Digital twin predicting diet response before and after long-term fasting
Fig 2
Model features compared to previous model.
(A) Overview of the qualitative predictions and improvements in new model, compared to previous models. Previous models can only either i) ignore protein ingestion in glucose simulations, or ii) have a static formula for a phenomenological conversion between protein and plasma glucose, which incorrectly increases the hepatic glucose uptake. In contrast, iii) in the new model, we can have a protein-induced increase in gluconeogenesis and hepatic glucose production, which is much larger after fasting than in a fed state. The arrows and their sizes represent the qualitative relationships between the fluxes between plasma glucose and plasma liver during the second OPTT response, for the three model alternatives. (B) Experimental data (error bars) validating another key difference between the new (blue line) and old model simulations (orange line): the decrease of plasma glucose during fasting. (C) New model (blue line) can describe all of the mechanistic flux data (error bars) that led to the ‘Dalla Man model’ [21], equally as well as that model and its subsequent improvements (orange line). The data shows responses to a mixed meal at 0.5 h (black bar). (D) Examples of predictions of key mechanistic variables that new model can produce, which the original Dalla Man model and its subsequent improvements (including [23]) cannot produce. (E) Qualitative aspects of metabolism compared to simulations, where predictions (blue filled bars) are compared to data (grey filled bars) for organ-specific glucose uptake (i, [32]), organ-specific endogenous glucose production (EGP) (ii,[35]), and insulin clearance (iii, [33]). Model uncertainty is represented as error bars on blue filled bars, and error bars on grey filled bars are qualitative reasonable intervals of each respective metabolic flow or reaction.