291 research outputs found

    Model based dynamics analysis in live cell microtubule images

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    Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data. Results: In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior. Conclusion: Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior

    SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES). IV. Spatial Clustering and Halo Masses of Submillimeter Galaxies

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    We analyze an extremely deep 450 μm image (1σ = 0.56 mJy beam−1) of a sime300 arcmin2 area in the CANDELS/COSMOS field as part of the Sub-millimeter Common User Bolometric Array-2 Ultra Deep Imaging EAO Survey. We select a robust (signal-to-noise ratio ≥4) and flux-limited (≥4 mJy) sample of 164 submillimeter galaxies (SMGs) at 450 μm that have K-band counterparts in the COSMOS2015 catalog identified from radio or mid-infrared imaging. Utilizing this SMG sample and the 4705 K-band-selected non-SMGs that reside within the noise level ≤1 mJy beam−1 region of the 450 μm image as a training set, we develop a machine-learning classifier using K-band magnitude and color–color pairs based on the 13-band photometry available in this field. We apply the trained machine-learning classifier to the wider COSMOS field (1.6 deg2) using the same COSMOS2015 catalog and identify a sample of 6182 SMG candidates with similar colors. The number density, radio and/or mid-infrared detection rates, redshift and stellar-mass distributions, and the stacked 450 μm fluxes of these SMG candidates, from the S2COSMOS observations of the wide field, agree with the measurements made in the much smaller CANDELS field, supporting the effectiveness of the classifier. Using this SMG candidate sample, we measure the two-point autocorrelation functions from z = 3 down to z = 0.5. We find that the SMG candidates reside in halos with masses of sime(2.0 ± 0.5) × 1013 h −1 M ☉ across this redshift range. We do not find evidence of downsizing that has been suggested by other recent observational studies

    Heterochronic faecal transplantation boosts gut germinal centres in aged mice

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    Ageing is a complex multifactorial process associated with a plethora of disorders, which contribute significantly to morbidity worldwide. One of the organs significantly affected by age is the gut. Age-dependent changes of the gut-associated microbiome have been linked to increased frailty and systemic inflammation. This change in microbial composition with age occurs in parallel with a decline in function of the gut immune system, however it is not clear if there is a causal link between the two. Here we report that the defective germinal centre reaction in Peyer’s patches of aged mice can be rescued by faecal transfers from younger adults into aged mice and by immunisations with cholera toxin, without affecting germinal centre reactions in peripheral lymph nodes. This demonstrates that the poor germinal centre reaction in aged animals is not irreversible, and that it is possible to improve this response in older individuals by providing appropriate stimuli

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    A general modeling and visualization tool for comparing different members of a group: application to studying tau-mediated regulation of microtubule dynamics

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    <p>Abstract</p> <p>Background</p> <p>Innumerable biological investigations require comparing collections of molecules, cells or organisms to one another with respect to one or more of their properties. Almost all of these comparisons are performed manually, which can be susceptible to inadvertent bias as well as miss subtle effects. The development and application of computer-assisted analytical and interpretive tools could help address these issues and thereby dramatically improve these investigations.</p> <p>Results</p> <p>We have developed novel computer-assisted analytical and interpretive tools and applied them to recent studies examining the ability of 3-repeat and 4-repeat tau to regulate the dynamic behavior of microtubules in vitro. More specifically, we have developed an automated and objective method to define growth, shortening and attenuation events from real time videos of dynamic microtubules, and demonstrated its validity by comparing it to manually assessed data. Additionally, we have used the same data to develop a general strategy of building different models of interest, computing appropriate dissimilarity functions to compare them, and embedding them on a two-dimensional plot for visualization and easy comparison. Application of these methods to assess microtubule growth rates and growth rate distributions established the validity of the embedding procedure and revealed non-linearity in the relationship between the tau:tubulin molar ratio and growth rate distribution.</p> <p>Conclusion</p> <p>This work addresses the need of the biological community for rigorously quantitative and generally applicable computational tools for comparative studies. The two-dimensional embedding method retains the inherent structure of the data, and yet markedly simplifies comparison between models and parameters of different samples. Most notably, even in cases where numerous parameters exist by which to compare the different samples, our embedding procedure provides a generally applicable computational strategy to detect subtle relationships between different molecules or conditions that might otherwise escape manual analyses.</p

    Internet-based treatment for older adults with depression and co-morbid cardiovascular disease: protocol for a randomised, double-blind, placebo controlled trial

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    <p>Abstract</p> <p>Background</p> <p>Depression, cardiovascular disease (CVD) risk factors and cognitive impairment are important causes of disability and poor health outcomes. In combination they lead to an even worse prognosis. Internet or web-based interventions have been shown to deliver efficacious psychological intervention programs for depression on a large scale, yet no published studies have evaluated their impact among patients with co-existing physical conditions. The aims of this randomised controlled trial are to determine the effects of an evidence-based internet intervention program for depression on depressive mood symptoms, cognitive function and treatment adherence in patients at risk of CVD.</p> <p>Methods/Design</p> <p>This study is an internet-based, double-blind, parallel group randomised controlled trial. The trial will compare the effectiveness of online cognitive behavioural therapy with an online attention control placebo. The trial will consist of a 12-week intervention phase with a 40-week follow-up. It will be conducted in urban and rural New South Wales, Australia and will recruit a community-based sample of adults aged 45 to 75 years. Recruitment, intervention, cognitive testing and follow-up data collection will all be internet-based and automated. The primary outcome is a change in severity of depressive symptoms from baseline to three-months. Secondary outcomes are changes in cognitive function and adherence to treatment for CVD from baseline to three, six and 12-months.</p> <p>Discussion</p> <p>Prior studies of depression amongst patients with CVD have targeted those with previous vascular events and major depression. The potential for intervening earlier in these disease states appears to have significant potential and has yet to be tested. Scalable psychological programs using web-based interventions could deliver care to large numbers in a cost effective way if efficacy were proved. This study will determine the effects of a web-based intervention on depressive symptoms and adherence to treatment among patients at risk of CVD. In addition it will also precisely and reliably define the effects of the intervention upon aspects of cognitive function that are likely to be affected early in at risk individuals, using sensitive and responsive measures.</p> <p>Trial registration</p> <p>Australian New Zealand Clinical Trials Registry (ANZCTR): <a href="http://www.anzctr.org.au/ACTRN12610000085077.aspx">ACTRN12610000085077</a></p

    Rif1 maintains telomeres and mediates DNA repair by encasing DNA ends

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    In yeast, Rif1 is part of the telosome, where it inhibits telomerase and checkpoint signaling at chromosome ends. In mammalian cells, Rif1 is not telomeric, but it suppresses DNA end resection at chromosomal breaks, promoting repair by nonhomologous end joining (NHEJ). Here, we describe crystal structures for the uncharacterized and conserved ∼125-kDa N-terminal domain of Rif1 from Saccharomyces cerevisiae (Rif1-NTD), revealing an α-helical fold shaped like a shepherd's crook. We identify a high-affinity DNA-binding site in the Rif1-NTD that fully encases DNA as a head-to-tail dimer. Engagement of the Rif1-NTD with telomeres proved essential for checkpoint control and telomere length regulation. Unexpectedly, Rif1-NTD also promoted NHEJ at DNA breaks in yeast, revealing a conserved role of Rif1 in DNA repair. We propose that tight associations between the Rif1-NTD and DNA gate access of processing factors to DNA ends, enabling Rif1 to mediate diverse telomere maintenance and DNA repair functions
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