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- W2098779716 abstract "The influence of protein source on postprandial urea kinetics is poorly understood, despite its nutritional significance with respect to nitrogen homeostasis. Furthermore, traditional tracer infusion studies underestimate acute postprandial change in urea kinetics.We investigated postprandial, non-steady state urea kinetics and their modulation by qualitative and quantitative factors of protein intake by the combined use of robust clinical data on nitrogen postprandial distribution and mathematical modeling.In healthy subjects standardized to a normal protein intake for 7 d, dietary and total nitrogen kinetics were measured for 8 h in plasma proteins, body, and urinary urea after the ingestion of a (15)N-labeled milk (n = 8), soy (n = 8), or wheat (n = 8) protein meal. In subjects who received the soy protein meal, these postprandial measurements were repeated after a further 7-d adaptation to a high protein intake. A 4-compartment model was developed to calculate from these data the postprandial kinetics of production, urinary excretion, and intestinal hydrolysis of urea nitrogen from both dietary and endogenous sources.Urinary urea excretion was not influenced by the protein source in the meal but was influenced by the protein level in the diet. By contrast, urea production and hydrolysis were higher when ingesting plant versus animal protein, together with a higher efficiency of urea hydrolysis (50-60% versus 25% of the urea produced being hydrolyzed, respectively).We conclude that urea hydrolysis is an acute nitrogen-sparing mechanism that can counterbalance a postprandial higher urea production, and the efficiency of this recycling is higher when the usual protein intake is lower." @default.
- W2098779716 created "2016-06-24" @default.
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- W2098779716 date "2008-06-01" @default.
- W2098779716 modified "2023-10-16" @default.
- W2098779716 title "Urea-nitrogen production and salvage are modulated by protein intake in fed humans: results of an oral stable-isotope-tracer protocol and compartmental modeling" @default.
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- W2098779716 doi "https://doi.org/10.1093/ajcn/87.6.1702" @default.
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