Dataset Information

A two-component pre-seeded dermal-epidermal scaffold.

ABSTRACT: We have developed a bilayered dermal-epidermal scaffold for application in the treatment of full-thickness skin defects. The dermal component gels in situ and adapts to the lesion shape, delivering human dermal fibroblasts in a matrix of fibrin and cross-linked hyaluronic acid modified with a cell adhesion-promoting peptide. Fibroblasts were able to form a tridimensional matrix due to material features such as tailored mechanical properties, presence of protease-degradable elements and cell-binding ligands. The epidermal component is a robust membrane containing cross-linked hyaluronic acid and poly-l-lysine, on which keratinocytes were able to attach and to form a monolayer. Amine-aldehyde bonding at the interface between the two components allows the formation of a tightly bound composite scaffold. Both parts of the scaffold were designed to provide cell-type-specific cues to allow for cell proliferation and form a construct that mimics the skin environment.

SUBMITTER: Monteiro IP

PROVIDER: S-EPMC4254066 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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A two-component pre-seeded dermal-epidermal scaffold.

Monteiro I P IP Gabriel D D Timko B P BP Hashimoto M M Karajanagi S S Tong R R Marques A P AP Reis R L RL Kohane D S DS

Acta biomaterialia 20140901 12

We have developed a bilayered dermal-epidermal scaffold for application in the treatment of full-thickness skin defects. The dermal component gels in situ and adapts to the lesion shape, delivering human dermal fibroblasts in a matrix of fibrin and cross-linked hyaluronic acid modified with a cell adhesion-promoting peptide. Fibroblasts were able to form a tridimensional matrix due to material features such as tailored mechanical properties, presence of protease-degradable elements and cell-bind ...[more]

PMID: 25192821

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Project description:Regeneration of periodontal tissue is the most promising method for restoring periodontal structures. To find a suitable bioactive three-dimensional scaffold promoting cell proliferation and differentiation is critical in periodontal tissue engineering. The objective of this study was to evaluate the biocompatibility of a novel porcine acellular dermal matrix as periodontal tissue scaffolds both in vitro and in vivo. The scaffolds in this study were purified porcine acellular dermal matrix (PADM) and hydroxyapatite-treated PADM (HA-PADM). The biodegradation patterns of the scaffolds were evaluated in vitro. The biocompatibility of the scaffolds in vivo was assessed by implanting them into the sacrospinal muscle of 20 New Zealand white rabbits. The hPDL cells were cultured with PADM or HA-PADM scaffolds for 3, 7, 14, 21 and 28 days. Cell viability assay, scanning electron microscopy (SEM), hematoxylin and eosin (H&E) staining, immunohistochemistry and confocal microscopy were used to evaluate the biocompatibility of the scaffolds. In vitro, both PADM and HA-PADM scaffolds displayed appropriate biodegradation pattern, and also, demonstrated favorable tissue compatibility without tissue necrosis, fibrosis and other abnormal response. The absorbance readings of the WST-1 assay were increased with the time course, suggesting the cell proliferation in the scaffolds. The hPDL cells attaching, spreading and morphology on the surface of the scaffold were visualized by SEM, H&E staining, immnuohistochemistry and confocal microscopy, demonstrated that hPDL cells were able to grow into the HA-PADM scaffolds and the amount of cells were growing up in the course of time. This study proved that HA-PADM scaffold had good biocompatibility in animals in vivo and appropriate biodegrading characteristics in vitro. The hPDL cells were able to proliferate and migrate into the scaffold. These observations may suggest that HA-PADM scaffold is a potential cell carrier for periodontal tissue regeneration.

Dataset Information

A two-component pre-seeded dermal-epidermal scaffold.

Publications

A two-component pre-seeded dermal-epidermal scaffold.

Similar Datasets

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