Accurate discrimination of clinically related cancer types using circulating extracellular vesicles (EVs) remains challenging because plasma EVs are heterogeneous, low-abundance, and difficult to profile in a multiplexed and quantitative manner. Here, we developed a microfluidic surface plasmon resonance imaging (SPRi) platform for eight-marker EV protein phenotyping and machine learning-assisted multi-cancer discrimination. Heterogeneous EV populations were broadly captured through cholesterol–phospholipid membrane interactions, followed by protein-specific signal amplification using aptamer-functionalized gold nanoparticles targeting CD63, EGFR, EpCAM, HER2, ICAM-1, ITGB1, MUC1, and PD-L1. The platform achieved sensitive EV detection over 10³–10⁸ particles mL⁻¹, with a limit of detection below 10³ particles mL⁻¹, and showed favorable analytical reliability in specificity and spike-and-recovery assays. In 94 clinical plasma samples from healthy donors and patients with gastric cancer, colorectal cancer, or breast cancer, single-marker and averaged-response analyses revealed clear cancer-associated EV alterations but showed limited ability to resolve cancer type-specific differences. By integrating the eight-dimensional EV protein profiles, multiple machine learning models improved multi-cancer discrimination, with all six models achieving multiclass AUC values of 1.000 and five-fold cross-validation accuracies around 0.95 in the present cohort. This study demonstrates that microfluidic SPRi-based EV phenotyping can transform plasma EV surface protein signatures into model-recognizable discriminative patterns, providing a feasible liquid biopsy strategy for non-invasive multi-cancer discrimination.
Traditional piezoelectric cancer therapy primarily uses ultrasound to activate piezoelectric biomaterials to generate radicals for killing tumor cells. Although effective, this approach faces challenges including tumor resistance to oxidative stress and limited therapeutic efficacy of traditional piezoelectric biomaterials. In this work, we rationally design and engineer a single-phase sono-electro-enzymatic nanocoupler that intrinsically couples sono-piezoelectric conversion, charge-driven redox catalysis, and enzyme-mimetic bioactivity. This nanocoupler is engineered by strategically doping Mn into Aurivillius phase SrBi4Ti4O15 nanosheets. The Mn doping simultaneously enhances the apparent local electromechanical response, reduces the apparent optical bandgap, and creates Mn2+/Mn3+ redox centers that feature multienzyme-mimetic catalytic activities. Under ultrasound stimulation, piezoelectric activation is coupled with Mn-mediated catalytic redox reactions, forming an amplified sono-electro-enzymatic cascade. This cascade activates multiple PANoptosis-related cell-death pathways, effectively inducing tumor cell death. This work establishes a sono-electro-enzymatic cascade that induces a PANoptosis-like multimodal cell-death phenotype, providing a representative paradigm for piezoelectric catalysis-enabled suppression of postsurgical glioma recurrence.
Sepsis caused by drug-resistant bacteria remains a global health crisis. Under such circumstances, phage therapy represents a promising option. However, phage-mediated bacterial lysis process can release a large amount of lipopolysaccharide (LPS), which in turn triggers inflammatory storms. Herein, we equipped phage with LPS-degrading CeO₂ nanozymes (X03@CeO₂). In vitro, X03@CeO₂ achieved 99.99
