Natural products and integrative technologies in cardiovascular protection, regeneration, and disease modeling

Cardiovascular diseases remain the predominant cause of morbidity and mortality worldwide, encompassing a wide spectrum of conditions such as myocardial infarction, cardiomyopathy, heart failure, and myocarditis. Despite advances in clinical management, effective strategies to achieve cardiac protection, repair, and regeneration are still insufficient. This ongoing challenge highlights the urgent need for innovative, mechanism-based therapeutic approaches. Recent years have seen growing interest in natural products, which provide a rich and chemically diverse source of bioactive molecules with the potential to modulate complex signaling networks underlying cardiovascular pathologies. Emerging evidence demonstrates that natural compounds can influence critical processes including inflammation, fibrosis, metabolic remodeling, and regenerative capacity. Nevertheless, a comprehensive understanding of their mechanisms of action and translational relevance remains lacking. In parallel, rapid progress in experimental and computational techniques—including genetic models, induced pluripotent stem cell (iPSC)-derived cardiovascular systems, multi-omics profiling, and artificial intelligence (AI)—is transforming our ability to decipher disease mechanisms and accelerate therapeutic discovery.This Research Topic aims to provide an integrated and interdisciplinary platform to connect natural products research with cutting-edge cardiovascular biology and emerging technologies. The principal objective is to promote mechanistic and translational insights into the roles of natural compounds and bioactive molecules in the context of cardiac protection, regeneration, remodeling, and inflammatory processes such as myocarditis. We invite submissions spanning multiple biological scales and model systems, including in vivo animal models (e.g., genetically engineered mice), in vitro platforms (such as iPSC-derived cardio systems), and advanced computational methodologies.To further advance this field, we particularly encourage contributions that:Uncover molecular and transcriptional mechanisms underlying cardiovascular disease and tissue regenerationIntegrate multi-omics and systems-level analyses to dissect complex pathwaysApply AI or machine learning to drug discovery and target identification in cardiac researchLeverage advanced experimental models for rigorous functional validationBridge basic mechanistic findings with translational, preclinical, or clinical applicationsTo gather comprehensive insights within these boundaries, we welcome submissions addressing, but not limited to, the following themes:• Molecular mechanisms of natural products in cardiovascular protection and repair• Natural product-mediated modulation of inflammation, fibrosis, and remodeling• Application of iPSC-derived cardiovascular systems for drug screening and mechanistic studies• Integration of multi-omics and bioinformatics for target and pathway discovery• The use of artificial intelligence and machine learning in natural products research• Translational research bridging experimental findings to clinical relevance• Methodological advances in experimental models and preclinical validationWe welcome original research articles, reviews, mini-reviews, perspectives, and methodological contributions.Please note:All contributions to this Research Topic must adhere to the Four Pillars of Best Practice in Ethnopharmacology and the ConPhyMP statement (Front. Pharmacol., 13:953205). Manuscripts must include detailed descriptions of biological material, extraction methods, and processing procedures; submissions lacking these details will be desk-rejected. The full best-practice guidance is available at: https://ga-online.org/best-practice.Authors are encouraged to self-assess their manuscripts using the ConPhyMP tool before submission.The following types of submissions fall outside the scope of this Research Topic:• In silico network pharmacology studies of complex mixtures that lack experimental or functional validation (note: AI/machine learning approaches integrated with in vitro, in vivo, or clinical data are welcome)• Studies reporting only chemical antioxidant assays (e.g., DPPH, ABTS) without pharmacological target identification or mechanistic follow-up relevant to cardiovascular pathology• Small molecules exhibiting in silico or in vitro effects but without specific pharmacological targets relevant to cardiovascular disease• Bibliometric or scientometric analyses Topic editors: Xiaoxin Chen, Huiliang Qiu, Yuanyuan Cheng, Kentaro Hirose Source: https://www.frontiersin.org/research-topics/80252/natural-products-and-integrative-technologies-in-cardiovascular-protection-regeneration-and-disease-modeling