Gut‐Targeted Nutraceutical Delivery: Engineering Microbiome‐Responsive Nutraceutical Interfaces
J Renukadevi, M. Ranjani, P. Sneha, Jahir Hussain, Harikrishnan Shakthi
Saveetha University
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
The gut microbiome plays a central role in maintaining host health, influencing immunity, metabolism, epithelial integrity, and the gut–brain axis. Dysbiosis of this complex microbial ecosystem is implicated in a variety of chronic diseases, including inflammatory bowel disease, metabolic syndrome, and neurological disorders. Nutraceuticals such as prebiotics, polyphenols, probiotics, postbiotics, bioactive peptides, and micronutrients—hold promise for restoring microbial homeostasis and supporting gut health. However, their clinical utility is limited by poor stability, premature degradation in the upper gastrointestinal tract, and variability in microbiome composition. Recent advances in microbiome‐responsive delivery systems have addressed these challenges by engineering smart platforms that synchronize bioactive release with the unique biochemical signals of the gut, including pH gradients, microbial enzymes, redox cues, and fermentation‐driven changes. These innovative systems, incorporating pH‐sensitive hydrogels, enzyme‐ and redox‐responsive nanogels, hybrid polymer carriers, synbiotic co‐encapsulation, functional food matrices, and edible coatings, enhance nutraceutical stability, bioavailability, and site‐specific action. Preclinical and emerging clinical evidence demonstrates their potential to modulate the microbiome, attenuate inflammation, and promote mucosal healing. Despite encouraging progress, translational hurdles—such as limited human trials, regulatory uncertainties, and interindividual variability—must still be overcome. This review comprehensively explores the design principles, mechanisms, applications, and future perspectives of microbiome‐responsive nutraceutical interfaces, highlighting their transformative potential in advancing personalized gut health interventions.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
生物医学Gut microbiota and health
Diet and metabolism studies · 3D Printing in Biomedical Research
参考文献 93
此处列出前 3 条
引用本文 16
按被引量排序,此处列出前 3 条