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Updated: Jan 15, 2026

Injection of Hydrogel Biomaterial Scaffolds to The Brain After Stroke
Published on: October 1, 2020
虚血性脳卒中後のマウスにおける機能的回復を促進するアンタゴミルローディングβペプチドヒドロゲル
Yi-Kai Chen1, Ketav Kulkarni2, Marie-Isabel Aguilar2
1Department of Pharmacology, Monash University, Clayton, VIC, 3800, Australia; Biomedicine Discovery Institute, Monash University, Clayton, VIC, 3800, Australia.
Abstract:
Ischaemic stroke is a leading cause of mortality and disability, arising from interrupted cerebral blood flow and subsequent neuronal death. MicroRNAs, particularly miR-181a, have emerged as promising therapeutic targets due to their roles in regulating apoptosis and oxidative stress. While miR-181a inhibition using antagomirs can improve neuronal survival, translation to clinical practice is hampered by inefficient delivery across the blood-brain barrier and poor pharmacokinetics. Here, we developed a series of novel β-peptide hydrogels as injectable delivery systems to encapsulate and release a miR-181a antagomir in a controlled manner within the infarct region. β-peptides were synthesised with varied incorporation of β-homolysine residues to modulate electrostatic interactions with nucleic acids. The resulting hydrogels demonstrated shear-thinning and self-healing properties, stiffness values within the physiological range of brain tissue and tunable nucleic acid release profiles extending over 3 weeks. Following photothrombotic stroke in mice, intracerebral injection of antagomir-loaded hydrogel achieved precise infarct delivery and sustained presence for at least 7 days. Although infarct size reduction was modest, functional recovery, measured by improved motor coordination in the hanging wire test, was significantly enhanced in the hydrogel-antagomir group compared with controls. These findings highlight β-peptide hydrogels as promising platforms for localised, sustained delivery of nucleic acid therapeutics. This work establishes proof-of-concept for hydrogel-mediated miRNA delivery in stroke and provides a foundation for further optimisation in clinically relevant models.
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