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software environment matlab runtime v.9.0.1 14  (MathWorks Inc)


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    MathWorks Inc software environment matlab runtime v.9.0.1 14
    Software Environment Matlab Runtime V.9.0.1 14, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+runtime+software/pm33022392-199-26-28
    Average 90 stars, based on 1 article reviews
    software environment matlab runtime v.9.0.1 14 - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: De-risking excipient particle size distribution variability with automated robust mixing: Integrating quality by design and process analytical technology.
    Article Snippet: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record.. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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    Article Title: De-risking excipient particle size distribution variability with automated robust mixing: Integrating quality by design and process analytical technology.
    Article Snippet: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record.. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.



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    Intravital Systems Microscopy: Multiparametric SVM classification of tumor cell locomotion and microenvironmental parameters (a) Identifying and quantifying fast-locomoting cells. Left panels, raw images of an individual z-section from the 4D stack (at 0 and 60 min; 0′ and 60′). Middle panels, 0′ was subtracted from 60′, resulting in Δ60 (top); image was then thresholded/binarized (bottom). Right panels, results of motility analysis including quantification of fast locomoting cells (top) and the overlay with the 0′ image (bottom). Scale bar 50 μm. (b) Identifying and quantifying invadopodia in slow locomoting cells. Raw images of a cell at time 0, with fully extended invadopodium at 3 min and partially retracted invadopodium at 15 min. Overlays Δ3 and Δ15 show invadopodia extension highlighted in magenta. Scale bar 10 μm. (c) Binarized images used for extraction of microenvironmental parameters. Image in Fig. 1c was separated and thresholded, resulting in binary images of collagen (magenta), tumor cells (green), macrophages (cyan) and blood vessels (red). (c′) Collagen fiber map (left) and dimensionless straightness histogram (right) from <t>ctFIRE</t> <t>software.</t> (d) 3D projection of SVM classification results. Red spheres denote slow locomotion, blue-fast locomotion, green- misclassifications. The size of the spheres indicates the number of locomoting cells in the FOV. Dmax (μm) stands for the diameter of the largest blood vessel in the FOV, macrophages (%) and collagen (%) stand for the thresholded area in respective channels
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    Intravital Systems Microscopy: Multiparametric SVM classification of tumor cell locomotion and microenvironmental parameters (a) Identifying and quantifying fast-locomoting cells. Left panels, raw images of an individual z-section from the 4D stack (at 0 and 60 min; 0′ and 60′). Middle panels, 0′ was subtracted from 60′, resulting in Δ60 (top); image was then thresholded/binarized (bottom). Right panels, results of motility analysis including quantification of fast locomoting cells (top) and the overlay with the 0′ image (bottom). Scale bar 50 μm. (b) Identifying and quantifying invadopodia in slow locomoting cells. Raw images of a cell at time 0, with fully extended invadopodium at 3 min and partially retracted invadopodium at 15 min. Overlays Δ3 and Δ15 show invadopodia extension highlighted in magenta. Scale bar 10 μm. (c) Binarized images used for extraction of microenvironmental parameters. Image in Fig. 1c was separated and thresholded, resulting in binary images of collagen (magenta), tumor cells (green), macrophages (cyan) and blood vessels (red). (c′) Collagen fiber map (left) and dimensionless straightness histogram (right) from ctFIRE software. (d) 3D projection of SVM classification results. Red spheres denote slow locomotion, blue-fast locomotion, green- misclassifications. The size of the spheres indicates the number of locomoting cells in the FOV. Dmax (μm) stands for the diameter of the largest blood vessel in the FOV, macrophages (%) and collagen (%) stand for the thresholded area in respective channels

    Journal: Methods in molecular biology (Clifton, N.J.)

    Article Title: Intravital Imaging of Tumor Cell Motility in the Tumor Microenvironment Context

    doi: 10.1007/978-1-4939-7701-7_14

    Figure Lengend Snippet: Intravital Systems Microscopy: Multiparametric SVM classification of tumor cell locomotion and microenvironmental parameters (a) Identifying and quantifying fast-locomoting cells. Left panels, raw images of an individual z-section from the 4D stack (at 0 and 60 min; 0′ and 60′). Middle panels, 0′ was subtracted from 60′, resulting in Δ60 (top); image was then thresholded/binarized (bottom). Right panels, results of motility analysis including quantification of fast locomoting cells (top) and the overlay with the 0′ image (bottom). Scale bar 50 μm. (b) Identifying and quantifying invadopodia in slow locomoting cells. Raw images of a cell at time 0, with fully extended invadopodium at 3 min and partially retracted invadopodium at 15 min. Overlays Δ3 and Δ15 show invadopodia extension highlighted in magenta. Scale bar 10 μm. (c) Binarized images used for extraction of microenvironmental parameters. Image in Fig. 1c was separated and thresholded, resulting in binary images of collagen (magenta), tumor cells (green), macrophages (cyan) and blood vessels (red). (c′) Collagen fiber map (left) and dimensionless straightness histogram (right) from ctFIRE software. (d) 3D projection of SVM classification results. Red spheres denote slow locomotion, blue-fast locomotion, green- misclassifications. The size of the spheres indicates the number of locomoting cells in the FOV. Dmax (μm) stands for the diameter of the largest blood vessel in the FOV, macrophages (%) and collagen (%) stand for the thresholded area in respective channels

    Article Snippet: The ctFIRE software requires MATLAB compiler runtime (MCR 7.17 2012a) installation.

    Techniques: Microscopy, Extraction, Software