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Issue 5, 2019
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Hydrogels composed of hyaluronic acid and dendritic ELPs: hierarchical structure and physical properties

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Abstract

Hydrogels that mimic the native extracellular matrix were prepared from hyaluronic acid (HA) and amine-terminated dendritic elastin-like peptides (denELPs) of generations 1, 2, and 3 (G1, 2, and 3) as crosslinking units. The physical properties of the hydrogels were investigated by rheology, scanning electron microscopy, swelling tests, small-angle X-ray scattering (SAXS), and model drug loading and release assays. Hydrogel properties depended on the generation number of the denELP, which contained structural segments based on the repeating GLPGL pentamer. Hydrogels with higher generation denELPs (G2 and 3) showed similar properties, but those prepared from G1 denELPs were rheologically weaker, had a larger mesh size, absorbed less model drug, and released the drug more quickly. Interestingly, most of the HA_denELP hydrogels studied here remained transparent upon gelation, but after lyophilization and addition of water retained opaque, “solid-like” regions for up to 4 d during rehydration. This rehydration process was carefully evaluated through time-course SAXS studies, and the phenomenon was attributed to the formation of pre-coacervates in the gel-forming step, which slowly swelled in water during rehydration. These findings provide important insights into the behavior of ELP-based hydrogels, in which physical crosslinking of the ELP domains can be controlled to tune mechanical properties, highlighting the potential of HA_denELP hydrogels as biomaterials.

Graphical abstract: Hydrogels composed of hyaluronic acid and dendritic ELPs: hierarchical structure and physical properties

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Publication details

The article was received on 04 Dec 2018, accepted on 05 Jan 2019 and first published on 15 Jan 2019


Article type: Paper
DOI: 10.1039/C8SM02450B
Citation: Soft Matter, 2019,15, 917-925

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    Hydrogels composed of hyaluronic acid and dendritic ELPs: hierarchical structure and physical properties

    Y. Shmidov, M. Zhou, G. Yosefi, R. Bitton and J. B. Matson, Soft Matter, 2019, 15, 917
    DOI: 10.1039/C8SM02450B

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