Backlund, Fredrik G. and Schmuck, Benjamin and Miranda, Gisele H. B. and Greco, Gabriele and Pugno, Nicola M. and Rydén, Jesper and Rising, Anna
(2022).
An Image-Analysis-Based Method for the Prediction of Recombinant Protein Fiber Tensile Strength.
Materials. 15
:3
, 708
[Research article]
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Abstract
Silk fibers derived from the cocoon of silk moths and the wide range of silks produced by spiders exhibit an array of features, such as extraordinary tensile strength, elasticity, and adhesive properties. The functional features and mechanical properties can be derived from the structural composition and organization of the silk fibers. Artificial recombinant protein fibers based on engineered spider silk proteins have been successfully made previously and represent a promising way towards the large-scale production of fibers with predesigned features. However, for the production and use of protein fibers, there is a need for reliable objective quality control procedures that could be automated and that do not destroy the fibers in the process. Furthermore, there is still a lack of understanding the specifics of how the structural composition and organization relate to the ultimate function of silk-like fibers. In this study, we develop a new method for the categorization of protein fibers that enabled a highly accurate prediction of fiber tensile strength. Based on the use of a common light microscope equipped with polarizers together with image analysis for the precise determination of fiber morphology and optical properties, this represents an easy-to-use, objective non-destructive quality control process for protein fiber manufacturing and provides further insights into the link between the supramolecular organization and mechanical functionality of protein fibers.
Authors/Creators: | Backlund, Fredrik G. and Schmuck, Benjamin and Miranda, Gisele H. B. and Greco, Gabriele and Pugno, Nicola M. and Rydén, Jesper and Rising, Anna | ||||||
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Title: | An Image-Analysis-Based Method for the Prediction of Recombinant Protein Fiber Tensile Strength | ||||||
Series Name/Journal: | Materials | ||||||
Year of publishing : | 2022 | ||||||
Volume: | 15 | ||||||
Number: | 3 | ||||||
Article number: | 708 | ||||||
Number of Pages: | 13 | ||||||
Publisher: | MDPI | ||||||
Language: | English | ||||||
Publication Type: | Research article | ||||||
Article category: | Scientific peer reviewed | ||||||
Version: | Published version | ||||||
Copyright: | Creative Commons: Attribution 4.0 | ||||||
Full Text Status: | Public | ||||||
Subjects: | (A) Swedish standard research categories 2011 > 1 Natural sciences > 106 Biological Sciences (Medical to be 3 and Agricultural to be 4) > Biophysics | ||||||
Keywords: | spider silk, protein fibers, image analysis, structure-function relationship, prediction, mechanical properties | ||||||
URN:NBN: | urn:nbn:se:slu:epsilon-p-116853 | ||||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-116853 | ||||||
Additional ID: |
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ID Code: | 27703 | ||||||
Faculty: | VH - Faculty of Veterinary Medicine and Animal Science NJ - Fakulteten för naturresurser och jordbruksvetenskap | ||||||
Department: | (VH) > Dept. of Anatomy, Physiology and Biochemistry (NL, NJ) > Dept. of Energy and Technology | ||||||
Deposited By: | SLUpub Connector | ||||||
Deposited On: | 05 May 2022 11:25 | ||||||
Metadata Last Modified: | 05 May 2022 11:31 |
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