4.7 Article

A Physiological-Based Model for Simulating the Bioavailability and Kinetics of Sulforaphane from Broccoli Products

期刊

FOODS
卷 10, 期 11, 页码 -

出版社

MDPI
DOI: 10.3390/foods10112761

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physiological-based model; sulforaphane; glucoraphanin; compartmental model; broccoli; bioavailability; myrosinase; parameter estimation

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This study developed a physiological-based digestion model to simulate the conversion of glucoraphanin to sulforaphane and evaluate its bioavailability in the human body. The model accurately predicted sulforaphane formation in different broccoli products and could serve as a foundation for predicting the biological effects of sulforaphane in personalized nutrition.
There are no known physiological-based digestion models that depict glucoraphanin (GR) to sulforaphane (SR) conversion and subsequent absorption. The aim of this research was to make a physiological-based digestion model that includes SR formation, both by endogenous myrosinase and gut bacterial enzymes, and to simulate the SR bioavailability. An 18-compartment model (mouth, two stomach, seven small intestine, seven large intestine, and blood compartments) describing transit, reactions and absorption was made. The model, consisting of differential equations, was fit to data from a human intervention study using Mathwork's Simulink and Matlab software. SR urine metabolite data from participants who consumed different broccoli products were used to estimate several model parameters and validate the model. The products had high, medium, low, and zero myrosinase content. The model's predicted values fit the experimental values very well. Parity plots showed that the predicted values closely matched experimental values for the high (r(2) = 0.95), and low (r(2) = 0.93) products, but less so for the medium (r(2) = 0.85) and zero (r(2) = 0.78) myrosinase products. This is the first physiological-based model to depict the unique bioconversion processes of bioactive SR from broccoli. This model represents a preliminary step in creating a predictive model for the biological effect of SR, which can be used in the growing field of personalized nutrition.

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