{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T11:38:47Z","timestamp":1792582727491,"version":"4.5.0"},"reference-count":29,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T00:00:00Z","timestamp":1792540800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T00:00:00Z","timestamp":1792540800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["QN25H280047"],"award-info":[{"award-number":["QN25H280047"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LQN25H310003"],"award-info":[{"award-number":["LQN25H310003"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"award":["QN25H280047"],"award-info":[{"award-number":["QN25H280047"]}],"id":[{"id":"https:\/\/ror.org\/04aqat463","id-type":"ROR","asserted-by":"publisher"}]},{"award":["LQN25H310003"],"award-info":[{"award-number":["LQN25H310003"]}],"id":[{"id":"https:\/\/ror.org\/04aqat463","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82505303"],"award-info":[{"award-number":["82505303"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["82505303"],"award-info":[{"award-number":["82505303"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Medical Health Science and Technology Project of Zhejiang Province","award":["2025KY650"],"award-info":[{"award-number":["2025KY650"]}]},{"name":"Traditional Chinese Medicine Science and Technology Project of Zhejiang Province","award":["2026ZF24"],"award-info":[{"award-number":["2026ZF24"]}]},{"name":"Basic Scientific Research Funds of Department of Education of Zhejiang Province","award":["KYQN2024005"],"award-info":[{"award-number":["KYQN2024005"]}]},{"award":["KYQN2024005"],"award-info":[{"award-number":["KYQN2024005"]}],"id":[{"id":"https:\/\/ror.org\/05gj07w56","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Zhejiang Pharmaceutical Association Hospital Pharmacy Special Research Funding","award":["2025ZYY54"],"award-info":[{"award-number":["2025ZYY54"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>Background: Linking metabolite composition to biological activities remains challenging in herbal medicines, where diverse metabolites may collectively contribute to pharmacological effects. Although metabolite profiling is fundamental to quality assessment, conventional quality evaluation often provides limited information on how variation in metabolite composition relates to biological activities. Objectives: This study aimed to develop a multi-component\u2013multi-bioactivity framework integrating metabolite profiling and bioactivity assessment, enabling bidirectional mapping between metabolite composition and biological responses and providing a functional perspective for quality characterization of complex herbal medicines. Salvia miltiorrhiza Bunge (Danshen), a widely used medicinal plant with a chemically diverse metabolome and well-documented cardiovascular activities, was selected as a representative model system. Methods: Quantitative 1H NMR spectroscopy was employed to profile 28 metabolites in Danshen, while zebrafish-based bioassays were used to assess three cardiovascular-related bioactivities: pro-angiogenic, anti-thrombotic, and vasodilatory activities. A lifecycle-oriented approach was introduced for bioassay development to improve the robustness and reproducibility of biological measurements. Multiple machine learning approaches were integrated within a two-level stacking ensemble framework to construct quantitative metabolite\u2013bioactivity relationship models and capture nonlinear associations between metabolite composition and biological activities. Results: The stacked models consistently outperformed the individual learners across the three cardiovascular bioactivities, achieving R2 values of 0.895\u20130.931 and RMSE values of 0.116\u20130.130. External validation using 10 independent Danshen samples further supported the predictive reliability of the stacked models. Based on model-derived metabolite contributions, a quantitative and interpretable metabolite\u2013bioactivity network linking 28 metabolites with three cardiovascular-related activities was constructed, revealing both shared and activity-specific metabolic contributors. Conclusions: This study establishes an interpretable framework integrating NMR-based metabolite profiling, robust multi-endpoint bioassays, and ensemble learning to connect metabolite composition with functional bioactivity. The framework provides a complementary bioactivity-informed perspective for the quality characterization of medicinal plants and supports systems-level evaluation of complex herbal medicines.<\/jats:p>","DOI":"10.3390\/metabo16100798","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T10:20:38Z","timestamp":1792578038000},"page":"798","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Interpretable Ensemble-Learning Framework for Decoding Multi-Component\u2013Multi-Bioactivity Relationships in Salvia miltiorrhiza Based on 1H NMR Metabolomics and Lifecycle-Oriented Bioassays"],"prefix":"10.3390","volume":"16","author":[{"given":"Wenzhu","family":"Li","sequence":"first","affiliation":[{"name":"Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People\u2019s Hospital (Affiliated People\u2019s Hospital), Hangzhou Medical College, Hangzhou 310014, China"},{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China"},{"name":"State Key Laboratory of Component-Based Chinese Medicine, Innovation Center in Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]},{"given":"Shasha","family":"Li","sequence":"additional","affiliation":[{"name":"Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People\u2019s Hospital (Affiliated People\u2019s Hospital), Hangzhou Medical College, Hangzhou 310014, 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University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"supervision","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"given":"Nan","family":"Wang","sequence":"additional","affiliation":[{"name":"Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People\u2019s Hospital (Affiliated People\u2019s Hospital), Hangzhou Medical College, Hangzhou 310014, China"},{"name":"College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"}]},{"given":"Jiana","family":"Shi","sequence":"additional","affiliation":[{"name":"Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People\u2019s Hospital (Affiliated People\u2019s Hospital), Hangzhou Medical College, Hangzhou 310014, 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