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microtubule networks  (BioMimetic Therapeutics)

 
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    Structured Review

    BioMimetic Therapeutics microtubule networks
    <t>Microtubule</t> trajectory point distribution.
    Microtubule Networks, supplied by BioMimetic Therapeutics, 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/microtubule+networks/microtubule+networks/pmc11857404-40-15-19
    Average 90 stars, based on 1 article reviews
    microtubule networks - by Bioz Stars, 2026-11
    90/100 stars

    Images

    1) Product Images from "Dual-Scale Collaborative Optimization of Microtubule Self-Healing Composites Based on Variable-Angle Fiber Design"

    Article Title: Dual-Scale Collaborative Optimization of Microtubule Self-Healing Composites Based on Variable-Angle Fiber Design

    Journal: Materials

    doi: 10.3390/ma18040905

    Microtubule trajectory point distribution.
    Figure Legend Snippet: Microtubule trajectory point distribution.

    Techniques Used:

    Description of microtubules.
    Figure Legend Snippet: Description of microtubules.

    Techniques Used:

    The entry and exit points of the microtubule network and the loops.
    Figure Legend Snippet: The entry and exit points of the microtubule network and the loops.

    Techniques Used:

    Optimal solution parameters for single/dual-scale optimization.
    Figure Legend Snippet: Optimal solution parameters for single/dual-scale optimization.

    Techniques Used:

    Related Articles

    Polymer:

    Article Title: Dual-Scale Collaborative Optimization of Microtubule Self-Healing Composites Based on Variable-Angle Fiber Design
    Article Snippet: .. Aragón et al. [ ] employed a multi-objective genetic algorithm to design two- and three-dimensional microtubule networks embedded in biomimetic self-healing/self-cooling polymer materials while considering various objective functions and constraints such as flow efficiency, homogeneity, network redundancy, and volume fraction. ..



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    Image Search Results


    Microtubule trajectory point distribution.

    Journal: Materials

    Article Title: Dual-Scale Collaborative Optimization of Microtubule Self-Healing Composites Based on Variable-Angle Fiber Design

    doi: 10.3390/ma18040905

    Figure Lengend Snippet: Microtubule trajectory point distribution.

    Article Snippet: Aragón et al. [ ] employed a multi-objective genetic algorithm to design two- and three-dimensional microtubule networks embedded in biomimetic self-healing/self-cooling polymer materials while considering various objective functions and constraints such as flow efficiency, homogeneity, network redundancy, and volume fraction.

    Techniques:

    Description of microtubules.

    Journal: Materials

    Article Title: Dual-Scale Collaborative Optimization of Microtubule Self-Healing Composites Based on Variable-Angle Fiber Design

    doi: 10.3390/ma18040905

    Figure Lengend Snippet: Description of microtubules.

    Article Snippet: Aragón et al. [ ] employed a multi-objective genetic algorithm to design two- and three-dimensional microtubule networks embedded in biomimetic self-healing/self-cooling polymer materials while considering various objective functions and constraints such as flow efficiency, homogeneity, network redundancy, and volume fraction.

    Techniques:

    The entry and exit points of the microtubule network and the loops.

    Journal: Materials

    Article Title: Dual-Scale Collaborative Optimization of Microtubule Self-Healing Composites Based on Variable-Angle Fiber Design

    doi: 10.3390/ma18040905

    Figure Lengend Snippet: The entry and exit points of the microtubule network and the loops.

    Article Snippet: Aragón et al. [ ] employed a multi-objective genetic algorithm to design two- and three-dimensional microtubule networks embedded in biomimetic self-healing/self-cooling polymer materials while considering various objective functions and constraints such as flow efficiency, homogeneity, network redundancy, and volume fraction.

    Techniques:

    Optimal solution parameters for single/dual-scale optimization.

    Journal: Materials

    Article Title: Dual-Scale Collaborative Optimization of Microtubule Self-Healing Composites Based on Variable-Angle Fiber Design

    doi: 10.3390/ma18040905

    Figure Lengend Snippet: Optimal solution parameters for single/dual-scale optimization.

    Article Snippet: Aragón et al. [ ] employed a multi-objective genetic algorithm to design two- and three-dimensional microtubule networks embedded in biomimetic self-healing/self-cooling polymer materials while considering various objective functions and constraints such as flow efficiency, homogeneity, network redundancy, and volume fraction.

    Techniques:

    a Schematic view of the mitotic control network. Note the multiple interconnected positive and double-negative feedback loops. b Preparation of cycling Xenopus egg extracts and the workflow of monitoring spontaneous mitotic trigger waves in thin PTFE tubes by epifluorescence microscopy. c Measurements of protein concentrations in the original and concentrated extract (retentate) as well the filtrate from the ultrafiltration filters. n = 4 for extracts, 6 for retentates, and 5 for filtrates. d A montage (left) and its corresponding kymograph (right) of a single tube undergoing 3 rounds of mitosis in the course of ~2 h. The bright signal is polymerized microtubules stained with SiR-tubulin and the dark bands correspond to the mitotic state in which most microtubules are depolymerized. e Representative kymographs (right column) of extracts of different cytoplasmic concentrations prepared from 1 x extracts (top 2 rows) or from 2 x retentate (bottom 3 rows). Left column shows the volume fractions of buffer (XB buffer without sucrose) and extracts that went into the samples. f Duration of the first completely observable cell cycle under the microscope, starting from interphase. Means ± S.E.M. are shown, n = 3 (three independent experiments). g Speeds of mitotic trigger waves at different cytoplasmic concentrations. Means ± S.E.M. are shown. Data is compiled from n = 8 independent experiments. Source data are provided as a Source Data file.

    Journal: Nature Communications

    Article Title: Robust trigger wave speed in Xenopus cytoplasmic extracts

    doi: 10.1038/s41467-024-50119-0

    Figure Lengend Snippet: a Schematic view of the mitotic control network. Note the multiple interconnected positive and double-negative feedback loops. b Preparation of cycling Xenopus egg extracts and the workflow of monitoring spontaneous mitotic trigger waves in thin PTFE tubes by epifluorescence microscopy. c Measurements of protein concentrations in the original and concentrated extract (retentate) as well the filtrate from the ultrafiltration filters. n = 4 for extracts, 6 for retentates, and 5 for filtrates. d A montage (left) and its corresponding kymograph (right) of a single tube undergoing 3 rounds of mitosis in the course of ~2 h. The bright signal is polymerized microtubules stained with SiR-tubulin and the dark bands correspond to the mitotic state in which most microtubules are depolymerized. e Representative kymographs (right column) of extracts of different cytoplasmic concentrations prepared from 1 x extracts (top 2 rows) or from 2 x retentate (bottom 3 rows). Left column shows the volume fractions of buffer (XB buffer without sucrose) and extracts that went into the samples. f Duration of the first completely observable cell cycle under the microscope, starting from interphase. Means ± S.E.M. are shown, n = 3 (three independent experiments). g Speeds of mitotic trigger waves at different cytoplasmic concentrations. Means ± S.E.M. are shown. Data is compiled from n = 8 independent experiments. Source data are provided as a Source Data file.

    Article Snippet: We used 200 nM SiR-tubulin (CY-SC002, Cytoskeleton, Inc) to visualize the microtubule networks, which dissolve at the onset of mitosis, providing a sensitive readout for the mitotic wave fronts.

    Techniques: Control, Epifluorescence Microscopy, Staining, Microscopy