Controlled Release of Metformin Hydrochloride from Core-Shell Nanofibers with Fish Sarcoplasmic Protein
Abstract
Background and Objectives: A coaxial electrospinning technique was used to produce core/shell nanofibers of a polylactic acid (PLA) as a shell and a polyvinyl alcohol (PVA) containing metformin hydrochloride (MH) as a core. Materials and Methods: Fish sarcoplasmic protein (FSP) was extracted from fresh bonito and incorporated into nanofiber at various concentrations to investigate the influence on properties of the coaxial nanofibers. The morphology, chemical structure and thermal properties of the nanofibers were studied. Results: The results show that uniform and bead-free structured nanofibers with diameters ranging from 621 nm to 681 nm were obtained. A differential scanning calorimetry (DSC) analysis shows that FSP had a reducing effect on the crystallinity of the nanofibers. Furthermore, the drug release profile of electrospun fibers was analyzed using the spectrophotometric method. Conclusions: The nanofibers showed prolonged and sustained release and the first order kinetic seems to be more suitable to describe the release. MTT assay suggests that the produced drug and protein loaded coaxial nanofibers are non-toxic and enhance cell attachment. Thus, these results demonstrate that the produced nanofibers had the potential to be used for diabetic wound healing applications.
Read the paper
Related studies
- Metformin as an adjuvant in breast cancer treatment
- Metformin Lysosomal Targeting: A Novel Aspect to Be Investigated for Metformin Repurposing in Neurodegenerative Diseases?
- Aberrant HSF1 signaling activation underlies metformin amelioration of myocardial infarction in mice
- Metformin induces ZFP36 by mTORC1 inhibition in cervical cancer-derived cell lines
- Protein Interaction Network for Identifying Vascular Response of Metformin (Oral Antidiabetic)
- Preventing Long COVID With Metformin
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.