19,256 research outputs found

    Advanced optical imaging in living embryos

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    Developmental biology investigations have evolved from static studies of embryo anatomy and into dynamic studies of the genetic and cellular mechanisms responsible for shaping the embryo anatomy. With the advancement of fluorescent protein fusions, the ability to visualize and comprehend how thousands to millions of cells interact with one another to form tissues and organs in three dimensions (xyz) over time (t) is just beginning to be realized and exploited. In this review, we explore recent advances utilizing confocal and multi-photon time-lapse microscopy to capture gene expression, cell behavior, and embryo development. From choosing the appropriate fluorophore, to labeling strategy, to experimental set-up, and data pipeline handling, this review covers the various aspects related to acquiring and analyzing multi-dimensional data sets. These innovative techniques in multi-dimensional imaging and analysis can be applied across a number of fields in time and space including protein dynamics to cell biology to morphogenesis

    Multispectral fingerprinting for improved in vivo cell dynamics analysis

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    Background: Tracing cell dynamics in the embryo becomes tremendously difficult when cell trajectories cross in space and time and tissue density obscure individual cell borders. Here, we used the chick neural crest (NC) as a model to test multicolor cell labeling and multispectral confocal imaging strategies to overcome these roadblocks. Results: We found that multicolor nuclear cell labeling and multispectral imaging led to improved resolution of in vivo NC cell identification by providing a unique spectral identity for each cell. NC cell spectral identity allowed for more accurate cell tracking and was consistent during short term time-lapse imaging sessions. Computer model simulations predicted significantly better object counting for increasing cell densities in 3-color compared to 1-color nuclear cell labeling. To better resolve cell contacts, we show that a combination of 2-color membrane and 1-color nuclear cell labeling dramatically improved the semi-automated analysis of NC cell interactions, yet preserved the ability to track cell movements. We also found channel versus lambda scanning of multicolor labeled embryos significantly reduced the time and effort of image acquisition and analysis of large 3D volume data sets. Conclusions: Our results reveal that multicolor cell labeling and multispectral imaging provide a cellular fingerprint that may uniquely determine a cell's position within the embryo. Together, these methods offer a spectral toolbox to resolve in vivo cell dynamics in unprecedented detail

    Analyzing library collections with starfield visualizations

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    This paper presents a qualitative and formative study of the uses of a starfield-based visualization interface for analysis of library collections. The evaluation process has produced feedback that suggests ways to significantly improve starfield interfaces and the interaction process to improve their learnability and usability. The study also gave us clear indication of additional potential uses of starfield visualizations that can be exploited by further functionality and interface development. We report on resulting implications for the design and use of starfield visualizations that will impact their graphical interface features, their use for managing data quality and their potential for various forms of visual data mining. Although the current implementation and analysis focuses on the collection of a physical library, the most important contributions of our work will be in digital libraries, in which volume, complexity and dynamism of collections are increasing dramatically and tools are needed for visualization and analysis

    Chlamydial infection from outside to inside

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    Chlamydia are obligate intracellular bacteria, characterized by a unique biphasic developmental cycle. Specific interactions with the host cell are crucial for the bacteria's survival and amplification because of the reduced chlamydial genome. At the start of infection, pathogen-host interactions are set in place in order for Chlamydia to enter the host cell and reach the nutrient-rich peri-Golgi region. Once intracellular localization is established, interactions with organelles and pathways of the host cell enable the necessary hijacking of host-derived nutrients. Detailed information on the aforementioned processes will increase our understanding on the intracellular pathogenesis of chlamydiae and hence might lead to new strategies to battle chlamydial infection. This review summarizes how chlamydiae generate their intracellular niche in the host cell, acquire host-derived nutrients in order to enable their growth and finally exit the host cell in order to infect new cells. Moreover, the evolution in the development of molecular genetic tools, necessary for studying the chlamydial infection biology in more depth, is discussed in great detail

    Experiences with starfield visualizations for analysis of library collections

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    This paper presents a qualitative and formative study of the uses of a starfield-based visualization interface for analysis of library collections. The evaluation process has produced feedback that suggests ways to significantly improve starfield interfaces and the interaction process to improve their learnability and usability. The study also gave us clear indication of additional potential uses of starfield visualizations that can be exploited by further functionality and interface development. We report on resulting implications for the design and use of starfield visualizations that will impact their graphical interface features, their use for managing data quality and their potential for various forms of visual data mining. Although the current implementation and analysis focuses on the collection of a physical library, the most important contributions of our work will be in digital libraries, in which volume, complexity and dynamism of collections are increasing dramatically and tools are needed for visualization and analysis

    Adaptive foveated single-pixel imaging with dynamic super-sampling

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    As an alternative to conventional multi-pixel cameras, single-pixel cameras enable images to be recorded using a single detector that measures the correlations between the scene and a set of patterns. However, to fully sample a scene in this way requires at least the same number of correlation measurements as there are pixels in the reconstructed image. Therefore single-pixel imaging systems typically exhibit low frame-rates. To mitigate this, a range of compressive sensing techniques have been developed which rely on a priori knowledge of the scene to reconstruct images from an under-sampled set of measurements. In this work we take a different approach and adopt a strategy inspired by the foveated vision systems found in the animal kingdom - a framework that exploits the spatio-temporal redundancy present in many dynamic scenes. In our single-pixel imaging system a high-resolution foveal region follows motion within the scene, but unlike a simple zoom, every frame delivers new spatial information from across the entire field-of-view. Using this approach we demonstrate a four-fold reduction in the time taken to record the detail of rapidly evolving features, whilst simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This tiered super-sampling technique enables the reconstruction of video streams in which both the resolution and the effective exposure-time spatially vary and adapt dynamically in response to the evolution of the scene. The methods described here can complement existing compressive sensing approaches and may be applied to enhance a variety of computational imagers that rely on sequential correlation measurements.Comment: 13 pages, 5 figure
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