Background: Non-invasive therapies for heart failure represent one of the current major focuses in clinical research. Plant-derived extracellular vesicles (PEVs) have recently emerged as a promising therapeutic modality. Objectives: In this study, we investigated the therapeutic potential of PEVs in heart failure with preserved ejection fraction (HFpEF), focusing on extracellular vesicles derived from Lycium barbarum (Gq-EVs). Methods: We first obtained Gq-EVs with high biological activity and high concentration from Lycium barbarum juice and characterized them by using transmission electron microscopy, nanoparticle tracking analysis, and metabolite composition analysis. Results: Our in vivo findings indicate that nebulized inhalation of Gq-EVs for 7, 14, and 21 days improved abnormal cardiac diastolic function, reduced excessive myocardial hypertrophy, and attenuated inflammatory cell infiltration and collagen deposition in HFpEF mice. Further in vivo and in vitro experiments showed that Gq-EVs can reach injured cardiac tissue, improve mitochondrial function, and are associated with reduced cardiomyocyte apoptosis and amelioration of myocardial hypertrophy, potentially involving TP53-related apoptotic signaling. Conclusions: Overall, nebulized delivery of Gq-EVs may be a relatively non-invasive, well-tolerated, and cost-effective therapeutic strategy for HFpEF, highlighting the potential of PEV-based nanotherapies and offering a sustainable approach for the medical utilization of Lycium barbarum resources.

Background: Cardiometabolic diseases are characterized by long disease courses, substantial inter-individual heterogeneity, and complex interactions among multiple risk factors, posing significant challenges to long-term management and precision interventions. Digital twin technology, which constructs individualized digital representations of patients, has demonstrated unique potential in precision disease management and clinical decision support. However, there remains a gap in the systematic synthesis of its applications in cardiometabolic disease management. Objective: This scoping review aimed to systematically outline the core application scenarios of digital twin technology in cardiometabolic disease management, summarize the integrated data sources and key technical approaches used to construct and operate digital twins, identify current technical, ethical, and clinical challenges, and outline future research directions. Methods: A scoping review was conducted on November 29, 2025. Relevant studies on the application of digital twin technology in cardiometabolic disease management were systematically searched, screened, and selected. Data were extracted and synthesized with a focus on application scenarios, data sources, modeling approaches, implementation stages, and reported challenges. Results: Of the 5596 articles identified, 32 met inclusion criteria after screening. Digital twin applications in cardiometabolic diseases primarily focused on individualized risk prediction and stratification, optimization of treatment and intervention strategies, and clinical decision support. Integrated data sources mainly included physiological and metabolic data, electronic data of clinical documents, medical imaging, and behavioral and lifestyle-related data. Data-driven models were the most commonly used approach, followed by mechanistic models, hybrid models, multi-scale or multi-physics models, and simulation-based optimization methods. Most studies remained at the proof-of-concept or early implementation stage. Major challenges included limited data availability and integration, difficulties in model personalization and validation, ethical and privacy concerns, and insufficient integration into clinical and care workflows. Conclusions: Digital twin technology shows significant promise for precision management of cardiometabolic diseases. Existing studies indicate that digital twins are primarily applied in individualized risk assessment, optimization of treatment strategies, disease progression simulation, and long-term management support. However, prevailing research remains predominantly data-driven and is not yet fully aligned with sustained disease management and routine care processes. Future efforts should emphasize mechanistic and hybrid modeling approaches, conduct multicenter prospective validations and randomized controlled trials, and promote interoperable and privacy-preserving system deployment to support the sustainable implementation of digital twins in cardiometabolic disease management.

Non‐alcoholic fatty liver disease (NAFLD) is a common metabolic liver disorder with limited effective pharmacological treatments. Tetrandrine (Tet), a major bioactive alkaloid derived from Stephaniae Tetrandrae Radix , has shown anti‐inflammatory and metabolic regulatory potential. In this study, we systematically investigated the therapeutic effects and underlying mechanisms of STR alkaloids, with a focus on Tet in NAFLD. Network pharmacology identified active alkaloids and 194 overlapping targets associated with NAFLD, and protein–protein interaction analysis highlighted TP53, EGFR, STAT3, AKT1, and TNF as key hub genes. Functional enrichment analyses indicated that the PI3K/AKT, MAPK, and FoxO signaling pathways were significantly involved, with PI3K/AKT emerging as the central signaling pathway. Molecular docking and molecular dynamics simulations demonstrated stable binding interactions between Tet and STAT3 as well as TNF. Mendelian randomization analysis further suggested a causal relationship between elevated STAT3 expression and increased NAFLD risk. Experimental validation in a thioacetamide‐induced zebrafish NAFLD model showed that Tet significantly reduced hepatic lipid accumulation and decreased serum TG, TC, ALT, and AST levels. Mechanistically, Tet activated PI3K/AKT/STAT3 signaling while inhibiting TP53 and Bax. External validation using GEO datasets supported AKT1 and EGFR as important regulatory genes. Overall, these findings demonstrated that Tet ameliorates NAFLD by modulating lipid metabolism and apoptosis through activation of the PI3K/AKT/STAT3 signaling pathway, providing integrated computational, genetic, and experimental evidence for its potential as a therapeutic agent.