In Vitro Models for Studying Secondary Plant Metabolite Digestion and Bioaccessibility

消化(炼金术) 生物利用度 多酚 类胡萝卜素 化学 生物化学 食品科学 体外 生物 色谱法 药理学 抗氧化剂
作者
Marie Alminger,Anna-M. Aura,Torsten Bohn,Claire Dufour,Sedef Nehir El,Andréia Gomes,Sibel Karakaya,M. Carmen Martínez-Cuesta,Gordon J. McDougall,Teresa Requena,Cláudia N. Santos
出处
期刊:Comprehensive Reviews in Food Science and Food Safety [Wiley]
卷期号:13 (4): 413-436 被引量:304
标识
DOI:10.1111/1541-4337.12081
摘要

Abstract There is an increased interest in secondary plant metabolites, such as polyphenols and carotenoids, due to their proposed health benefits. Much attention has focused on their bioavailability, a prerequisite for further physiological functions. As human studies are time consuming, costly, and restricted by ethical concerns, in vitro models for investigating the effects of digestion on these compounds have been developed and employed to predict their release from the food matrix, bioaccessibility, and assess changes in their profiles prior to absorption. Most typically, models simulate digestion in the oral cavity, the stomach, the small intestine, and, occasionally, the large intestine. A plethora of models have been reported, the choice mostly driven by the type of phytochemical studied, whether the purpose is screening or studying under close physiological conditions, and the availability of the model systems. Unfortunately, the diversity of model conditions has hampered the ability to compare results across different studies. For example, there is substantial variability in the time of digestion, concentrations of salts, enzymes, and bile acids used, pH, the inclusion of various digestion stages; and whether chosen conditions are static (with fixed concentrations of enzymes, bile salts, digesta, and so on) or dynamic (varying concentrations of these constituents). This review presents an overview of models that have been employed to study the digestion of both lipophilic and hydrophilic phytochemicals, comparing digestive conditions in vitro and in vivo and, finally, suggests a set of parameters for static models that resemble physiological conditions.

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