586 research outputs found

    Too close for comfort: spatial patterns in acorn barnacle populations

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    Spatial patterns in aggregations form as a result of the interplay between costs and benefits experienced by individuals. Such self-organisation of aggregations can be explained using a zonal model in which a short-range zone of repulsion and longer-range zone of attraction surrounding individuals leads to emergent pattern properties. The signal of these processes can be detected using spatial pattern analyses. Furthermore, in sessile organisms, post-settlement mortality reveals the relative costs and benefits of positions within the aggregation. Acorn barnacles are known to require contact with conspecifics for reproduction and are therefore believed to aggregate for this purpose; isolated individuals may also be more susceptible to abiotic stress and predation. At short distances, however, competition for space and resources is likely to occur. In this study spatial patterns of barnacles (Semibalanus balanoides L.) were analysed using pair-correlation functions. Individuals were dispersed at distances below 0.30 cm, but peak relative density occurred at a distance of 0.36 cm from conspecifics. This is much closer than required for reproductive access, implying a strong aggregative drive, up to the point of physical contact with neighbours. Nevertheless, analysis of dead barnacles illustrated that such proximity carries a cost as barnacles with many neighbours were more likely to have died. The inferences obtained from these patterns are that barnacles aggregate as closely as they can, and that local neighbourhood competition is a powerful determinant of mortality. These processes give rise to the observed pattern properties

    Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: a secondary analysis of a multicentre, prospective, observational cohort

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    BACKGROUND: Idiopathic pulmonary fibrosis is a progressive fibrotic lung disease with a variable clinical trajectory. Decline in forced vital capacity (FVC) is the main indicator of progression; however, missingness prevents long-term analysis of patterns in lung function. We aimed to identify distinct clusters of lung function trajectory among patients with idiopathic pulmonary fibrosis using machine learning techniques. METHODS: We did a secondary analysis of longitudinal data on FVC collected from a cohort of patients with idiopathic pulmonary fibrosis from the PROFILE study; a multicentre, prospective, observational cohort study. We evaluated the imputation performance of conventional and machine learning techniques to impute missing data and then analysed the fully imputed dataset by unsupervised clustering using self-organising maps. We compared anthropometric features, genomic associations, serum biomarkers, and clinical outcomes between clusters. We also performed a replication of the analysis on data from a cohort of patients with idiopathic pulmonary fibrosis from an independent dataset, obtained from the Chicago Consortium. FINDINGS: 415 (71%) of 581 participants recruited into the PROFILE study were eligible for further analysis. An unsupervised machine learning algorithm had the lowest imputation error among tested methods, and self-organising maps identified four distinct clusters (1-4), which was confirmed by sensitivity analysis. Cluster 1 comprised 140 (34%) participants and was associated with a disease trajectory showing a linear decline in FVC over 3 years. Cluster 2 comprised 100 (24%) participants and was associated with a trajectory showing an initial improvement in FVC before subsequently decreasing. Cluster 3 comprised 113 (27%) participants and was associated with a trajectory showing an initial decline in FVC before subsequent stabilisation. Cluster 4 comprised 62 (15%) participants and was associated with a trajectory showing stable lung function. Median survival was shortest in cluster 1 (2·87 years [IQR 2·29-3·40]) and cluster 3 (2·23 years [1·75-3·84]), followed by cluster 2 (4·74 years [3·96-5·73]), and was longest in cluster 4 (5·56 years [5·18-6·62]). Baseline FEV1 to FVC ratio and concentrations of the biomarker SP-D were significantly higher in clusters 1 and 3. Similar lung function clusters with some shared anthropometric features were identified in the replication cohort. INTERPRETATION: Using a data-driven unsupervised approach, we identified four clusters of lung function trajectory with distinct clinical and biochemical features. Enriching or stratifying longitudinal spirometric data into clusters might optimise evaluation of intervention efficacy during clinical trials and patient management. FUNDING: National Institute for Health and Care Research, Medical Research Council, and GlaxoSmithKline

    Loss of ELK1 has differential effects on age-dependent organ fibrosis

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    ETS domain-containing protein-1 (ELK1) is a transcription factor important in regulating αvβ6 integrin expression. αvβ6 integrins activate the profibrotic cytokine Transforming Growth Factor β1 (TGFβ1) and are increased in the alveolar epithelium in idiopathic pulmonary fibrosis (IPF). IPF is a disease associated with aging and therefore we hypothesised that aged animals lacking Elk1 globally would develop spontaneous fibrosis in organs where αvβ6 mediated TGFβ activation has been implicated. Here we identify that Elk1-knockout (Elk1−/0) mice aged to one year developed spontaneous fibrosis in the absence of injury in both the lung and the liver but not in the heart or kidneys. The lungs of Elk1−/0 aged mice demonstrated increased collagen deposition, in particular collagen 3α1, located in small fibrotic foci and thickened alveolar walls. Despite the liver having relatively low global levels of ELK1 expression, Elk1−/0 animals developed hepatosteatosis and fibrosis. The loss of Elk1 also had differential effects on Itgb1, Itgb5 and Itgb6 expression in the four organs potentially explaining the phenotypic differences in these organs. To understand the potential causes of reduced ELK1 in human disease we exposed human lung epithelial cells and murine lung slices to cigarette smoke extract, which lead to reduced ELK1 expression andmay explain the loss of ELK1 in human disease. These data support a fundamental role for ELK1 in protecting against the development of progressive fibrosis via transcriptional regulation of beta integrin subunit genes, and demonstrate that loss of ELK1 can be caused by cigarette smoke

    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

    A cross-sectional study of the number and frequency of terms used to refer to knowledge translation in a body of health literature in 2006: a Tower of Babel?

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    <p/> <p>Background</p> <p>The study of implementing research findings into practice is rapidly growing and has acquired many competing names (<it>e.g</it>., dissemination, uptake, utilization, translation) and contributing disciplines. The use of multiple terms across disciplines pose barriers to communication and progress for applying research findings. We sought to establish an inventory of terms describing this field and how often authors use them in a collection of health literature published in 2006.</p> <p>Methods</p> <p>We refer to this field as knowledge translation (KT). Terms describing aspects of KT and their definitions were collected from literature, the internet, reports, textbooks, and contact with experts. We compiled a database of KT and other articles by reading 12 healthcare journals representing multiple disciplines. All articles published in these journals in 2006 were categorized as being KT or not. The KT articles (all KT) were further categorized, if possible, for whether they described KT projects or implementations (KT application articles), or presented the theoretical basis, models, tools, methods, or techniques of KT (KT theory articles). Accuracy was checked using duplicate reading. Custom designed software determined how often KT terms were used in the titles and abstracts of articles categorized as being KT.</p> <p>Results</p> <p>A total of 2,603 articles were assessed, and 581 were identified as KT articles. Of these, 201 described KT applications, and 153 included KT theory. Of the 100 KT terms collected, 46 were used by the authors in the titles or abstracts of articles categorized as being KT. For all 581 KT articles, eight terms or term variations used by authors were highly discriminating for separating KT and non-KT articles (p < 0.001): implementation, adoption, quality improvement, dissemination, complex intervention (with multiple endings), implementation (within three words of) research, and complex intervention. More KT terms were associated with KT application articles (n = 13) and KT theory articles (n = 18).</p> <p>Conclusions</p> <p>We collected 100 terms describing KT research. Authors used 46 of them in titles and abstracts of KT articles. Of these, approximately half discriminated between KT and non-KT articles. Thus, the need for consolidation and consistent use of fewer terms related to KT research is evident.</p

    Balancing with Vibration: A Prelude for “Drift and Act” Balance Control

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    Stick balancing at the fingertip is a powerful paradigm for the study of the control of human balance. Here we show that the mean stick balancing time is increased by about two-fold when a subject stands on a vibrating platform that produces vertical vibrations at the fingertip (0.001 m, 15–50 Hz). High speed motion capture measurements in three dimensions demonstrate that vibration does not shorten the neural latency for stick balancing or change the distribution of the changes in speed made by the fingertip during stick balancing, but does decrease the amplitude of the fluctuations in the relative positions of the fingertip and the tip of the stick in the horizontal plane, A(x,y). The findings are interpreted in terms of a time-delayed “drift and act” control mechanism in which controlling movements are made only when controlled variables exceed a threshold, i.e. the stick survival time measures the time to cross a threshold. The amplitude of the oscillations produced by this mechanism can be decreased by parametric excitation. It is shown that a plot of the logarithm of the vibration-induced increase in stick balancing skill, a measure of the mean first passage time, versus the standard deviation of the A(x,y) fluctuations, a measure of the distance to the threshold, is linear as expected for the times to cross a threshold in a stochastic dynamical system. These observations suggest that the balanced state represents a complex time–dependent state which is situated in a basin of attraction that is of the same order of size. The fact that vibration amplitude can benefit balance control raises the possibility of minimizing risk of falling through appropriate changes in the design of footwear and roughness of the walking surfaces

    Diabetes-Specific Nutrition Algorithm: A Transcultural Program to Optimize Diabetes and Prediabetes Care

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    Type 2 diabetes (T2D) and prediabetes have a major global impact through high disease prevalence, significant downstream pathophysiologic effects, and enormous financial liabilities. To mitigate this disease burden, interventions of proven effectiveness must be used. Evidence shows that nutrition therapy improves glycemic control and reduces the risks of diabetes and its complications. Accordingly, diabetes-specific nutrition therapy should be incorporated into comprehensive patient management programs. Evidence-based recommendations for healthy lifestyles that include healthy eating can be found in clinical practice guidelines (CPGs) from professional medical organizations. To enable broad implementation of these guidelines, recommendations must be reconstructed to account for cultural differences in lifestyle, food availability, and genetic factors. To begin, published CPGs and relevant medical literature were reviewed and evidence ratings applied according to established protocols for guidelines. From this information, an algorithm for the nutritional management of people with T2D and prediabetes was created. Subsequently, algorithm nodes were populated with transcultural attributes to guide decisions. The resultant transcultural diabetes-specific nutrition algorithm (tDNA) was simplified and optimized for global implementation and validation according to current standards for CPG development and cultural adaptation. Thus, the tDNA is a tool to facilitate the delivery of nutrition therapy to patients with T2D and prediabetes in a variety of cultures and geographic locations. It is anticipated that this novel approach can reduce the burden of diabetes, improve quality of life, and save lives. The specific Southeast Asian and Asian Indian tDNA versions can be found in companion articles in this issue of Current Diabetes Reports
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