Southern Medical University

Neuropathic pain remains a major clinical challenge owing to complex neuroimmune mechanisms and limited disease-modifying therapies. Neuroinflammation within the dorsal root ganglion (DRG), particularly macrophage infiltration and pro-inflammatory polarization, is a key driver of sensory neuronal sensitization and pain persistence. Here, we report an injectable reactive oxygen species (ROS)-responsive natural drug self-delivery hydrogel for localized and sustained treatment of neuropathic pain. Single-cell transcriptomic reanalysis revealed marked macrophage accumulation in injured DRGs, accompanied by M1-like polarization and aberrant phosphatidylinositol 3-kinase (PI3K)-Akt activation. Mechanism-guided virtual screening identified glycyrrhizic acid (GA), a bioactive natural product, as a promising PI3K-targeting candidate. To improve local bioavailability, GA was engineered into a 1,4-phenylenediboronic acid (1,4-PBA)-functionalized self-assembled hydrogel, termed GA-PBA-GA (GPG), through dynamic boronate ester bonds and non-covalent interactions. The GPG hydrogel exhibited injectability, self-healing, biodegradability, biocompatibility, and inflammation-associated ROS-triggered GA release. In vitro, GPG suppressed PI3K-Akt signaling, reduced pro-inflammatory macrophage activation, and promoted M1-to-M2 repolarization. In a rat model of L5 spinal nerve ligation-induced neuropathic pain, peri-DRG administration alleviated mechanical and thermal hypersensitivity, improved gait and electrophysiological function, reduced DRG macrophage-mediated neuroinflammation, and attenuated spinal microglial activation. This ROS-responsive natural drug self-delivery hydrogel provides a minimally invasive strategy for remodeling DRG neuroinflammation and achieving sustained relief of neuropathic pain through localized drug delivery.

Cardiovascular stents are life-saving interventions for occlusive vascular diseases, yet current designs such as drug-eluting stents suppress restenosis via universal antiproliferation, inevitably impairing endothelial regeneration and raising the risk of late thrombosis. Here, we introduce a bioinspired endothelial-selective peptide self-assembling nanofibrous coating (ECSP-SANC) that integrates extracellular matrix (ECM)-mimetic β-sheet nanofibrous topography with REDV (Arg-Glu-Asp-Val)-mediated endothelial recognition cues to create a regenerative stent interface. ECSP-SANC forms a highly hydrated three-dimensional nanofibrous network that recapitulates key architectural features of native ECM while displaying accessible REDV motifs to preferentially promote endothelial cell adhesion, migration, proliferation, and functional maturation. In parallel, the coating suppresses smooth muscle cell overgrowth and synthetic phenotypic switching, thereby conferring an endothelial competitive advantage on the stent surface. The hydrated nanofibrous interface also minimizes platelet adhesion and inflammatory responses, contributing to improved hemocompatibility and local immune regulation. In a rabbit iliac artery implantation model, ECSP-SANC-functionalized stents accelerated re-endothelialization, suppressed neointimal hyperplasia, and effectively prevented restenosis. This approach demonstrates that precise integration of endothelial-selective biochemical signals with ECM-mimetic architecture can orchestrate vascular repair beyond conventional antiproliferative strategies. ECSP-SANC represents a versatile, next-generation platform for regenerative stent coatings, offering a blueprint for cardiovascular therapies that harmonize anti-restenotic efficacy with rapid endothelial recovery.

The clinical translation of small extracellular vesicle-derived microRNAs (sEV-miRNAs) for early colorectal cancer (CRC) diagnosis is often limited by their low abundance and complexity of biological fluids. Herein, we developed an ultrasensitive electrochemical platform based on multifunctional DNA nanoflower-assisted catalytic hairpin assembly (NF-CHA) for sEV-miRNAs detection. The NF acts as a localized scaffold to accelerate CHA kinetics and load abundant signal reporter. As a result, the NF-CHA strategy enables the platform achieving a limit of detection of 23.65 aM. To improve diagnostic performance, we employed different sEV-miRNAs combination and machine learning (ML) algorithms, achieving an area under the curve (AUC) of 0.996 for distinguishing early-stage CRC from healthy donors in clinical samples. Therefore, the electrochemical platform holds a great promise as a robust tool for CRC early diagnosis.