2020
DOI: 10.3390/pharmaceutics12040296
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Effect of Food and an Animal’s Sex on P-Glycoprotein Expression and Luminal Fluids in the Gastrointestinal Tract of Wistar Rats

Abstract: The rat is one of the most commonly used animal models in pre-clinical studies. Limited information between the sexes and the effect of food consumption on the gastrointestinal (GI) physiology, however, is acknowledged or understood. This study aimed to investigate the potential sex differences and effect of food intake on the intestinal luminal fluid and the efflux membrane transporter P-glycoprotein (P-gp) along the intestinal tract of male and female Wistar rats. To characterise the intestinal luminal fluid… Show more

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Cited by 21 publications
(23 citation statements)
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“…This difference could also be responsible for differences in the concentration of drug and PEG 400 in the intestinal lumen in humans, which in turn could affect transit and permeability between the sexes. If we take into consideration that we are observing similar effects of PEG 400 in rats and humans, and given the considerable difference between the rat and human GI luminal environment, we do not believe sex differences in GI luminal environment (Dou et al, 2020) could be the cause for pronounced difference in the way males and females of both species react to PEG 400.…”
Section: Discussionmentioning
confidence: 98%
See 1 more Smart Citation
“…This difference could also be responsible for differences in the concentration of drug and PEG 400 in the intestinal lumen in humans, which in turn could affect transit and permeability between the sexes. If we take into consideration that we are observing similar effects of PEG 400 in rats and humans, and given the considerable difference between the rat and human GI luminal environment, we do not believe sex differences in GI luminal environment (Dou et al, 2020) could be the cause for pronounced difference in the way males and females of both species react to PEG 400.…”
Section: Discussionmentioning
confidence: 98%
“…In order to understand the potential mechanism as to why sex-related differences in drug bioavailability may occur, a number of studies have demonstrated that the intestinal efflux transporter, P-glycoprotein (P-gp) is differentially expressed between the sexes in an animal model (Dou et al, 2020;Dou et al, 2018;Mai et al, 2018a;Mai et al, 2018c). P-gp is postulated to serve as an essential protective mechanism in the intestinal luminal environment by heavily mediating oral drug absorption.…”
Section: Introductionmentioning
confidence: 99%
“…This difference could also be responsible for differences in the concentration of drug and PEG 400 in the intestinal lumen in humans, which in turn could affect transit and permeability between the sexes. If we take into consideration that we are observing similar effects of PEG 400 in rats and humans, and given the considerable difference between the rat and human GI luminal environment, we do not believe sex differences in GI luminal environment [28] could be the cause for pronounced difference in the way males and females of both species react to PEG 400.…”
Section: Discussionmentioning
confidence: 98%
“…In order to understand the potential mechanism as to why sex-related differences in drug bioavailability may occur, a number of studies have demonstrated that the intestinal efflux transporter, P-glycoprotein (P-gp) is differentially expressed between the sexes in an animal model [28][29][30][31]. P-gp is postulated to serve as an essential protective mechanism in the intestinal luminal environment by heavily mediating oral drug absorption.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, specialists in the field must rely on their knowledge to adapt formulations to suit the pharmaceutical needs of the individual [50]. There are many factors to consider during personalised formulation design, some include: patient's swallowing capacity, flavour preferences, required drug dose, required drug release kinetics, presence of disease, sex, age, motor skills, and coadministered medications [184][185][186][187][188][189][190][191][192][193][194][195][196][197][198][199]. ML has the capacity to consider all these factors and predict optimal formulation design features based on an individual's requirements [154,[200][201][202].…”
Section: Machine Learning In the Pre-printing Stagementioning
confidence: 99%