Predicting human glucose response curve using an engineered small intestine system in combination with mathematical modeling

Priyadarshini, S.; Elumalai, A.; Moses, J.A.; Anandharamakrishnan, C.

doi:10.1016/j.jfoodeng.2020.110395

Cited by 8 publications

(5 citation statements)

References 50 publications

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“…The limits of agreement were within -24•52 and 22•63, corresponding to the lower and upper limits, respectively (Fig. 8) (166) . This system combines in vitro, ex vivo and in silico approaches.…”

Section: Relevance To In Vivo Recordsmentioning

confidence: 64%

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Determining the glycaemic responses of foods: conventional and emerging approaches

2021

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A low-glycemic diet is crucial for those with diabetes and cardiovascular diseases. Information on the glycemic index (GI) of different ingredients can help in designing novel food products for such target groups. This is because of the intricate dependency of material source, composition, food structure, and processing conditions, among other factors, on the glycemic responses. Different approaches have been used to predict the GI of foods, certain discrepancies exist because of factors including the inter-individual variation among human subjects. Besides other aspects, it is important to understand the mechanism of food digestion because an approach to predict GI must essentially mimic the complex processes in the human gastrointestinal tract. The focus of this work is to review the advances in various approaches for predicting the glycemic responses of foods. This has been explained by detailing conventional approaches, their merits and limitations, and the need to focus on emerging approaches. Given the fact that no single approach can be generalized for all applications, the review emphasizes the scope of deriving insights for improvements in methodologies. Reviewing the conventional and emerging approaches for the determination of GI in foods, this detailed work is intended to serve as a state-of-the-art resource for food and nutritionists who work on developing low GI foods.

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Section: Relevance To In Vivo Recordsmentioning

confidence: 64%

“…8. Validation of predicted oral glucose tolerance test using engineered small intestine system (166)…”

Section: Discussionmentioning

confidence: 99%

Determining the glycaemic responses of foods: conventional and emerging approaches

2021

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“…Apparent permeability provides the first approximation of the rate of a compound's ability to cross the intestinal barrier effectively. 29 In this study, the apparent permeability coefficient ( P app ) of perfusate transport across the rat small intestinal epithelial cells was calculated from the steady-state level of the perfusate diffusing out of the intestinal segment using eqn (1) as follows: 30,31 where Q is the amount of the compound ( e.g. , glucose) present in the receptacle outside the intestinal sac, mg; A is the effective surface area of the intestinal sac available for diffusion, cm 2 ; C i and C 0 represent the compound concentration inside and outside the intestinal sac at the initial time ( t = 0), mg mL −1 ; and Q normalized represents the normalized Q considering the minor differences in the surface area of the intestinal sac and the initial concentration of the compound in/outside the intestinal sac, cm.…”

Section: Methodsmentioning

confidence: 99%

Section: Food and Function Papermentioning

confidence: 99%

Intestinal absorption of DHA microcapsules with different formulations based onex vivorat intestine andin vitrodialysis models

Chen

et al. 2023

Food Funct.

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“…[8][9][10] For in vitro systems, it is difficult to implement complex geometrical features of a real small intestine, such as circular folds and villi, which affect the flow pattern and thus the mass transfer. 11,12 Even if some research groups used excised animal intestinal tissues 13 or cultured epithelial cell monolayer, 14 various movements of the intestinal walls, for example, segmentation and peristalsis, can hardly be implemented in those experiments.…”

Section: Introductionmentioning

confidence: 99%

New understanding from intestinal absorption model: How physiological features influence mass transfer and absorption

Qin

Chen

et al. 2023

AIChE Journal

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Mathematical modeling of mass transfer and absorption in the small intestine has been a challenging task. Systematic review and analysis of existing efforts indicate the need to pursue a reliable predictive model that is physically sound and computationally efficient. With the consideration of 3D intestinal inner wall structure, this work rigorously derives an absorption model that can be used as a source term in a 1D distributed model, conventionally called the diffusion–convection–reaction model. Moreover, computational fluid dynamics simulations are carried out to generate in silico experimental data for quantification of the mass‐transfer coefficient in the absorption model. This model facilitates a better understanding of the intricate influence of intestinal morphology and motility on mass transfer and absorption in the intestine. Rat duodenum featuring a villous structure and pendular movement is selected as an example to demonstrate the capability of this approach.

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Predicting human glucose response curve using an engineered small intestine system in combination with mathematical modeling

Cited by 8 publications

References 50 publications

Determining the glycaemic responses of foods: conventional and emerging approaches

Determining the glycaemic responses of foods: conventional and emerging approaches

Intestinal absorption of DHA microcapsules with different formulations based onex vivorat intestine andin vitrodialysis models

New understanding from intestinal absorption model: How physiological features influence mass transfer and absorption

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