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Updated: May 26, 2026

Synergetic Use of Neural Precursor Cells and Self-assembling Peptides in Experimental Cervical Spinal Cord Injury
Published on: February 23, 2015
Multidimensional Engineering of Extracellular Vesicles for Targeted Delivery and Microglial Reprograming in Spinal
Wu Xiong1, Minhao Liu1, Juan Wang2
1Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, Jiangsu, China.
Abstract:
The recovery of neurological function following spinal cord injury (SCI) is primarily constrained by two core pathological mechanisms: neuroinflammation and impaired tissue regeneration. While extracellular vesicles (EVs) have emerged as a promising therapeutic approach, their clinical translation remains limited by the inherent low bioactivity of natural EVs and suboptimal targeting efficiency at lesion sites. In this study, we developed a targeted EV delivery system with synergistic therapeutic potential, termed C-A/R-EVs, through a multidimensional engineering strategy. Specifically, the system leverages the blood-spinal cord barrier-penetrating ability of Angiopep-2 and the pathologically neovascular targeting capability of RGD to achieve precise localization in the SCI region. Additionally, a curcumin pretreatment strategy is employed to enhance the anti-inflammatory and neuroregenerative properties of the EVs. SnRNA-seq reveals that C-A/R-EVs reprogram microglia from a pro-inflammatory phenotype to a reparative phenotype, effectively suppressing neuroinflammation and promoting neural repair. Mechanistically, C-A/R-EVs facilitate axonal regeneration through enhancing the phagocytosis of myelin debris via reparative microglia, while simultaneously reducing the presence of inflammatory microglia to mitigate postinjury neuroinflammation. Moreover, C-A/R-EVs contribute to the restoration of the blood-spinal cord barrier. This study provides new insights into the design and fabrication of engineered EVs to synergistically enhance spinal cord repair through multimodal mechanisms.
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