Malate-Based Biodegradable Scaffolds Activate Cellular Energetic Metabolism for Accelerated Wound Healing.
Min WuYitao ZhaoMeihan TaoMeimei FuYue WangQi LiuZhihui LuJinshan GuoPublished in: ACS applied materials & interfaces (2023)
The latest advancements in cellular bioenergetics have revealed the potential of transferring chemical energy to biological energy for therapeutic applications. Despite efforts, a three-dimensional (3D) scaffold that can induce long-term bioenergetic effects and facilitate tissue regeneration remains a big challenge. Herein, the cellular energetic metabolism promotion ability of l-malate, an important intermediate of the tricarboxylic acid (TCA) cycle, was proved, and a series of bioenergetic porous scaffolds were fabricated by synthesizing poly(diol l-malate) (PDoM) prepolymers via a facial one-pot polycondensation of l-malic acid and aliphatic diols, followed by scaffold fabrication and thermal-cross-linking. The degradation products of the developed PDoM scaffolds can regulate the metabolic microenvironment by entering mitochondria and participating in the TCA cycle to elevate intracellular adenosine triphosphate (ATP) levels, thus promoting the cellular biosynthesis, including the production of collagen type I (Col1a1), fibronectin 1 (Fn1), and actin alpha 2 (Acta2/α-Sma). The porous PDoM scaffold was demonstrated to support the growth of the cocultured mesenchymal stem cells (MSCs) and promote their secretion of bioactive molecules [such as vascular endothelial growth factor (VEGF), transforming growth factor-β1 (TGF-β1), and basic fibroblast growth factor (bFGF)], and this stem cells-laden scaffold architecture was proved to accelerate wound healing in a critical full-thickness skin defect model on rats.
Keyphrases
- tissue engineering
- wound healing
- vascular endothelial growth factor
- transforming growth factor
- stem cells
- mesenchymal stem cells
- epithelial mesenchymal transition
- umbilical cord
- endothelial cells
- cell death
- drug delivery
- soft tissue
- optical coherence tomography
- risk assessment
- big data
- reactive oxygen species
- machine learning
- human health
- climate change
- cell migration