Targeted delivery and ROS-responsive release of celastrol by a macrophage membrane biomimetic liposome alleviates acute kidney injury

Abstract

Acute kidney injury (AKI) is characterized by an abrupt decline in renal function, often resulting from dysregulated production of reactive oxygen species (ROS) and an excessive inflammatory response. Celastrol, known for its anti-inflammatory and antioxidant properties, emerges as a promising therapeutic candidate for AKI. However, its clinical application is impeded by poor aqueous solubility, limited renal accumulation, and potential tissue toxicity. In this study, we engineered a macrophage membrane-camouflaged, ROS-responsive liposomal nanoplatform encapsulating celastrol (MST) that integrates inflammation-directed targeting with microenvironment-triggered release. Experimental findings indicate that the preservation of macrophage membrane proteins allowed MST to selectively target inflamed renal tissues, where it was efficiently internalized by damaged renal tubular cells, enabling rapid local drug release in response to elevated ROS levels. MST markedly mitigated oxidative damage both in vitro and in vivo, inhibited renal cell apoptosis, and reduced the inflammatory response in a renal ischemia-reperfusion injury model. Ultimately, MST achieved superior improvements in renal function, outperforming both non-biomimetic and non-responsive comparators, while demonstrating a favorable preliminary systemic safety profile. This study introduces a promising ROS-responsive biomimetic platform for AKI intervention.

Graphical abstract: Targeted delivery and ROS-responsive release of celastrol by a macrophage membrane biomimetic liposome alleviates acute kidney injury

Supplementary files

Article information

Article type
Paper
Submitted
13 Feb 2026
Accepted
22 May 2026
First published
16 Jun 2026

Nanoscale, 2026, Advance Article

Targeted delivery and ROS-responsive release of celastrol by a macrophage membrane biomimetic liposome alleviates acute kidney injury

G. Cheng, D. Bai, W. Chen, J. Wang, J. Xu, Y. Zhang, L. Li, Q. Lin, Z. Zhang, J. Ruan, L. Zhang and L. Guo, Nanoscale, 2026, Advance Article , DOI: 10.1039/D6NR00641H

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