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  • 1
    In: Biological Imaging, Cambridge University Press (CUP), Vol. 3 ( 2023)
    Abstract: Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.
    Type of Medium: Online Resource
    ISSN: 2633-903X
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2023
    detail.hit.zdb_id: 3053464-1
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  • 2
    In: Proceedings of the Nutrition Society, Cambridge University Press (CUP), Vol. 79, No. 2 ( 2020-05), p. 225-235
    Abstract: Food phytochemicals are increasingly considered to play a key role in the cardiometabolic health effects of plant foods. However, the heterogeneity in responsiveness to their intake frequently observed in clinical trials can hinder the beneficial effects of these compounds in specific subpopulations. A range of factors, including genetic background, gut microbiota, age, sex and health status, could be involved in these interindividual variations; however, the current knowledge is limited and fragmented. The European network, European Cooperation in Science and Technology (COST)-POSITIVe, has analysed, in a systematic way, existing knowledge with the aim to better understand the factors responsible for the interindividual variation in response to the consumption of the major families of plant food bioactives, regarding their bioavailability and bioefficacy. If differences in bioavailability, likely reflecting differences in human subjects’ genetics or in gut microbiota composition and functionality, are believed to underpin much of the interindividual variability, the key molecular determinants or microbial species remain to be identified. The systematic analysis of published studies conducted to assess the interindividual variation in biomarkers of cardiometabolic risk suggested some factors (such as adiposity and health status) as involved in between-subject variation. However, the contribution of these factors is not demonstrated consistently across the different compounds and biological outcomes and would deserve further investigations. The findings of the network clearly highlight that the human subjects’ intervention studies published so far are not adequate to investigate the relevant determinants of the absorption/metabolism and biological responsiveness. They also emphasise the need for a new generation of intervention studies designed to capture this interindividual variation.
    Type of Medium: Online Resource
    ISSN: 0029-6651 , 1475-2719
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2016335-6
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