction with information and support received and change in the way women felt about themselves. Factor 1 had good reliability (Cronbach’s alpha 0.769), however reliability of the Factor 2 was poorer (0.482). Data collected at four subsequent time points demonstrated that the factor structure was stable over time. Conclusion This study demonstrates the presence and reliability of a scale measuring worries within the POSM. This analysis will inform its future use in this population and in other related contexts
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