We have a new part of the digital twin published! This time the new part, or sub-model, concerns the fat-driven disease etiology in the liver, based on fat fluxes in and out of the liver (Fig B below). As can be seen in Fig A, the model agrees with data for MRS PDFF, which is a magnetic resonance-based way of measuring liver fat, as well as with data for De novo lipogenesis (DNL), and e.g. ketone production and VLDL-TAG (Fig 2C-D in the paper). As usual, the model can describe data from different clinical studies, covering different diet and drug interventions in different cohorts, and the model can also successfully predict new data not used for training. This new sub-model is now being connected with the other meal and drug response models in the overall digital twin backend, and will thus become an integrated part of the future digital twin applications.
Full reference: A unified framework for prediction of liver steatosis dynamics in response to different diet and drug interventions. Simonsson C, Nyman E, Gennemark P, Gustafsson P, Hotz I, Ekstedt M, Lundberg P, Cedersund G.Clin Nutr. 2024 Jun;43(6):1532-1543. doi: 10.1016/j.clnu.2024.05.017
