title: A method for modeling growth of organs and transplants based on the general growth law: application to the liver in dogs and humans.
abstract: Understanding biological phenomena requires a systemic approach that incorporates different mechanisms acting on different spatial and temporal scales, since in organisms the workings of all components, such as organelles, cells, and organs interrelate. This inherent interdependency between diverse biological mechanisms, both on the same and on different scales, provides the functioning of an organism capable of maintaining homeostasis and physiological stability through numerous feedback loops. Thus, developing models of organisms and their constituents should be done within the overall systemic context of the studied phenomena. We introduce such a method for modeling growth and regeneration of livers at the organ scale, considering it a part of the overall multi-scale biochemical and biophysical processes of an organism. Our method is based on the earlier discovered general growth law, postulating that any biological growth process comprises a uniquely defined distribution of nutritional resources between maintenance needs and biomass production. Based on this law, we introduce a liver growth model that allows to accurately predicting the growth of liver transplants in dogs and liver grafts in humans. Using this model, we find quantitative growth characteristics, such as the time point when the transition period after surgery is over and the liver resumes normal growth, rates at which hepatocytes are involved in proliferation, etc. We then use the model to determine and quantify otherwise unobservable metabolic properties of livers.
authors.affiliation: Research and Development Lab, Segmentsoft Inc., Toronto, Ontario, Canada.
authors.forename: Yuri K
authors.initials: YK
authors.lastname: Shestopaloff
authors.affiliation: MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.
authors.forename: Ivo F
authors.initials: IF
authors.lastname: Sbalzarini
mesh_terms: D000465:Algorithms; D000818:Animals; D004285:Dogs; D005260:Female; D006801:Humans; D008099:Liver / Q000254:growth & development*; D016031:Liver Transplantation; D008297:Male; D023421:Models, Animal; D008954:Models, Biological; D009929:Organ Size; D013997:Time Factors