Whose Game Are We Playing? Children's Perspectives on Organised Team Sports in New Zealand

Background The childhood years are highlighted as a crucial time when ongoing participation in physical activity can be nurtured and maintained. The nurturing of a child’s proclivity to participate in organised sport normally falls into the domain of adults and both parents and coaches have been identified as key influences in children’s enjoyment of sport. However, some negative perceptions exist about the role played by both parents and coaches, and concerns are commonly expressed in the media about excessive parental and coach touchline behaviour. Objectives Although children’s perspectives are increasingly being acknowledged as legitimate and valuable, it would appear from the social science literature that young children are still marginalised as active participants in areas of health-related research. The primary objective of this study was to give voice to children’s views of sport, and in particular to examine how adult behaviours affected children’s enjoyment of sport. Methods A cross-sectional study that utilised eight focus group interviews with a total of 32 children (aged 6 to 11 years) in the Greater Auckland area of New Zealand. This paper presents a Foucauldian discourse analysis of children’s views relating to their sporting experiences. Results The dominance of a sport as competition discourse would appear to serve the needs more of coaches and parents than the needs of children. Coaches who appear to be firmly positioned within a competitive discourse use their power to support coaching practices that clash with the guidelines and resources provided for them by their sporting bodies. Conclusion A discursive analysis shows that many children may be exposed to discursive practices that are not conducive to a child-centred sporting environment. There is pressure on children, through disciplinary measures, to conform to the normative behaviours associated with a dominant competitive discourse in sport

Evolution of associative learning in chemical networks

Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ’memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells

Differential effects of bile acids on the postprandial secretion of gut hormones: a randomized crossover study.

Bile acids (BA) regulate postprandial metabolism directly and indirectly by affecting the secretion of gut hormones like glucagon-like peptide-1 (GLP-1). The postprandial effects of BA on the secretion of other metabolically active hormones are not well understood. The objective of this study was to investigate the effects of oral ursodeoxycholic acid (UDCA) and chenodeoxycholic acid (CDCA) on postprandial secretion of GLP-1, oxyntomodulin (OXM), peptide YY (PYY), glucose-dependent insulinotropic peptide (GIP), glucagon, and ghrelin. Twelve healthy volunteers underwent a mixed meal test 60 min after ingestion of UDCA (12-16 mg/kg), CDCA (13-16 mg/kg), or no BA in a randomized crossover study. Glucose, insulin, GLP-1, OXM, PYY, GIP, glucagon, ghrelin, and fibroblast growth factor 19 were measured prior to BA administration at -60 and 0 min (just prior to mixed meal) and 15, 30, 60, 120, 180, and 240 min after the meal. UDCA and CDCA provoked differential gut hormone responses; UDCA did not have any significant effects, but CDCA provoked significant increases in GLP-1 and OXM and a profound reduction in GIP. CDCA increased fasting GLP-1 and OXM secretion in parallel with an increase in insulin. On the other hand, CDCA reduced postprandial secretion of GIP, with an associated reduction in postprandial insulin secretion. Exogenous CDCA can exert multiple salutary effects on the secretion of gut hormones; if these effects are confirmed in obesity and type 2 diabetes, CDCA may be a potential therapy for these conditions. NEW & NOTEWORTHY: Oral CDCA and UDCA have different effects on gut and pancreatic hormone secretion. A single dose of CDCA increased fasting secretion of the hormones GLP-1 and OXM with an accompanying increase in insulin secretion. CDCA also reduced postprandial GIP secretion, which was associated with reduced insulin. In contrast, UDCA did not change gut hormone secretion fasting or postprandially. Oral CDCA could be beneficial to patients with obesity and diabetes

Estimation of Dietary Iron Bioavailability from Food Iron Intake and Iron Status

Currently there are no satisfactory methods for estimating dietary iron absorption (bioavailability) at a population level, but this is essential for deriving dietary reference values using the factorial approach. The aim of this work was to develop a novel approach for estimating dietary iron absorption using a population sample from a sub-section of the UK National Diet and Nutrition Survey (NDNS). Data were analyzed in 873 subjects from the 2000–2001 adult cohort of the NDNS, for whom both dietary intake data and hematological measures (hemoglobin and serum ferritin (SF) concentrations) were available. There were 495 men aged 19–64 y (mean age 42.7±12.1 y) and 378 pre-menopausal women (mean age 35.7±8.2 y). Individual dietary iron requirements were estimated using the Institute of Medicine calculations. A full probability approach was then applied to estimate the prevalence of dietary intakes that were insufficient to meet the needs of the men and women separately, based on their estimated daily iron intake and a series of absorption values ranging from 1–40%. The prevalence of SF concentrations below selected cut-off values (indicating that absorption was not high enough to maintain iron stores) was derived from individual SF concentrations. An estimate of dietary iron absorption required to maintain specified SF values was then calculated by matching the observed prevalence of insufficiency with the prevalence predicted for the series of absorption estimates. Mean daily dietary iron intakes were 13.5 mg for men and 9.8 mg for women. Mean calculated dietary absorption was 8% in men (50th percentile for SF 85 µg/L) and 17% in women (50th percentile for SF 38 µg/L). At a ferritin level of 45 µg/L estimated absorption was similar in men (14%) and women (13%). This new method can be used to calculate dietary iron absorption at a population level using data describing total iron intake and SF concentration

Early Warning Signals for Critical Transitions: A Generalized Modeling Approach

Critical transitions are sudden, often irreversible, changes that can occur in a large variety of complex systems; signals that warn of critical transitions are therefore highly desirable. We propose a new method for early warning signals that integrates multiple sources of information and data about the system through the framework of a generalized model. We demonstrate our proposed approach through several examples, including a previously published fisheries model. We regard our method as complementary to existing early warning signals, taking an approach of intermediate complexity between model-free approaches and fully parameterized simulations. One potential advantage of our approach is that, under appropriate conditions, it may reduce the amount of time series data required for a robust early warning signal

Is health-related quality of life associated with the risk of low-energy wrist fracture: a case-control study

<p>Abstract</p> <p>Background</p> <p>Some risk factors for low-energy wrist fracture have been identified. However, self-reported measures such as health-related quality of life (HRQOL) have not been examined as potential risk factors for wrist fracture. The aims of this study were to compare HRQOL prior to a low-energy wrist fracture in elderly patients (≥ 50 years) with HRQOL in age- and sex-matched controls, and to explore the association between HRQOL and wrist fracture after adjusting for known risk factors for fracture such as age, weight, osteoporosis and falls.</p> <p>Methods</p> <p>Patients with a low-energy wrist fracture (n = 181) and age- and sex-matched controls (n = 181) were studied. Shortly after fracture (median 10 days), patients assessed their HRQOL before fracture using the Short Form 36 (SF-36). Statistical tests included <it>t </it>tests and multivariate logistic regression analysis.</p> <p>Results</p> <p>Several dimensions of HRQOL were significantly associated with wrist fracture. The direction of the associations with wrist fracture varied between the different sub-dimensions of the SF-36. After controlling for demographic and clinical variables, higher scores on <it>general health </it>(odds ratio (OR) = 1.31, 95% confidence interval (CI) = 1.10–1.56), <it>bodily pain </it>(OR = 1.18, 95% CI = 1.03–1.34) and <it>mental health </it>(OR = 1.39, 95% CI = 1.09–1.79) were related to an increased chance of being a wrist fracture patient rather than a control. In contrast, higher scores on <it>physical role limitation </it>(OR = 0.87, 95% CI = 0.79–0.95) and <it>social function </it>(OR = 0.65, 95% CI 0.53–0.80) decreased this chance. Significant associations with wrist fracture were also found for living alone (OR = 1.91, 95% CI 1.07–3.4), low body mass index (BMI) (OR = 0.92, 95% CI 0.86–0.98), osteoporosis (OR = 3.30, 95% CI 1.67–6.50) and previous falls (OR = 2.01, 95% CI 1.16–3.49).</p> <p>Conclusion</p> <p>Wrist fracture patients perceive themselves to be as healthy as the controls before fracture. Our data indicate that patients with favourable and unfavourable HRQOL measures may be at increased risk of wrist fracture.</p

Current and emerging treatment of osteoporosis

The goal of treating a patient with recent fragility fracture should not only be to treat the patient in the acute phase but also to prevent further fractures. Interventions to increase bone mass to preventing further fragility fractures can be classified as non-pharmacological and pharmacological. All European and international guidelines base the need for treatment, not on the diagnosis of osteoporosis (based on the T-score), but on the risk of fracture, which is strongly influenced by the presence of a fragility fracture, especially vertebral or femoral fractures. Before treatment, it is important to make a differential diagnosis between primary and secondary osteoporosis because anti-osteoporotic drug treatment would be useless if the primary illness causing osteoporosis is not treated too. Some studies show that anti-osteoporotic drugs are frequently interrupted within 1 month of their prescription; this happens not so much due to the occurrence of adverse events but mostly because patients have not been sufficiently informed about the importance of taking the drug and because are not receiving personalised treatment. All data confirm that, in older people, vitamin D deficiency is highly prevalent and calcium intake is often not adequate. So, osteoporosis guidelines recommend calcium and vitamin D for all patients in association with antiosteoporotic therapy. We have many drugs for the treatment of patients at high risk of fracture, but we should use drugs based on evidence of their efficacy and safety in older-age subgroups, provided by targeted studies or extrapolated data. In this chapter, we describe efficacy, route of administration, adverse events and recent technical remarks of current antiresorptive and anabolic osteoporosis therapies. Furthermore, we describe emerging therapies, such as Abaloparatide and Romosozumab

Accelerated Profile HMM Searches

Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the “multiple segment Viterbi” (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call “sparse rescaling”. These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches