Predictive design framework for electrospun pectin nanofibers in biomedical applications
- Авторы: Tugaeva G.
- Выпуск: Том 1, № 2 (2025)
- Раздел: Статьи
- URL: https://ogarev-online.ru/3033-5493/article/view/376514
- ID: 376514
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Аннотация
Pectin, a structurally diverse plant-derived polysaccharide, is emerging as a distinctive platform for engineering bioinstructive nanofibrous scaffolds. Compared to other natural polymers commonly used in electrospinning, such as alginate, hyaluronic acid or collagen, pectin offers a unique combination of mucoadhesiveness, immunomodulatory potential, and fine-tunable molecular architecture governed by the balance of homogalacturonan and rhamnogalacturonan domains. However, its intrinsic polyelectrolyte behavior, low chain entanglement, and high aqueous solubility have historically constrained its use in nanofiber fabrication. Recent advances in chemical modification, solvent engineering, and post-spinning stabilization have enabled the generation of electrospun pectin fibers with controllable morphology, mechanical resilience, and degradation kinetics. This review introduces a predictive structure–property–function framework for the rational design of electrospun pectin nanofibers in biomedical applications. We classify molecular strategies into three groups (covalent, physical, and compositional) and evaluate how each of them affects fiber formation and downstream biological performance, with particular focus on immunological interaction, bioactive loading, and scaffold remodeling. In parallel, we identify translational bottlenecks including material variability, sterilization sensitivity, and regulatory misalignment of crosslinking chemistries. By integrating these factors into a design informed scaffold logic, this review provides a roadmap for advancing electrospun pectin materials from laboratory prototypes to clinically viable platforms for regenerative medicine, wound healing, and localized therapeutic delivery.
Об авторах
Gilyana K. Tugaeva
Автор, ответственный за переписку.
Email: kazakova_g_k@staff.sechenov.ru
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