Graphene oxide/polyethylene glycol aerogel reinforced with grape seed extracts as wound dressing
Source abstract
Abstract
In this study, graphene oxide (GO) and polyethylene glycol (PEG) composite aerogels were developed by non-covalent interactions, and then, grape seed extracts (Ex), high in proanthocyanidins (PAs), were incorporated into these materials to evaluate their hemostatic performance. The morphology, chemical features, surface charge, aerogel/blood cell interactions, absorption and blood coagulation capacity, cytotoxicity and extract release from the aerogels were investigated. The aerogels showed heterogeneous porous structures capable of absorbing more than 20 times their weight when in contact with fresh human blood and water. No significant differences were observed in the physical properties of the aerogels with the inclusion of grape seed extracts. However, the effects of this natural compound were favorable to blood coagulation clotting, increasing the coagulated blood content from 77% to 84% for GO-PEG and GO-PEG/Ex aerogels after 30 s of reaction, respectively. The aerogel/blood cell interactions demonstrated the adhesion of red blood cells (RBCs) and leukocytes on the aerogel’s surface, these interactions being favored by the inclusion of grape extracts on GO-PEG matrices. The aerogels showed proliferative effects on human dermal fibroblast cells, which could be associated with the presence of PEG and PAs in their matrices. Finally, the PAs release studies from the GO-PEG/Ex aerogel matrix showed that a combined mechanism of Fickian and non-Fickian diffusion governed these release processes. This study provides a new material whose hemocompatibility properties and phytodrug release ability support its application as a hemostatic device.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Graphene and Nanomaterials Applications · Electrospun Nanofibers in Biomedical Applications · Bone Tissue Engineering Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (60)
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